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Faro’s $37.3M Series B: Agentic AI for Clinical Development
Faro AI raised $37.3M Series B co-led by Merck Global Health Innovation Fund and S32, with General Catalyst returning. Platform used by 6 of the world’s 10 largest pharma companies. Structured clinical-intent data — not chat-on-PDFs.
Faro AI closed a $37.3 million Series B on August 26, 2026, co-led by Merck Global Health Innovation Fund and S32. General Catalyst returned with Northpond, Polaris, PTX, and Zetta; Ankona joined. S32 now has a directory profile: S32; Merck GHI does not have a VCT fund page.
Unexpected truth: the company says it already sits inside six of the ten largest pharma companies — then raises a mid-size Series B to turn protocol-centric structure into agentic workflows, not another drafting demo.
This page is for healthtech scouts and founders selling into regulated development orgs. Last verified August 31, 2026. Primary: Faro’s own Series B letter.
Five-minute decision
| If you need… | Verdict |
|---|---|
| What happened | Funded. $37.3M Series B. Merck GHI + S32 co-lead. No valuation. |
| What Faro is | Structured clinical-development data model + agent layer starting at the protocol. |
| Whether it is shipping | Yes — 6/10 largest pharma (company). |
| Whether to diligence | Yes, if clinical-dev AI must survive regulated multi-system workflows. |
Investigate further when: your buyer already drafts protocols in siloed tools and feels the downstream breakage.
Wait or pass when: you need ARR, retention, or a disclosed mark.
What happened
| Field | Detail |
|---|---|
| Company | Faro AI (ex-Faro Health; San Diego) |
| Round | $37.3M Series B · Aug 26, 2026 |
| Co-leads | Merck Global Health Innovation Fund, S32 |
| Returning | General Catalyst, Northpond, Polaris, PTX, Zetta |
| New | Ankona Capital |
| Traction claim | 6 of top 10 global pharma (company) |
Who uses it — and why this syndicate
Users: large-pharma clinical development teams spanning study design, protocol authoring, study build, execution, data flows, and review. Faro’s letter: customers want agents that understand why an endpoint was chosen and what that implies for schedules, data collection, downstream systems, and regulatory constraints — not a paragraph rewriter.
Why Merck GHI + S32 + GC fit:
- Merck GHI is strategic capital with pharma-native diligence; Mike Morgan’s quote frames agentic AI as quality + time, not novelty.
- S32 co-leading signals multi-stage healthcare infrastructure appetite.
- General Catalyst already underwrote the earlier Faro Health thesis; returning is portfolio continuity as the brand shifts Health → AI.
Likely reason Faro raises from them: enterprise pharma sales cycles need patient capital and a strategic that understands ICH/regulated process risk — not a consumer-AI growth fund.
Why now
Biopharma is moving from AI-as-isolated-task to AI-across-workflows. Faro spent years on proprietary clinical development data models so agents can reason over intent, with documents as outputs rather than the system of record. Series B funds expanding agent capabilities on that substrate.
What is not proven
- No valuation, ARR, NRR, or named logos beyond the 6/10 claim.
- “Largest pharma” definition not footnoted.
- Agentic workflow depth vs protocol-authoring assistance is company-described, not independently audited.
Competitive map
| Category | Examples | Faro contrast |
|---|---|---|
| Protocol drafting AI | Document copilots | Faro claims structured intent across the continuum |
| eClinical / EDC suites | Incumbent trial software | Faro positions as AI layer, not full replacement |
| Health data infra (Metriport et al.) | Interop / records | Different job: development program design vs care delivery data |
Implication
The open question is whether Faro becomes the system of intent for clinical development or stays a high-end protocol tool with agent wrappers. Diligence the 6/10 claim with reference calls before treating Series B as category victory.
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Editorial note: AI tools assisted with research, structure, or drafting. Venture Capital Tracker retains human editorial responsibility for factual accuracy, relevance, and source quality before publication.
