Due Diligence Template: Evaluating AI Startups for Clinical Contracts

Hook: Why provider teams must tighten vendor checks after AI vendor volatility

Healthcare leaders juggling slow clinic access, fragmented records, and rising costs now face an added risk: AI vendor volatility. In 2025–2026 the market saw consolidation, debt restructurings, and surprise product sunsetting that left providers scrambling to preserve clinical workflows and patient data. If your organization is contracting with an AI startup for clinical use, a shallow evaluation can mean interrupted care, compliance gaps, and hidden costs. This guide gives a practical, proven due diligence template for evaluating AI startups before signing clinical contracts—plus a downloadable checklist covering financial health, compliance posture, model transparency, SLAs, and exit strategies.

The 2026 context: why due diligence matters now

Late 2025 and early 2026 accelerated two trends that change vendor risk profiles for providers:

• Market volatility and consolidation among AI vendors—some public and private firms restructured debt or pivoted product lines, increasing the probability of unexpected service changes.
• Stronger regulation and enforcement—global frameworks like the EU AI Act commenced enforcement, and U.S. regulators (FDA guidance on AI/ML-enabled SaMD, updated HIPAA enforcement priorities) increased documentation expectations for clinical AI products.

That combination means providers must treat AI vendor evaluation as both a standard procurement exercise and a clinical risk-control activity.

Inverted pyramid: what matters most

Most important: Can the vendor sustain operations, keep data secure, and be compelled to support clinical continuity if they fail? Then: Is the model clinically valid, auditable, and integrated with your workflows? Finally: Are contractual terms (SLAs, exit, IP) forcing vendor accountability?

Due diligence framework: 10 pillars for clinical contracts

Use these pillars as your evaluation checklist. For each, we include practical evidence to request, red flags, and scorecard guidance.

1. Financial health & viability

• Documents to request: latest audited financials (or reviewed financials), 12–24 month cash runway, cap table, major client references, recent fundraising or debt agreements.
• Metrics to evaluate: runway (months), monthly net burn, customer concentration (revenue from top 3 clients), recurring revenue % (ARR), margin trends.
• Red flags: runway <18 months without committed financing, >40% revenue from one customer, undisclosed debt covenants, frequent executive turnover.
• Practical step: require a covenant or escrow tied to operational continuity (see exit strategy section).

2. Compliance posture & certifications

• Documents to request: HIPAA BAA template, SOC 2 Type II report, ISO 27001 certificate, evidence of penetration testing and remediation, GDPR/Data Protection Impact Assessment (if EU data), FedRAMP status for federal integrations.
• 2026 update: regulators now expect documented model lifecycle governance and risk assessments (aligned with FDA/GMLP and EU AI Act obligations).
• Red flags: refusal to sign a BAA, no SOC 2 or equivalent evidence, one-off security reports with no remediation history.

3. Data governance & privacy

• Ask for: data flow diagrams, retention policies, de-identification approaches, third-party subprocessors list, and contractual subprocessor approvals.
• Must-have terms: clear data ownership clauses, portability commitments (standardized format), breach notification timelines (≤72 hours), and obligations for deletion on contract termination.
• Red flags: vague exportability or deletion terms, undisclosed subprocessors, or training pipelines that reuse patient data without consent.

4. Model transparency & clinical validation

• Request: validation study reports, performance metrics stratified by clinical subgroups, prospective trial or retrospective validation datasets, and access to model evaluation logs.
• Key metrics: sensitivity/specificity, AUROC, calibration plots, false positive/negative rates, and real-world performance drift monitoring.
• 2026 trend: expect requests for model cards, provenance metadata, and reproducible evaluation notebooks—providers must demand these for clinical audits.
• Red flags: refusal to share validation data or black-box claims without auditability, no post-deployment monitoring plan.

5. Software architecture & integration

• Ask for: API specifications, HL7/FHIR compatibility, authentication mechanisms (OIDC/SAML), message workflows, and a documented change management process.
• Integration tests to run: end-to-end clinical workflow simulation, latency under peak load, and error handling scenarios.
• Red flags: proprietary connectors only, no sandbox environment, or inability to support standard EHR integration methods.

6. SLAs, performance guarantees & monitoring

• Essential SLA items: uptime (99.9% baseline for clinical tools), incident response times (P1: 1 hour), mean time to recovery (MTTR), data loss guarantees, and financial credits for SLA breaches.
• Clinical performance SLAs: clauses tying model accuracy to minimum thresholds and remediation if drift exceeds pre-defined limits.
• Red flags: vague uptime guarantees, no financial recourse, or absent performance measurement definitions.

7. Security & penetration testing

• Ask for: results from the latest third-party penetration test, red team assessments, secure development lifecycle (SDL) policies, and encryption standards in transit and at rest.
• Required timeline: regular pentests (annual or after major releases) and proof of remediation for critical findings.
• Red flags: no independent tests, or a history of recurring critical vulnerabilities.

8. Personnel, governance & clinical oversight

• Request org charts, key personnel CVs (CTO, head of data science, compliance officer), clinical advisory board members, and evidence they perform regular model review.
• Red flags: lack of named clinical leads, heavy reliance on contractors for core functionalities, or frequent leadership churn.

9. Pricing, hidden costs & commercial terms

• Clarify: pricing model (per-user, per-encounter, subscription), variable costs during scale, change orders, and fees for integrations, customizations, or data exports.
• Red flags: opaque pricing for scale, high termination fees, or vendor lock-in via proprietary data formats.

10. Exit strategy & contingency planning

Non-negotiable: your contract must include concrete operational continuity clauses. After vendor failures and pivots in 2025–26, exit planning is now procurement-critical.

• Must-have contract clauses:
  • Data portability in standardized, machine-readable formats within X days of termination.
  • Code / IP escrow with an industry escrow provider triggered on insolvency or failure to meet SLAs.
  • Transition services agreement (TSA) for at least 90–180 days post-termination with defined support levels and costs.
  • Source access or documented rollback procedures for embedded clinical workflows.
• Practical steps: run a yearly mock vendor exit tabletop exercise with IT, clinical engineering, legal, and procurement to validate the plan.
• Red flags: vendor refusal to agree to escrow or TSA, or vague portability timelines.

Sample SLA language & scoring rubric

Below are concrete examples you can paste into procurement drafts and a simple scoring rubric to quantify vendor risk.

Example SLA clauses

• Uptime: Vendor guarantees 99.9% uptime measured monthly. Credits: 5% of monthly fee for each 0.1% below target beyond 99.6%.
• Clinical accuracy: Model maintains AUROC ≥ 0.85 and sensitivity ≥ X% on agreed validation dataset. If drift causes deterioration >5% over rolling 30 days, vendor must remediate within 30 days or suspend automated recommendations.
• Incident response: P1 incident response within 1 hour, mitigation plan within 24 hours, full root cause & remediation within 30 days.
• Data breach notification: Vendor notifies customer within 48 hours of discovery and provides remediation and patient notification support as required by law.

Simple scoring rubric (0–3 per pillar)

1. 0 = unacceptable/no evidence
2. 1 = partial evidence, requires mitigation
3. 2 = meets expectations with minor gaps
4. 3 = best practice / exceeds expectations

Score all 10 pillars (max 30). Thresholds: 24–30 = green, 16–23 = yellow with mandatory mitigations, <16 = red (do not proceed without corrective action).

Operational checklist (actionable next steps)

Use this short operating sequence when evaluating any AI startup for clinical contracts:

1. Initial screening: request the 10 core documents (financial summary, SOC2, BAA, model validation, API docs, pentest report, org chart, pricing, data flow diagram, 12-month runway).
2. Score using the rubric and identify top 3 risk mitigations per vendor.
3. Negotiate SLAs and exit clauses with procurement and legal. Insist on code/data escrow and TSA triggers tied to financial distress or prolonged SLA breaches.
4. Run integration pilot in a sandbox with real-world EHR traffic and a safety-first clinical rollback plan.
5. Require quarterly performance reporting and an annual tabletop exit simulation.

Case example: lessons from recent vendor volatility

The sudden restructuring and product shifts several vendors executed in 2025 showed that even firms with secure certifications can change risk profiles quickly.

When a midsize clinical AI vendor restructured in late 2025, several hospitals were unable to export annotated datasets because the contract lacked portability clauses and the vendor’s subprocessors were onshore-to-offshore transition. Those providers learned three lessons: require portability by design, validate subprocessors in advance, and escrow essential assets.

Downloadable due diligence checklist

Get a ready-to-use, printable checklist and contract clause bank to take to procurement and legal. The checklist mirrors the 10 pillars above and includes copyable SLA and exit clauses.

Download the Due Diligence Checklist (PDF) — or copy the checklist below into your RFP package.

Inline quick copy checklist

• Financial: audited/reviewed financials, runway ≥18 months, customer concentration <40%.
• Compliance: HIPAA BAA, SOC2 Type II, ISO 27001 where applicable, FedRAMP if federal.
• Data: clear ownership, portability, deletion, subprocessors listed.
• Model: validation studies, stratified metrics, model card & drift monitoring.
• Integration: FHIR/HL7 compatibility, test sandbox, documented APIs.
• SLA: uptime 99.9%, incident response P1 = 1 hour, accuracy guarantees & credits.
• Security: yearly pentest, remediation timeline, encryption standards.
• Governance: named clinical lead, advisory board, stable exec team.
• Pricing: transparent scale costs, no proprietary lock-in for exports.
• Exit: data portability & escrow, 90–180 day TSA, escrow provider named.

Final checklist: red flags that should stop a deal

• Runway <12 months with no committed financing.
• Refusal to sign a HIPAA BAA or provide SOC2 Type II report.
• Black-box claims with no auditability or refused access to validation data.
• No data portability or escrow agreement; excessive termination fees.
• Unremediated critical security findings or persistent leadership churn.

Actionable takeaways

• Make financial and exit clauses non-negotiable: escrow, TSA, and portability must be contractual deliverables.
• Demand model transparency and continuous monitoring: clinical AI is not a one-time validation event.
• Embed tabletop exit exercises into annual vendor management cycles—practice avoids care disruptions.
• Score vendors objectively with the 10-pillar rubric and tie procurement escalations to the score.

Where providers should focus investment in 2026

Prioritize tooling and processes that reduce vendor lock-in and increase oversight: automated export utilities, standardized FHIR-based connectors, a centralized vendor risk dashboard, and legal templates that include escrow specifics. These investments safeguard continuity even when vendors pivot or consolidate.

Closing: a clear next step

Due diligence for clinical AI vendors is no longer optional. With continued market volatility and tighter regulation in 2026, provider teams must be proactive and contractual about continuity, transparency, and safety. Start by downloading the checklist and running a cold-start score on any AI vendor you rely on—then require escrow and TSA clauses before pilot deployment.

Call to action: Download the printable Due Diligence Checklist (PDF) and get a complimentary 30-minute vendor risk triage call with our clinical procurement experts. Download checklist | Book the triage call.

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