Stratalize Healthcare Intelligence

Verify current crypto asset price via multi-source consensus. Returns attested consensus price with agreement score across independent sources (CoinGecko, Binance, Kraken).

Resolve whether a crypto asset is above or below a threshold via multi-source consensus for settlement and verification workflows.

Use when a CFO or procurement team needs to know if they are overpaying for any software vendor. Returns monthly_median, monthly_low, monthly_high, annual_median, pricing_model, source, and data_as_of from healthcare vendor benchmark lookups with Stratalize composite medians as fallback when no vendor-specific row exists. Example: Salesforce CRM median ~$8,400/mo — organizations above the monthly_high range are overpaying by a recoverable margin. Source: healthcare_vendor_benchmarks with Stratalize composite medians.

Use when benchmarking total spend in a software category against same-size peers. Returns median monthly spend, p25/p75 band, and sample size for any software category by company size. Example: Mid-market CRM spend median ~$3,500/mo, p75 of $4,900 — organizations above p75 have a negotiation mandate supported by market data. Source: Stratalize enterprise spend composite.

Use when preparing to renew or renegotiate a SaaS contract. Returns typical discount percentage, best negotiation windows, leverage points, auto-renewal risk flags, and a negotiation script for any vendor. Example: Salesforce renewals average 12-18% discount when initiated 90 days before renewal with multi-year commit — Q4 close urgency adds 5-8% additional leverage. Source: Stratalize procurement intelligence composite.

Use when building a vendor shortlist for a new software category purchase. Returns vendors ranked by mention count and median spend from enterprise spend data. Example: HR tech category — Workday median $42K/mo, BambooHR $3,200/mo, Rippling $8,400/mo — 13x spend spread between enterprise and SMB confirms size-appropriate shortlisting. Source: Stratalize market composite.

Use when evaluating a vendor switch or building a competitive RFP against an incumbent. Returns alternative vendors with migration complexity scores, estimated savings, and switching narrative. Example: Salesforce alternatives — HubSpot at 22% lower median spend with comparable CRM coverage, Pipedrive at 41% lower for sales-only — migration complexity rated MEDIUM for both. Source: Stratalize competitive displacement composite.

Use when a major SaaS contract is approaching renewal or auto-renewal risk. Returns timing strategy, leverage points, walk-away alternatives, and a complete negotiation script for any vendor. Example: Datadog renewal — initiate 90 days before, cite Grafana Cloud at 40% lower cost as walk-away, target 15-20% discount — Q4 close adds urgency leverage. Source: Stratalize procurement intelligence.

Use when sizing a technology budget for a specific industry and headcount, or identifying category spend outliers. Returns spend bands, category ranges, and outlier flags scaled to employee count. Example: 500-person healthcare org — total SaaS stack median $1.2M/yr, EHR 34% of spend, clinical productivity tools 18% — organizations above $1.8M are consolidation candidates. Source: Stratalize workforce-scaled composite.

Use when reviewing a new vendor agreement or benchmarking contract terms before a negotiation. Returns typical contract length, auto-renewal notice window, price escalation percentage, and key risk clauses for any major vendor. Example: Salesforce standard — 36-month term, 60-day auto-renewal notice, 7% annual escalation — missing the 60-day window costs 12 months of negotiation leverage. Source: Stratalize contract intelligence composite.

Use when benchmarking software category spend against same-size organizations before a purchase or renewal. Returns SMB, mid-market, and enterprise median monthly spend for any software category. Example: CRM median spend — SMB $1,200/mo, mid-market $8,400/mo, enterprise $42,000/mo — 35x spread confirms size-appropriate benchmarking before any negotiation. Source: Stratalize size-segmented composite.

Use when evaluating a new software purchase or reviewing a vendor quote for hidden costs. Returns common pricing models, hidden cost patterns, implementation cost ranges, and budget guidance by category. Example: CRM hidden costs — API overage $0.02/call adds $8,400/yr at 420K monthly calls, sandbox $1,200/mo additional, SSO integration $15K one-time — total cost 40% above list price. Source: Stratalize category pricing composite.

Use when assessing brand visibility in AI-generated recommendations or researching which vendors dominate AI platform responses in a software category. Returns vendors ranked by unprompted AI mention frequency. Example: CRM category — Salesforce 42 mentions across 100 queries, HubSpot 28, Microsoft Dynamics 14 — Salesforce dominates AI recommendations by 50% over nearest competitor. Source: Stratalize AI citation index.

Use when identifying gaps between AI platform recommendations and actual market position for a vendor or topic. Returns platform agreement score showing consistency across AI platforms. Example: Salesforce scores 0.91 agreement across ChatGPT, Claude, Gemini, Perplexity — near-universal consensus. Niche vendors often score below 0.50 — high divergence signals a content gap opportunity. Source: Stratalize multi-platform citation composite.

Use when monitoring a vendor brand trajectory in AI recommendations or tracking week-over-week competitor momentum for a CMO brief. Returns 4-week momentum score, trend direction, and weekly movement series. Example: HubSpot 4-week momentum +1.8, GROWING trend — 3 consecutive weeks of citation increase following major product launch — competitive signal requiring CMO attention. Source: Stratalize brand index.

Use when researching how AI systems characterize a vendor, category, trend, or business topic across multiple platforms simultaneously. Returns consensus score, sentiment mix, key themes, and platform-by-platform breakdown. Example: AI in healthcare scores 0.78 consensus — key themes: clinical decision support, administrative automation, prior auth reduction — high consensus signals established narrative safe for board communications. Source: Stratalize AI citation composite.

Use when benchmarking hospital operating costs against CMS peer cohort or preparing a healthcare CFO board presentation. Returns peer_group context, benchmark_percentiles, metadata, source attribution, and optional database_row detail from the matched CMS benchmark row by bed size, state, and hospital type. Example: 300-bed acute care hospital in Illinois — peer group and percentile outputs show where operating metrics sit versus cohort benchmarks. Source: CMS HCRIS cost reports.

Use when benchmarking payer performance, building a denial management strategy, or preparing revenue cycle board reporting. Returns denial rates by payer, prior authorization burden by specialty, and payer mix commentary. Example: Commercial payer denial rates — UnitedHealth 8.2%, Cigna 9.4%, Aetna 7.1% — prior auth burden 34% higher for specialist services — top quartile denial rate is 5.1%. Source: Stratalize national revenue cycle composite.

Use when advising on CMS Hospital Star Rating strategy or benchmarking a hospital quality performance trajectory. Returns domain weights, national distribution benchmarks, and improvement priorities. Example: Mortality domain weighted at 22% of overall star — hospitals moving 3 to 4 stars typically require 18-month mortality improvement program — 3-star hospitals represent 41% of the national distribution. Source: CMS Care Compare methodology.

Use when benchmarking hospital pharmacy costs or building a pharmacy cost reduction strategy for a board presentation. Returns drug cost per adjusted patient day, 340B savings opportunity, specialty drug drivers, and GPO targets by bed size. Example: 250-bed community hospital — drug cost $287/adjusted patient day vs $241 peer median — 340B eligibility could recover $1.8M annually — specialty drugs driving 61% of cost variance. Source: CMS cost report composite and 340B Health public data.

Use when assessing coding compliance risk before an OIG audit, preparing for a RAC review, or building a revenue integrity program. Returns E/M distribution benchmarks, upcoding risk signals, OIG audit priority themes, and RAC watchlist. Example: Cardiology practice E/M mix at 67% level 4/5 visits vs 48% national benchmark — flagged HIGH upcoding risk — OIG cardiology audit focus active in 2024-2025 cycle. Source: CMS and OIG compliance composite.

Use when benchmarking VBC contract performance, assessing FFS-to-VBC transition readiness, or preparing a population health strategy presentation. Returns MSSP ACO savings rates, BPCI episode costs, and MIPS quality signal medians. Example: MSSP Track 1 ACOs generating median 2.3% savings above benchmark — top quartile at 4.8% — organizations below 1.5% savings face program exit risk. Source: CMS VBC program data composite.

Use when benchmarking travel nurse contract rates or negotiating with a staffing agency. Returns bill-rate medians and bands by specialty and state. Example: ICU travel nurse median bill rate $95/hr in Illinois, p75 $108/hr — agencies billing above $115/hr are 21% above market — renegotiation typically recovers $180K-$240K annually per 10 FTE travelers. Source: BLS and Stratalize SIA-style composite.

Use when benchmarking EHR maintenance costs before a contract renewal or evaluating health IT budget efficiency. Returns benchmark cost per licensed bed with optional gap analysis when actual cost and bed count are provided. Example: Epic maintenance median $4,500/bed — 300-bed hospital at $6,200/bed is 38% above market — renegotiation trigger especially strong at 5+ year renewal cycles. Source: KLAS 2024, Kaufman Hall EHR TCO composite.

Use when benchmarking a healthcare vendor quote or preparing a supply chain contract negotiation. Returns market rates for EHR, staffing, food service, waste management, and med-surg by facility type. Example: Healthcare food service median $18.40/patient day for acute care — facilities above $22/patient day are 20% above market — GPO competitive rebid typically recovers 8-12%. Source: CMS and Stratalize healthcare vendor composite.

Use when evaluating staffing agency pricing or negotiating a travel nurse or locum contract. Returns median markup percentage with low/high band by agency and specialty type. Example: AMN Healthcare median markup 40%, Cross Country 37%, Aya 38% — ICU and OR specialties carry 5-8% premium — agencies billing above 45% markup are 12-18% above market. Source: Stratalize SIA 2024-style composite.

Use when benchmarking GPO contract performance or building a supply chain cost reduction case for a hospital board. Returns typical GPO savings percentage, leakage rate, and top savings categories. Example: Acute care GPO median savings 18% vs non-contract pricing — leakage rate 22% means 1-in-5 purchases bypass contract — leakage above 30% triggers mandatory compliance programs at most health systems. Source: HFMA and CMS composite.

Use when evaluating physician employment agreements, benchmarking compensation for recruitment, or preparing a medical staff compensation report. Returns median total compensation by specialty and state from BLS OES 2024 data. Example: Illinois cardiologist median $461K total compensation — interventional cardiology 34% above general cardiology — organizations below 25th percentile face retention risk in competitive markets. Source: BLS Occupational Employment Statistics.

Use when benchmarking hospital supply chain efficiency against CMS peer cohort or building a materials management cost reduction case. Returns supply cost as percentage of operating expense at p25/p50/p75 by bed size and state. Example: 200-bed community hospital — supply cost 19.4% of operating expense vs 16.8% peer median — closing the gap to median recovers $2.6M annually at $130M operating budget. Source: CMS HCRIS cost reports.

Use when benchmarking ASC financial performance, evaluating an ASC acquisition, or preparing an administrator board report. Returns cost per case medians and revenue mix percentages by specialty. Example: Orthopedic ASC cost per case median $4,200 — facilities above $5,100 are in the bottom cost quartile — orthopedic mix at 60% of cases maximizes margin vs ophthalmology-heavy mix. Source: ASCA and CMS 2024 composite.

Use when researching which vendors dominate AI recommendations in a healthcare technology category or validating a health IT vendor selection. Returns top recommended vendors, AI consensus narrative, and sample size from healthcare-specific citation analysis. Example: EHR category — Epic leads at 67% AI citation share, Oracle Health 18%, MEDITECH 9% — consensus near-universal for large health systems, fragmenting below 200 beds. Source: Stratalize AI citation composite.

Use when producing a quick industry intelligence brief or validating market narrative for a strategy deck. Returns AI-generated market summary, up to six key themes, and sentiment skew for any industry. Example: Healthcare IT market — POSITIVE sentiment 68%, key themes: EHR consolidation, AI-assisted coding, value-based care expansion — consolidation narrative dominant across 847 analyzed queries. Source: Stratalize AI citation composite.

Use when validating total IT spend against industry peers or building a software budget baseline for a CFO board presentation. Returns median monthly total software stack spend, category breakdown, and productivity tool medians by industry. Example: Mid-market healthcare org — median total SaaS spend $18,500/mo, EHR and clinical tools 41% of stack, productivity suite $2,800/mo — organizations above $26,000/mo are consolidation candidates. Source: Stratalize industry composite.

Use when assessing whether a software category faces near-term displacement risk, or timing a market entry or exit decision. Returns disruption risk score from 0 to 1 with evidence strings from citation volume patterns. Example: ERP category — disruption risk score 0.71, evidence: 34 citations referencing AI-native alternatives, 12 referencing no-code replacements — HIGH disruption risk for legacy on-premise vendors. Source: Stratalize citation volume heuristics.

Use when tracking competitive threats to an incumbent vendor or identifying switching trends in a software category. Returns vendors mentioned as replacements for a target vendor with switch narrative and mention counts. Example: Salesforce displacement — HubSpot replacing in SMB at 28 mentions, Dynamics replacing in enterprise at 19 — highest displacement pressure in mid-market 100-500 employees. Source: Stratalize citation displacement composite.

Use when screening a vendor for financial instability or procurement risk before a long-term contract commitment. Returns a risk score from 0 to 1 with risk indicators and negative mention evidence. Example: Vendor X scores 0.72 risk — indicators: customer churn citations, pricing disputes, product roadmap uncertainty — HIGH risk classification, recommend short-term contract only. Source: Stratalize citation risk composite.

Use when assessing software category maturity, timing a market entry, or evaluating consolidation risk in a category. Returns market structure signal (consolidating or fragmenting) with citation evidence. Example: HR tech category — CONSOLIDATING signal, top 3 vendors hold 71% of AI citation share — late-stage consolidation signals pricing power shift to incumbents. Source: Stratalize market structure composite.

Use when a current macro environment snapshot is needed for a trading brief, CFO board presentation, or investment committee context. Returns Fed funds rate, Treasury yields, CPI, PCE, and employment data when FRED API is configured. Example: Fed funds 5.33%, 10Y 4.42%, CPI 3.1% — rates and inflation above long-run targets, labor market tight — LATE-CYCLE positioning signal. Source: FRED St. Louis Fed, daily update.

Use when producing equity research, tracking brand share in AI sector coverage, or benchmarking a company AI visibility against sector peers. Returns top brands by AI mention share, sector trend narrative, and themed bullets for any equity sector. Example: Financials sector — JPMorgan leads at 34% citation share, Goldman 22%, BlackRock 18% — narrative focused on digital transformation and cost efficiency. Source: Stratalize AI citation composite.

Use when a technical trader needs wave counts, targets, and invalidation levels for major assets. Returns wave position, degree, target high/low, invalidation, and confidence for BTC, SPY, TLT, Gold. Example: Gold Wave 5 target $2,750, invalidation $2,520, confidence 62%.

Use when benchmarking portco technology spend for PE operating partners or building a software cost reduction case across a portfolio. Returns median software spend per company, category breakdown, and savings opportunity percentage. Example: Mid-market portco median $480K/yr — 18% savings opportunity through vendor consolidation — $86K/portco recovery across 10-company portfolio = $860K EBITDA improvement. Source: Stratalize PE Intelligence composite.

Use when assessing a SaaS category investment thesis, competitive dynamics, or market momentum before a strategic decision. Returns growth signal, AI citation leaders, and disruption risk for any software category. Example: CRM category — GROWING signal, Salesforce leads at 42% citation share, HubSpot gaining 8% share year-over-year, disruption risk MODERATE from AI-native CRMs — signals consolidation pressure on mid-tier vendors. Source: Stratalize market intelligence composite.

Use when evaluating VC software category attractiveness or assessing portfolio category exposure before an investment decision. Returns growth signal, top brands, and citation evidence for any software category. Example: AI infrastructure category — GROWTH signal, top brands Nvidia 67% citation share, Anthropic 18%, xAI 9% — accelerating citation growth signals sustained investment thesis. Source: Stratalize citation heuristics.

Use when conducting vendor diligence for a PE or VC portfolio company before a value creation initiative. Returns market rate data, brand index snapshot, and competitive displacement signals for any vendor. Example: Portco using Salesforce at $12,400/mo — market median $8,400/mo, 48% above market — immediate renegotiation opportunity with $48K annual EBITDA recovery. Source: Stratalize composite diligence.

Use when a CFO or procurement lead needs org-specific vendor pricing vs market before renewal or negotiation. Returns market_low, market_median, market_high, position_label, negotiation tactics, estimated_savings_monthly from benchmark_cache when fresh, or guidance to load intelligence in Stratalize. Example: Salesforce median ~$8,400/mo — recoverable gap when spend exceeds monthly_high. Source: benchmark_cache + Stratalize composites.

Use when benchmarking compensation against disclosed employer wages or assessing H-1B wage practices before a talent acquisition or competitive hire. Returns DOL LCA and H-1B wage aggregates by employer, job title, state, and fiscal year. Example: Microsoft H-1B software engineer — prevailing wage Level III $178K in Seattle, Level IV $215K — 847 certified positions in 2023, concentrated in Washington and California. Source: DOL Office of Foreign Labor Certification public filings.

Use when analyzing an employer H-1B compensation strategy or benchmarking tech sector wages against DOL prevailing wage data. Returns prevailing wage statistics, certified job titles, wage levels, and state distribution from DOL LCA filings. Example: Google H-1B — software engineer Level IV prevailing wage $195K, 1,243 certified positions in 2023 — concentrated in Mountain View and New York City offices. Source: DOL Labor Condition Application public data.

Use when evaluating hospital quality for a referral network decision, acquisition target assessment, or competitive quality analysis. Returns CMS Hospital Compare scores — safety, readmissions, patient experience, mortality, and overall star rating by hospital. Example: Northwestern Memorial — 5-star overall, top decile on mortality and safety, HCAHPS 87th percentile — benchmark for quality-driven referral network design. Source: CMS Care Compare synced data.

Use when researching a company federal revenue concentration, identifying government contract competitors, or assessing vendor dependency on federal business. Returns contract obligation data by vendor, agency, NAICS code, and fiscal year from USASpending. Example: Acme IT Services — $847M federal obligations FY2023, 67% from DoD, 3 agencies representing 89% of revenue — high concentration risk for supply chain or M&A due diligence. Source: USASpending.gov synced data.

Use when evaluating a bank for acquisition, partnership, correspondent banking, or competitive analysis in a local market. Returns FDIC-sourced assets, deposits, capital ratios, loan quality, and peer benchmark positioning. Example: Midwest Community Bank — $2.4B assets, CET1 12.3% (well above 6% minimum), NPL ratio 0.42% vs 0.71% peer median — strong capital position, favorable acquisition target profile. Source: FDIC BankFind synced call report data.

OSHA injury and illness rate benchmarks by company, industry, NAICS code, and state. Industry composite benchmarks available immediately with no sync required — establishment-specific data enabled when OSHA sync is connected. Covers injury rates, top-quartile performance, and EMR context for insurance, bonding, and public contract prequalification.

Use when assessing consumer finance risk, benchmarking complaint volume against peers, or conducting pre-acquisition due diligence on a financial institution. Returns CFPB complaint rollups by company and product — volume, issue themes, and response rate trends. Example: Regional Bank X — 847 CFPB complaints in 2023, 34% on mortgage servicing, complaint volume 2.3x peer median — elevated consumer protection risk signal. Source: CFPB Consumer Complaint Database synced data.

Use when assessing physician supply in a market, evaluating a healthcare network expansion, or benchmarking provider density for population health strategy. Returns NPI registry physician counts and market structure by specialty and state. Example: Illinois cardiology — 847 cardiologists, 2.3 per 10,000 population vs 2.7 national median — below-median supply signals referral network expansion opportunity. Source: CMS NPI Registry synced data.

Use when pulling public company financials for a comparable company analysis, M&A due diligence, or investor brief. Returns SEC EDGAR financial statement data — income statement, balance sheet, and key ratios from filed reports. Note: cache may reflect prior quarter — verify against latest SEC filing for time-sensitive analysis. Example: Salesforce FY2024 — $34.9B revenue, 29% operating margin on services, $4.1B operating cash flow — fundamental anchor for CRM sector comparable analysis. Source: SEC EDGAR synced filings.

Use when assessing physician payment transparency risk, evaluating manufacturer relationships, or preparing Sunshine Act compliance reporting. Returns CMS Open Payments aggregates by physician or manufacturer — payment amounts, types, and program year breakdown. Example: Dr. Smith — $847K general payments from 3 manufacturers in 2022, 67% from one device company in consulting fees — concentration above $100K triggers enhanced compliance review. Source: CMS Open Payments Sunshine Act database.

Use when assessing a company IP portfolio strength, tracking competitor patent activity, or preparing M&A patent due diligence. Returns USPTO filing rollups by assignee — patent counts, filing years, and CPC classification. Example: Qualcomm — 47,000+ active patents, 3,200 filed in 2023, concentrated in 5G and AI/ML — top 3 CPC codes represent 61% of portfolio — IP moat assessment critical for semiconductor M&A. Source: USPTO PatentsView synced data.

Use when assessing a technology vendor open-source presence, evaluating developer community strength, or researching a company GitHub footprint before a technical due diligence. Returns organization profile and top repository stats — stars, forks, contributors, and language breakdown. Example: HashiCorp GitHub — 18 public repos, Terraform at 38,000 stars, 147,000 forks, 2,800 contributors — strong community signal supporting enterprise adoption thesis. Source: GitHub public API.

Use when setting compensation ranges, evaluating a job offer, or preparing a comp committee presentation for any role. Returns p25, p50, p75 wage estimates with state and industry adjustments across 50+ role families. Example: Software engineer in Illinois — p25 $98K, median $127K, p75 $158K — organizations benchmarking above p75 retain 34% fewer departures in competitive talent markets. Source: BLS Occupational Employment Statistics, latest release.

Use when assessing SaaS company financial health, preparing investor reporting, or benchmarking KPIs before a fundraise or board presentation. Returns Rule of 40, burn multiple, CAC payback, NRR, gross margin, and ARR growth targets by ARR band. Example: $10-50M ARR benchmark — Rule of 40 median 28, NRR median 108%, CAC payback 18 months — companies below median Rule of 40 face 2-3x valuation compression in current market. Source: Stratalize SaaS benchmark tables.

Use when evaluating sales and marketing efficiency, setting CAC targets, or benchmarking GTM performance before a board review. Returns CAC payback ranges, LTV/CAC guardrails, and channel efficiency benchmarks by industry and GTM motion. Example: Mid-market SaaS with field sales — median CAC payback 22 months, LTV/CAC 3.8x — organizations above 30-month payback face capital efficiency pressure from investors. Source: Stratalize go-to-market composite.

Use when benchmarking working capital efficiency or preparing a CFO cash management brief. Working capital benchmarks — DSO, DPO, DIO, and cash conversion cycle (CCC) by industry and company size. Source: Hackett Group annual survey and BLS composite. CFO and treasury benchmark for lender covenant prep and cash flow optimization.

Use when valuing a business, setting hurdle rates, or benchmarking discount rates for M&A analysis or capital allocation. WACC benchmarks by sector and market cap tier from Damodaran annual dataset — used for DCF valuation, M&A pricing, board approval, and capital allocation. The most cited public finance benchmark. Updated January annually.

Use when building a public comps table, benchmarking a private company valuation, or preparing a fundraising benchmark. Public market valuation multiples — EV/EBITDA, EV/Revenue, P/E, and P/S by sector with p25/p50/p75 bands. Source: Damodaran January 2024 dataset. Used for board prep, M&A pricing, fundraising benchmarks, and DCF sanity checks. Free.

Use when valuing an acquisition target, benchmarking deal pricing, or preparing a fairness opinion. M&A transaction multiples — acquisition EV/EBITDA, EV/Revenue, and control premiums by industry and deal size. Source: Damodaran transaction dataset and public deal aggregates. Used by corp dev, PE deal teams, M&A advisors, and CFOs preparing fairness opinions.

Use when assessing a company debt capacity, benchmarking leverage against sector peers, or preparing a refinancing or credit rating discussion. Corporate leverage and debt benchmarks — Net Debt/EBITDA, interest coverage, and debt maturity profiles by credit rating tier and industry. Source: S&P Capital IQ public aggregates and Damodaran. Used by CFOs and treasurers for refinancing, covenant setting, and credit rating management.

Use when benchmarking audit costs, evaluating auditor proposals, or preparing an audit committee RFP. Audit fee benchmarks — total fees and fees as a percentage of revenue by company revenue band and auditor tier (Big 4 vs national vs regional). Source: Audit Analytics public aggregate data. Used by CFOs and audit committees in auditor RFPs and fee negotiations.

Use when benchmarking fund performance, setting LP return expectations, or evaluating a GP track record. Private equity and venture return benchmarks — IRR, TVPI, DPI by vintage year and strategy (buyout, growth equity, venture). Source: Cambridge Associates public benchmark summaries. Used by PE GPs, LPs, and fund CFOs for performance reporting and fundraising.

Venture capital round benchmarks — pre-money valuation, round size, dilution, and option pool standards by stage and sector. Source: Carta State of Private Markets quarterly. Used by founders, VC CFOs, and early-stage investors for round pricing and cap table modeling.

Bank regulatory capital and financial performance benchmarks — CET1, Tier 1 leverage, NIM, efficiency ratio, charge-off rates, and loan-to-deposit ratio by asset size tier. Source: FDIC call report public aggregates. For bank CFOs, risk officers, and bank analysts.

Insurance financial performance benchmarks — combined ratio, loss ratio, expense ratio, and reserve adequacy by line of business. Source: NAIC annual statistical report. For insurance CFOs, actuaries, and analysts reviewing underwriting performance.

Commercial real estate cap rate benchmarks by asset class, market tier, and geography. Source: CBRE and JLL quarterly cap rate surveys. Used by CRE acquisition teams, asset managers, and real estate CFOs for property pricing and portfolio valuation.

Commercial real estate debt benchmarks — DSCR minimums, LTV maximums, and spread ranges by property type and lender type (bank, agency, CMBS, life company). Source: MBA CREF databook and Trepp public data. For CRE CFOs and capital markets teams structuring financings.

Live mortgage rate benchmarks — 30Y and 15Y fixed from FRED weekly survey, ARM spreads, points and fees, DTI standards, and affordability index. For homebuyers, lenders, real estate agents, and housing analysts. Rates update weekly.

Residential real estate market benchmarks — home price indices, price-to-rent ratios, affordability, months of supply, and homeownership rate by market tier. Sources: FHFA HPI, FRED live data, Census. For residential investors, agents, developers, and housing analysts.

Live housing supply indicators — starts, permits, completions, and absorption by market tier from FRED and Census. Leading indicator for housing prices 6-12 months ahead. For developers, lenders, investors, and housing policy analysts.

Rental market benchmarks — asking rents by unit type, live vacancy rate from FRED, rent growth trends, and rent-to-income ratios by market tier. Sources: HUD Fair Market Rents, FRED live vacancy, ApartmentList public data. For landlords, multifamily investors, and property managers.

HUD Fair Market Rents by metro area and bedroom count. Used for affordable housing underwriting, Section 8 Housing Choice Voucher compliance, LIHTC income limit calculations, and housing authority budgeting. Source: HUD annual FMR dataset. Free.

Construction cost benchmarks — hard cost per SF by building type and region, soft cost ratios, contingency standards, and live material cost escalation signals. Sources: NAHB, Turner Building Cost Index, RSMeans composites. For developers, lenders, and project owners.

Development pro forma benchmarks — yield on cost, profit-on-cost, construction-to-perm spread, and return hurdles by product type. For developers underwriting new projects and lenders sizing construction loans. Sources: NAHB, ULI, industry composite.

REIT valuation and performance benchmarks — FFO multiples, AFFO multiples, dividend yields, NAV premium/discount, and total returns by property sector. Source: NAREIT public monthly data. For REIT analysts, portfolio managers, and IR teams. Free.

Property operating benchmarks — OpEx per SF, NOI margins, and occupancy rates by property type. Sources: BOMA Experience Exchange, IREM Income/Expense Analysis, NCREIF. For asset managers, property managers, and acquisition underwriters.

Property tax benchmarks — effective tax rates by state and property type, assessment ratios, and appeal success rates. Source: Lincoln Institute of Land Policy. For property owners, asset managers, and acquisition teams. Property tax is the largest controllable operating expense for most commercial properties.

NCREIF Property Index institutional return benchmarks — total returns, income returns, and appreciation by property type and region. The standard benchmark for institutional real estate portfolios. Source: NCREIF quarterly public data. For pension funds, endowments, and institutional asset managers.

CRE debt stress benchmarks — live delinquency rate from FRED, CMBS delinquency by property type, maturity wall exposure, and stressed cap rate scenarios. For lenders, special servicers, distressed investors, and regulators. Delinquency rate updates quarterly.

Credit union financial performance benchmarks — capital ratios, net interest margin, loan growth, and delinquency rates by asset size. Source: NCUA quarterly call report public data. For credit union CFOs preparing for NCUA exams and board reporting.

DeFi lending and stable yield benchmark from DeFiLlama Yields — top pools by APY with p25/p50/p75 APY bands, TVL, chain, and pool id. Optional protocol (project slug substring) and/or asset (symbol substring). With no filters, universe is stablecoin-marked pools (typical lending / money-market supply). Free public API, no key.

Live major currency pair benchmarks — USD/EUR, USD/JPY, USD/GBP, USD/CNY, USD/CAD, USD/MXN, DXY broad TWI, carry trade spread, and weekly/monthly/YTD rate change. Source: FRED. Updated daily. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Live investment grade and high yield credit spread benchmarks from FRED ICE BofA indices — OAS by rating tier, TED spread, 2s10s Treasury spread, and distress signal. Updates daily. For credit analysts and fixed income PMs. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Stablecoin lending yield benchmarks — USDC/USDT/DAI supply APY across Aave, Compound, Morpho, Spark by chain. p25/p50/p75 bands, TVL filter, and spread vs 3-month T-bill. Source: DeFiLlama + FRED. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields.

Live commodity price benchmarks — WTI crude, natural gas, gold, copper, wheat, soybeans. Weekly and monthly price changes, inflation pressure signal. Source: FRED. Updated daily. For traders and macro analysts. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Live US Treasury yield curve — 1M through 30Y yields with daily and weekly basis point changes, 2s10s and 2s30s spreads, inversion signal, SOFR, and curve shape classification. Source: FRED. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

DAO treasury benchmarks — top DAOs by treasury size, stablecoin percentage, runway, and governance token concentration. Median benchmarks: $550M treasury, 61% stablecoin, 48-month runway. Source: DeepDAO public data.

Real-world asset tokenization benchmarks — tokenized T-bill yields (Ondo, BlackRock BUIDL, Superstate, Franklin Templeton), RWA market TVL by category, YoY growth. $12.8B total RWA market. Source: DeFiLlama + public data.

Earnings quality and financial statement risk benchmarks — accruals ratio, cash conversion, and revenue recognition risk by sector. Source: SEC EDGAR aggregate + Sloan accruals model (academic standard). For CFOs, auditors, and analysts assessing financial reporting risk before M&A or investment.

Live gas price benchmarks for Ethereum, Base, and Solana. Returns Gwei, USD cost per transfer type, congestion category, and x402 agent economy context. Base vs ETH savings comparison. Source: public chain RPCs. Zero API key required. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Live TVL by blockchain — Ethereum, Base, Solana, Arbitrum, and 50+ chains from DeFiLlama. Rankings, 1D and 7D change, protocol counts, Ethereum dominance, and Base vs ETH TVL comparison for x402 agent context.

Live labor market benchmarks from FRED — unemployment, U-6 underemployment, JOLTS job openings, quit rate, labor participation, weekly claims, wage growth. Tight/balanced/loosening signal for macro agents and portfolio managers. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Live inflation benchmarks from FRED — CPI, core CPI, PCE, core PCE, 5Y and 10Y TIPS breakeven expectations, shelter and medical care components. Fed target gap, anchoring signal, and policy implication for macro agents. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Live consumer sentiment benchmarks from FRED — University of Michigan sentiment, Conference Board confidence, retail sales, PCE, personal saving rate. Strong/moderate/weak consumer signal for GDP and equity agents. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Global equity index benchmarks — S&P 500, Nasdaq, Russell 2000, Stoxx 600, DAX, FTSE 100, Nikkei 225, Hang Seng, Shanghai Composite, MSCI EM. YTD returns, P/E ratios, and risk-on/risk-off global signal. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

30-day rolling correlation matrix for BTC, ETH, and SOL — Pearson correlation pairs, beta to BTC, dominance context, and portfolio diversification signal. Source: DeFiLlama historical prices. For crypto portfolio agents. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Crypto options implied volatility benchmarks — BTC and ETH 7D/30D IV, put/call ratio, fear/greed signal, term structure shape, and VIX comparison. Source: Deribit public API + FRED. For options traders and volatility agents. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

ESG benchmarks by sector — carbon intensity Scope 1/2, net zero commitments, SBTi alignment, board independence, pay equity, and ESG composite scores. Sources: EPA GHGRP, MSCI ESG methodology. For sustainability agents and ESG analysts.

Climate financial risk benchmarks — physical risk (flood, hurricane, wildfire, heat), transition risk (carbon pricing scenarios, stranded assets), and lender implications. Source: FEMA NFIP, NGFS scenarios. For ESG and risk agents.

AML regulatory benchmarks — FinCEN SAR filing rates, OFAC SDN counts and recent additions, BSA enforcement fine history, travel rule thresholds, and compliance staffing benchmarks. For compliance agents and financial institution risk officers.

Use when assessing EU AI Act compliance readiness ahead of the August 2, 2026 enforcement deadline or preparing a board AI governance briefing. Returns a composite payload with framework, deadline, total_controls, controls[], hint, and query timestamp, optionally filtered by NIST function from compliance_controls reference data. Example: Filter by MAP to review mapped EU AI Act controls and implementation statuses in the returned controls array for governance planning. Source: EU AI Act mappings in compliance_controls reference data.

Use when assessing FCA model risk management compliance readiness or benchmarking an AI governance program against UK regulatory expectations. Returns coverage across 13 control objectives from FCA Policy Statement PS7/24. Example: PS7/24 requires documented model validation methodology, ongoing performance monitoring, and board-level model risk appetite statement — gaps in any of the three trigger supervisory concern. Source: FCA Policy Statement PS7/24.

Use when scheduling outdoor construction work, planning equipment deployment, or assessing weather risk for any US project site. Analyzes NOAA 7-day forecast data against construction delay thresholds — precipitation probability, wind speed above 25 mph, and freeze events below 32°F — returning a risk tier and specific high-risk days to avoid. Example: Chicago IL project site shows HIGH delay risk Thursday through Saturday — 70% precipitation probability, 2.3 inches rain forecast, 28°F overnight low Friday. Reschedule concrete pours and crane operations. Source: NOAA National Weather Service — official US government forecast.

Use when quantifying climate-related financial risk for insurance underwriting, real estate acquisition due diligence, ESG climate risk disclosures, or board-level climate briefings. Returns NOAA's official tally of billion-dollar weather disasters — hurricane, flooding, tornado, wildfire, winter storm — with event frequency, total economic losses, deaths, and trend direction. The same dataset cited by reinsurers, the Federal Reserve Financial Stability Report, and the SEC climate disclosure framework. Example: Texas 10-year history — 31 billion-dollar events, $174B total losses, frequency increasing — highest insured loss exposure of any US state. Source: NOAA NCEI Billion-Dollar Disasters.

Use when pricing physical climate risk for a location — real estate acquisition, commercial property underwriting, construction site selection, or climate-related financial disclosure. Returns a composite risk score across six perils (flood, hurricane, tornado, wildfire, extreme heat, freeze) using the same risk factors embedded in FEMA's National Risk Index. Example: Miami-Dade FL — EXTREME overall, top 2% hurricane exposure, Zone AE flood designation across 40% of commercial parcels, 94 days above 95°F annually — commercial property insurance costs 3.2x national median. Source: NOAA Climate Normals, FEMA National Risk Index, USGS Natural Hazards composite.

Use when establishing the macroeconomic cost of climate risk for board-level ESG reporting, reinsurance negotiations, infrastructure investment decisions, or climate-related financial risk disclosures under SEC or TCFD frameworks. Returns NOAA's official annual billion-dollar disaster economics — event count, total losses, deaths, and historical context showing 10-year trend acceleration. Example: 2023 — 28 events, $92.9B total losses, 12% above the 10-year average — the fifth consecutive year of above-average economic losses. Cited by the Federal Reserve, Treasury, and major reinsurers as the authoritative US climate loss series. Source: NOAA NCEI.

Use when assessing regulatory risk for a national bank or federal thrift before a merger, acquisition, partnership, correspondent banking relationship, or vendor engagement. Returns active and historical OCC enforcement actions — formal agreements, consent orders, cease-and-desist orders, and civil money penalties — the same records OCC examiners pull during supervisory reviews. Example: First National Bank of Springfield — formal agreement active since March 2022 requiring BSA/AML program overhaul, independent compliance consultant, and quarterly progress reports to OCC — agreement not yet terminated, elevates acquisition risk materially. Source: OCC Enforcement Actions — official supervisory records.

Use when evaluating a credit union for partnership, acquisition, membership, or competitive benchmarking in a local market. Returns NCUA call report financials — assets, deposits, loans, net worth ratio, delinquency rate, and ROA — with peer comparison signals. The same financial data NCUA examiners review during examination preparation. Well-capitalized threshold is 7% net worth ratio — institutions below this face mandatory corrective action. Example: ABC Federal Credit Union — $2.1B assets, 11.2% net worth ratio (59% above minimum), 0.38% delinquency vs 0.71% peer average — financially strong, low credit quality risk. Source: NCUA Call Report Data.

Use when assessing small business lending opportunity in a market, benchmarking a bank's SBA production against competitors, evaluating CRA lending performance by geography, or identifying industries with unmet capital needs. Returns SBA 7(a) and 504 loan approval data — counts, amounts, average sizes, top lenders, and industry concentration by state and NAICS sector. Example: Illinois manufacturing sector — 847 SBA loans approved in 2023, $425K average, top 3 lenders holding 31% market share — 69% of market accessible to community bank competition. Source: SBA Public Loan Disclosure Data.

Use when evaluating a bank's Community Reinvestment Act track record before a merger application, charter acquisition, branch expansion approval, or community lending partnership. CRA ratings — Outstanding, Satisfactory, Needs to Improve, Substantial Noncompliance — are a primary federal approval factor for bank mergers and acquisitions. A 'Needs to Improve' rating can delay or block merger approval by 12-24 months. Example: Heartland Community Bank — Outstanding CRA rating, 2023 FDIC exam, fourth consecutive Outstanding — maximum approval runway for pending acquisition of Gateway Savings Bank. Source: FFIEC CRA Ratings Database — the official federal record.

Use when screening a company, executive, vendor, or counterparty for federal litigation exposure before a contract award, acquisition, investment, board appointment, or enterprise partnership. Returns active and historical federal court dockets across all US district and appellate courts — case names, docket numbers, courts, filing dates, nature of suit, and active status. Example: Acme Corp — 4 active federal cases: patent infringement N.D. Cal. (filed 2023), FLSA collective action S.D.N.Y. with 847 plaintiffs (filed 2023), FTC antitrust investigation D.D.C. (filed 2024), securities class action S.D.N.Y. (filed 2024) — aggregate litigation liability exposure estimated above $200M. Source: CourtListener, 1M+ federal court documents.

Use when evaluating a pharmaceutical company, medical device manufacturer, or healthcare vendor for product safety risk, supply chain exposure, or regulatory compliance standing. Returns FDA recall classifications (Class I = risk of serious harm, Class II = moderate risk, Class III = unlikely to cause harm) with product descriptions and recall reasons. Class I recalls trigger mandatory FDA press releases and procurement review obligations. Example: MedSupply Corp — 2 Class I drug recalls in 36 months: contaminated IV solutions (2022) and mislabeled injectable (2023) — pattern of serious quality control failures requiring immediate vendor review. Source: OpenFDA Enforcement Reports.

Use when evaluating antitrust exposure, consumer protection liability, data privacy enforcement history, or deceptive practices risk for a company before an acquisition, strategic partnership, or enterprise vendor selection. FTC consent orders impose ongoing behavioral restrictions lasting 10-20 years and carry $50,000+ per day penalties for violations. Example: Tech Platform Corp — FTC consent order 2021, $150M civil penalty, 20-year restrictions on data monetization practices, biennial compliance reporting — restrictions survive acquisition and bind acquirer. Source: FTC Enforcement Cases and Proceedings.

Use when screening an employer, vendor, or acquisition target for wage and hour compliance risk before a contract award, supply chain partnership, PE acquisition, or HR due diligence review. Returns DOL Wage and Hour Division enforcement history — FLSA overtime violations, minimum wage violations, child labor violations — with back wages assessed and employees affected. Repeat violations are a strong predictor of class action exposure. Example: Logistics Co LLC — 3 WHD investigations 2019-2023, $1.2M back wages, 891 employees affected for FLSA overtime violations — classified repeat violator, 340% higher class action probability vs first-time violators. Source: DOL WHISARD Enforcement Database.

Use when building an AI governance compliance roadmap, advising on high-risk AI deployment obligations in Colorado, or briefing boards on upcoming US state AI regulatory requirements. Colorado SB 205 takes effect June 30, 2026 — the first comprehensive US state AI law. Returns developer and deployer obligations, high-risk AI system criteria, consumer rights, penalty structure ($20,000 per violation, AG enforcement), and comparison to EU AI Act. Example: AI-based loan underwriting system deployed in Colorado requires algorithmic impact assessment, plain-language consumer disclosure before first use, 3-year audit trail with AG access rights, and annual compliance certification — noncompliance triggers $20,000 per violation. Source: Colorado SB 205, enacted May 17, 2024.

Use when conducting an AI risk management gap assessment, building board-level AI governance documentation, preparing for a model risk examination, or aligning an AI program with federal regulatory expectations. NIST AI RMF 1.0 is the US federal standard for AI risk management — adopted by reference in the Executive Order on Safe AI and aligned with Federal Reserve SR 26-2, OCC model risk guidance, and FDIC requirements. Returns all four functions (GOVERN, MAP, MEASURE, MANAGE) with categories, subcategories, and implementation guidance. Example: GOVERN function requires board-level AI policy, documented accountability structures, and AI risk culture assessment — the first control examiners check in a model risk review. Source: NIST AI RMF 1.0.

Use when mapping AI regulatory compliance obligations across multiple states, advising on jurisdiction-specific AI deployment requirements, or briefing legal and compliance teams on the US state AI legislation landscape. As of May 2026, Colorado (June 30), Illinois, Texas, California, Virginia, and 9 additional states have enacted or advanced material AI legislation — creating a patchwork of obligations for multi-state AI deployments without a federal standard. Example: Financial institution deploying AI in 12 states faces 4 distinct compliance regimes with conflicting definitions of high-risk AI — multi-state compliance cost estimated $800K-$2M annually for mid-size institutions. Source: NCSL + Stratalize Regulatory Intelligence.

Use when preparing for a model risk management examination, building an SR 26-2 compliant model governance program, or assessing a financial institution's MRM framework against regulatory expectations. Returns Federal Reserve SR 26-2 and OCC requirements across development, independent validation, ongoing monitoring, and governance — with exam deficiency rates showing where institutions most commonly fail. For AI and ML models, SR 26-2 explicitly requires independent validation even for vendor-supplied models and black-box systems. Example: Documentation deficiencies are the most common exam finding at 67% of reviewed institutions — inadequate conceptual soundness documentation for credit scoring models triggers immediate MRA (Matter Requiring Attention). Source: Federal Reserve SR 26-2, OCC Bulletin 2026-13, FDIC FIL-15-2026.

Use when benchmarking workforce planning against sector labor market conditions, assessing industry growth trajectory for strategic planning, providing economic context for board reporting, or evaluating talent acquisition timing for a specific industry. Returns BLS payroll employment by major sector with month-over-month change, year-over-year change, and trend classification from the official establishment survey covering 650,000 US worksites — the same data the Federal Reserve uses to assess labor market conditions. Example: Healthcare sector — 8.41M employed, +47K MoM, +3.2% YoY, EXPANDING for 14 consecutive months — persistent hiring demand supports above-market compensation benchmarks. Source: Bureau of Labor Statistics Current Employment Statistics.

Use when analyzing inflation exposure by spending category, structuring or reviewing vendor contract escalation clauses, benchmarking healthcare or real estate cost inflation, or providing monetary policy context for a CFO or treasury brief. Medical care CPI and housing CPI consistently diverge from headline inflation — critical for healthcare budget planning and commercial lease negotiations. Example: Medical care CPI +3.8% YoY vs headline CPI +3.1% — healthcare costs inflating 23% faster than the general economy, directly driving hospital operating budget overruns in fixed-price service contracts. Source: Bureau of Labor Statistics CPI — the Federal Reserve's primary inflation benchmark.

Use when assessing country risk for international expansion, evaluating a foreign market for investment or partnership, benchmarking a country's economic trajectory for capital allocation decisions, or producing ESG country-level scoring. Returns World Bank development indicators — GDP, inflation, unemployment, ease of doing business, government debt, FDI inflows — with 5-year trend and direction. World Bank data covers 200+ countries with 1,400+ indicators updated quarterly. Example: Brazil — GDP growth 2.9% (2023), inflation declining from 9.3% to 4.6%, ease of doing business ranked 124th globally, net FDI inflows $65.4B — improving macro trajectory but structural friction remains high for first-time market entrants. Source: World Bank Open Data.

Use when benchmarking financial performance against industry-level tax return data, establishing valuation comparables for M&A, assessing typical effective tax rates by sector, or producing financial due diligence context from the most authoritative source of actual US business financial performance. Returns IRS SOI aggregate statistics from actual filed corporation income tax returns — gross receipts, net income margins, and effective tax rates by industry. Data reflects actual filed returns, not survey estimates. Example: Healthcare and Social Assistance — 284,000 returns, 8.3% net income margin, 19.1% effective tax rate, $4.2M average gross receipts per return — baseline for healthcare PE valuation and acquisition multiples analysis. Source: IRS Statistics of Income Division.