Who We Serve
DeepCrispr is not a generic LLM evaluation tool. It is the credibility assessment infrastructure that biotech, pharma, and clinical AI teams need to meet the FDA's 2025 computational model requirements.
Biotech & Pharma Sponsors
IND / NDA / 510(k) Submissions
You deploy AI models in clinical development (drug-drug interaction checkers, dosing algorithms, imaging classifiers) but lack the credibility evidence the FDA now demands under the 2025 framework.
What DeepCrispr Delivers
- Automated VVUQ scoring across Verification, Validation, and Uncertainty Quantification
- Credibility Assessment Reports generated from real adversarial test results
- Model Analysis Plan (MAP) artifacts ready for regulatory submission
- Paper-cited evidence chains for every scored failure mode
CROs & Regulatory Consultancies
Credibility Assessment Services
Your clients ask you to validate their AI/ML models for regulatory submissions, but current tools only measure accuracy on static benchmarks — they don't test real-world failure modes like hallucination, sycophancy, or tool bypass.
What DeepCrispr Delivers
- White-label credibility infrastructure: run DeepCrispr's test battery against client models
- 9 adversarial scenarios (T06-T14) covering DDI hallucination, billing upcoding, CRISPR fabrication
- DeepEval integration: hallucination and tool-correctness scores powered by open-source LLM-as-judge
- Export-ready regulatory artifacts: scored verdicts, context contradiction chains, ASME V&V 40 mapping
Clinical AI / MLOps Teams
Model Monitoring & Governance
You build and deploy clinical decision support tools. Post-market, the FDA expects continuous monitoring — but your MLOps pipeline has no automated credibility checks.
What DeepCrispr Delivers
- Continuous scoring endpoints: /score/hallucination, /score/tool-correctness, /score/abstention
- In-memory caching + 30s timeout protection for production workloads
- Graceful fallback: DeepEval LLM-as-judge when available, rule-based scoring always works
- Health endpoint + artifact inventory for model registry integration
Regulatory Affairs & QA
FDA Compliance Evidence
The CORE-MD score, the AIM-NASH precedent, and the FDA's 7-step framework all require documented credibility evidence — but your teams produce it manually in spreadsheets and Word docs.
What DeepCrispr Delivers
- Steps 4-7 of the FDA credibility framework automated with scored evidence
- VCAS, VPES, MPES scoring aligned with CORE-MD consortium recommendations
- Adversarial test artifacts with full provenance (prompt → response → verdict → paper citation)
- Context of Use (COU) builder for risk-proportionate assessment scoping
Ready to Build Your Credibility Evidence?
Stop generating AI outputs without proof. Build the credibility assessment infrastructure the FDA demands.