Pharma & Regulatory Intelligence

Quality, with a
second brain.

AI-assisted regulatory intelligence designed to support expert quality judgment — not replace it. Built for inspection readiness, documentation intelligence, and high-stakes quality systems.

Field Note · Regulatory Intelligence in Practice

The FDA-483 observation arrived at 6 PM on a Friday. By Monday morning, the quality team had a fully structured, evidence-grounded response ready for expert review.

Regulatory compliance in pharmaceuticals isn't just about passing an audit. It's about building a quality system that holds up every day, for every batch, under any scrutiny. Praverse's pharma intelligence platform was designed around a single non-negotiable constraint: in a GMP environment, a wrong answer from an AI system is worse than no answer at all. Every observation is mapped to evidence. Every CAPA draft traces back to its source document. Every output is a starting point for qualified expert judgment — never a substitute for it. The system drafts. Your team decides. That hierarchy is not a policy layered on top of the architecture. It is the architecture.

How It Works

Five stages. Zero guesswork.

Every AI interaction in a regulated environment follows a structured, traceable pipeline — from document ingestion to expert-approved archive.

01Ingest

Documents, observations, and records enter the system with full provenance tracking.

02Analyze

AI identifies patterns, flags deviations, and maps observations to regulatory frameworks.

03Draft

Evidence-grounded draft responses, CAPA plans, or SOP content generated for expert review.

04Review

Qualified personnel review, edit, and approve every AI-generated output before use.

05Archive

Approved outputs are stored with a full audit trail — who asked, what was surfaced, what was decided.

Aligned with USFDA 21 CFR Part 211, ICH Q9, and ICH Q10 guidelines. All AI-generated outputs are drafts and require final review by qualified personnel.
FDA-483

FDA 483 Response Assist

Reduces drafting time for FDA observation responses — pattern intelligence across enforcement trends with evidence-grounded drafting support.

OOS/OOT

OOS/OOT Analysis Aid

Accelerates root cause analysis for out-of-specification and out-of-trend specification discrepancies with structured investigation support.

DI

DI Assessment Helpers

Flags potential anomalies in Data Integrity audits — AI-assisted review of records against ALCOA+ data-integrity principles.

SOP

SOP Automation

Generates and manages Standard Operating Procedures — search, gap detection, and inspection-readiness across your quality system.

CAPA

CAPA Reasoning

Structured root-cause support and corrective action drafting with evidence trails linking every suggestion to source documentation.

QRM

Quality Risk Management

Risk signal aggregation across deviations, OOS, OOT, complaints, and recalls — continuous readiness scoring so audits become routine.

RCA

Human Error Investigation

Investigation support that distinguishes systemic causes from individual ones — designed for fair, thorough RCA under regulatory scrutiny.

AUDIT

Inspection Readiness

Continuous readiness scoring and inspection-preparation support so your next audit is a routine event, not a crisis.

Every output is traceable, reviewable, and evidence-grounded. Praverse systems are designed for environments where a wrong answer has consequences — so humans always hold final judgment.
Why It Matters

Regulated industries need different AI.

Evidence-Based Review

Every AI suggestion links back to the source document, observation, or record it came from. No hallucinated compliance.

Audit Trails by Default

Who asked, what the system surfaced, what the expert decided — captured automatically for every interaction.

Expert Judgment First

The system drafts, analyzes, and flags. Your quality professionals decide. That hierarchy is built into the architecture.

Make your next inspection routine.

Talk to us about AI-assisted quality intelligence for your GMP environment.