Sector valuation benchmarks
built from real market data

AI valuations are bifurcating. Infrastructure and model providers command premium multiples driven by compute moats and usage growth. Applied AI companies — across vertical SaaS, fintech, legal tech, and healthcare — are priced more selectively based on workflow depth, retention, and competitive defensibility.

This dataset covers 575 companies across HealthTech, Data Intelligence, Infrastructure, Marketing Tech, HR Tech, Fintech, Legal Tech, Search, and Computer Vision — combining public comps, private funding rounds, and M&A transactions to give founders and investors a structured benchmark across the full AI valuation spectrum.

EdTech valuations split sharply between enterprise-facing platforms and consumer learning products. Enterprise and workforce upskilling companies trade on ARR visibility and contract duration. Consumer platforms face steeper scrutiny on retention, engagement depth, and monetization sustainability.

This dataset covers 271+ companies across K-12, corporate training, higher education, certification platforms, and specialised learning technologies — drawing on public market comps, private funding benchmarks, and M&A transactions to provide a structured valuation reference across the full EdTech landscape.

PropTech valuations are closely tied to real estate cycle exposure. Transaction platforms carry more cyclical risk than operational software or data infrastructure businesses — and investors price that difference clearly. Recurring revenue structure and capital intensity are the two variables that most consistently separate premium from median multiples in this sector.

This dataset covers 216 companies across real estate transaction platforms, construction and development technology, investment platforms, and property data infrastructure — combining public comparables, private funding data, and M&A transactions to provide structured valuation context across the PropTech landscape.

Cybersecurity multiples are increasingly driven by platform positioning rather than point-solution performance. Companies building integrated security ecosystems around identity, endpoint, and cloud surface area consistently trade at higher multiples than specialists — even when the specialists show stronger near-term growth.

This dataset covers 250 companies across endpoint security, identity and access management, application security, OT/IoT protection, threat intelligence, data security, and governance and compliance — combining public market multiples, private funding benchmarks, and M&A comparables to support valuation analysis across the full cybersecurity stack.

Insurtech valuations hinge on one core question: how much regulated insurance risk does the company actually carry? Digital MGAs and embedded insurance infrastructure businesses are valued very differently from full-stack carriers. Distribution model, carrier dependency, and underwriting exposure are the variables that drive the widest multiple dispersion in this sector.

This dataset covers 110+ companies across digital carriers, embedded insurance infrastructure, underwriting automation, claims technology, reinsurance solutions, and analytics platforms — combining private and public market benchmarks alongside M&A activity to provide structured valuation context across modern insurance technology markets.

HR Tech multiples have compressed meaningfully since the 2021 peak, but the dispersion between categories remains significant. Core HRIS and payroll infrastructure companies trade at a premium to point solutions — driven by switching costs, data depth, and cross-sell potential. AI-native tools are being priced on adoption velocity rather than current revenue in many cases.

This dataset covers 100+ companies across recruiting technology, HRIS platforms, learning and development, workforce scheduling, employee engagement, payroll infrastructure, and HR analytics — drawing on private company comparables, public market multiples, and strategic acquisitions to benchmark valuation across the HR technology stack.

Fintech valuations are shaped by regulatory positioning, infrastructure depth, and take-rate defensibility. Payments infrastructure and embedded finance platforms command higher multiples than lending or consumer-facing applications — where credit risk, funding costs, and regulatory exposure all factor into investor pricing. The Q1 2026 dataset reflects a market that has broadly repriced quality over growth.

This dataset covers 416 companies across payments, lending, banking platforms, wealth technology, compliance infrastructure, and enterprise financial software — combining private funding data, public market multiples, and M&A transactions to provide a structured benchmark across the full fintech valuation spectrum.

Biotech valuations are stage-gated more explicitly than any other tech sector. Clinical milestones, regulatory pathway clarity, and IP depth drive more of the valuation outcome than revenue or growth metrics — particularly in early-stage companies where public market comps matter less than precedent transactions and pipeline risk assessments.

This dataset covers 200 companies across cell and gene therapy, diagnostics, synthetic biology, bioinformatics, biotech tools, and life sciences infrastructure — integrating public comparables, private funding benchmarks, and M&A transactions to support valuation analysis across the full biotech development spectrum.

API-first companies are valued on a different logic than traditional SaaS. Usage-based revenue models, developer ecosystem depth, and endpoint expansion potential matter more than seat counts. The best API businesses compound quietly — expansion revenue from existing customers often exceeds new logo growth, which creates a distinctive valuation dynamic that seat-based SaaS comps don't fully capture.

This dataset covers 286 companies across payments and banking APIs, identity and authentication, developer tooling, AI and ML interfaces, communications platforms, data enrichment, and vertical operational APIs — using EV-to-revenue and EV-to-funding benchmarks to provide consistent comparability across API infrastructure categories.

AdTech valuations are divided by position in the stack. Infrastructure players — DSPs, SSPs, measurement platforms — command more durable multiples than performance networks or creative tools, which are more exposed to ad spend cycles and platform dependency risk. First-party data access and identity resolution capabilities are increasingly factored into how acquirers price AdTech assets.

This dataset covers companies across demand- and supply-side platforms, retail media infrastructure, measurement and attribution, identity solutions, creative technology, and performance marketing ecosystems — combining public market benchmarks, private funding data, and M&A transactions to provide structured valuation insight across the advertising technology landscape.