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FDA 21 CFR Part 11 · GxP

AI safety + compliance for life sciences

The eval + guardrail + red-team + audit platform for AI touching regulated pharma workflows. Catch hallucinated dosages and off-label claims before they ship, keep trial data out of third-party LLMs, and hand your quality team a tamper-evident audit trail built for GxP-style review.

216
Scorers
77
LLM providers
324
Red-team plugins
2.57ms
Firewall p95
Pipette dispensing liquid into a laboratory microplate
Pharma & life sciencesFDA 21 CFR Part 11 · GxP

What ships today

Honest posture, not roadmap promises

Every checked item is in production today. In-progress items are flagged explicitly — no overclaiming, no vapor.

Tamper-evident audit log (integrity_hash + advisory-lock concurrency)
PII/PHI firewall with block mode across 18+ data types
Faithfulness + citation scorers for source-bound generation
BYOK provider keys via Vault — credentials never logged
Self-hosted deploy for validated environments
Per-tenant RBAC + evidence-bundle export for quality review
GxP validation-pack documentation (IQ/OQ templates)

Built for buyer reality

Pharma & life sciences AI use cases we ship for

Medical-information response drafting

AI drafts responses to healthcare-professional inquiries from the approved label and med-info library. A hallucinated dosage, contraindication, or off-label claim is a reportable event — every response must stay inside the approved source set.

EvalGuard features

  • Faithfulness scorer: every claim checked against the approved label + source library
  • Citation-format scorer rejects responses that cite outside the approved corpus
  • Output guardrail block mode: un-sourced dosage or efficacy claims never reach the requester
  • Tamper-evident audit log: every draft + reviewer decision preserved for inspection

Pharmacovigilance intake triage

AI screens inbound emails, call transcripts, and social mentions for potential adverse events. Missing a signal is a compliance failure; patient identifiers must be redacted before any third-party model sees the text.

EvalGuard features

  • PII firewall redacts patient name / DOB / contact details before the LLM call
  • Toxicity + safety scorers flag candidate adverse-event language for human triage
  • Answer-relevance scorer gates the triage summary against the source narrative
  • Gateway cost ledger attributes every intake scan to the PV cost center

Clinical-trial protocol Q&A for site staff

Site coordinators query an assistant grounded in the protocol + investigator brochure. Wrong visit windows or dosing schedules create protocol deviations — answers must be faithful, versioned, and auditable per site.

EvalGuard features

  • Hallucination scorer: answers checked against the current protocol version
  • Prompt-injection defense: 300+ attack plugins cover extraction attempts against trial data
  • Per-project BYOK isolation keeps each sponsor's trial corpus separate
  • Audit log records protocol version + answer per site for deviation review

Regulatory-submission drafting support

Writers use AI to summarize study data into submission modules. Numbers must match the source tables exactly, and the quality team needs evidence of every AI touch on the document trail.

EvalGuard features

  • Faithfulness scorer checks summary claims against the source tables
  • Multi-model routing with quality-cost strategy — accuracy threshold enforced per section
  • Evidence-bundle export: AI-assist trail packaged for quality + regulatory review
  • Per-tenant daily budget caps stop runaway drafting jobs before they burn spend

Wire it in 60 seconds

Wrap your OpenAI client. Get label-grounded guardrails.

Faithfulness thresholds + redaction rules + audit retention are configured once in the EvalGuard control plane. Your code only wraps the client.

typescript
import OpenAI from "openai";
import { wrapOpenAI, EvalGuardViolationError } from "@evalguard/openai";

const openai = wrapOpenAI(new OpenAI(), {
  apiKey: process.env.EVALGUARD_API_KEY!,
  projectId: "med-info-responses",
  metadata: { vertical: "pharma", gxp: true },
  blockOnViolation: true,                  // refuse un-sourced claims
  evalOnResponse: { failOnScore: 0.75 },   // label-faithfulness gate
  onViolation: (r) => notifyQuality(r.violations),
});

try {
  await openai.chat.completions.create({
    model: "gpt-4o",
    messages: [{ role: "user", content: medInfoPrompt }],
  });
} catch (err) {
  if (err instanceof EvalGuardViolationError) {
    // Block recorded in the tamper-evident audit trail. Replay via audit ID.
  }
}
Label corpus + faithfulness thresholds + retention live in the EvalGuard control plane — set once per project, no SDK calls needed.
Same integration for Anthropic, Gemini, and 91+ providers — swap wrapOpenAI for wrapAnthropic.

Ready to ship regulated-pharma AI you can defend?

Free trial includes the data firewall, faithfulness scorers, and the tamper-evident audit trail. Self-hosted deploy available for validated environments.

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