AI for Pharma & Life Sciences: GxP Validated, Audit-Ready AI

From clinical evidence to HCP compliance, we build AI that meets pharma's regulatory requirements from day one.

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Trusted by Leaders in Regulated Industries

Bayer
Takeda
Adidas
Rockwell Automation
Burckhardt Compression
Tillotts Pharma

Challenges

01

GxP validation slows AI adoption

IQ/OQ/PQ, 21 CFR Part 11, full audit trails. Most AI vendors have never been through pharma validation. The gap between what they promise and what passes QA is enormous.

02

HCP engagement compliance is manual and slow

Every communication needs review. Teams spend more time on compliance than engagement. The review bottleneck limits how fast your field teams can operate.

03

Clinical evidence volumes overwhelm manual processes

Thousands of new publications monthly. Teams can't read everything but are responsible for knowing everything. Manual literature review doesn't scale.

04

Pharmacovigilance can't keep up

AE reports from trials, spontaneous reports, literature, social media growing exponentially. Signal detection at the speed and scale required is beyond manual capability.

Use Cases

Real-world applications

HCP Engagement Compliance

AI reviews all healthcare professional communications against FDA regulations and industry codes before distribution.

80% faster compliance review

Clinical Evidence Automation

Continuous literature monitoring and evidence synthesis across PubMed, Embase, and internal clinical data.

10x faster evidence review

Pharmacovigilance & Safety Signals

AI monitors adverse event reports across clinical trials, spontaneous reports, and real-world evidence.

60% faster signal detection

Regulatory Document Intelligence

Semantic search across FDA submissions, EMA guidelines, ICH standards, and internal regulatory archives.

Medical Information Management

AI-powered medical inquiry response grounded in approved product information and clinical data.

GxP Audit Preparation

Automated evidence collection and CAPA documentation for GxP audits with full traceability.

50% less audit prep time

Our Method

Production AI in 90 days

01

Assess

Weeks 1-2

Map workflows, data sources, and compliance requirements. Identify highest-impact use case.

02

Build

Weeks 3-8

Architecture, development, and integration with your systems. Security hardening from day one.

03

Pilot

Weeks 9-10

Deploy with pilot group. Measure against success metrics. Refine based on real usage.

04

Harden

Weeks 11-12

Production hardening, monitoring, documentation, and handoff with training and support.

Start with a $9,500 Assessment

Assessment fee credited toward implementation

Compliance & Security

GxP21 CFR Part 11EU MDRGDPRICH GuidelinesPharmacovigilance RegsEMA Standards

Technology Partners

Microsoft Solutions PartnerAzurePower PlatformSharePointOpenAI

FAQ

Frequently asked questions

How do you handle GxP validation for AI systems?

We follow full IQ/OQ/PQ validation protocols with complete documentation for every AI system. Our implementations are built with 21 CFR Part 11 compliance from the architecture level, including electronic signatures, audit trails, and role-based access controls.

Can the AI integrate with our existing pharma systems?

Yes. We integrate with Veeva Vault, IQVIA, Medidata, SAP for Life Sciences, and other pharma-specific platforms. The AI reads from your systems of record without modifying validated data.

How does the AI handle adverse event detection across data sources?

Our pharmacovigilance AI monitors clinical trial databases, spontaneous reporting systems, published literature, and real-world evidence simultaneously. It uses NLP to identify potential safety signals across structured and unstructured sources, then routes findings to safety teams for medical review.

Is the system compliant with both FDA and EMA requirements?

Yes. We build AI systems that meet both FDA and EMA regulatory requirements simultaneously, including 21 CFR Part 11, EU MDR, GDPR data residency, and ICH guidelines. Multi-region pharma companies can run a single compliant system.

What is the typical timeline for deploying pharma AI?

Pharma deployments typically follow a 90-120 day timeline due to validation requirements: 2-3 week assessment, 6-8 week build including IQ/OQ/PQ, 2-3 week pilot with clinical users, then production hardening with ongoing validation documentation.

Ready to ship AI that actually works?

Start with a 15-minute call. No pitch decks. We'll discuss your use case and whether our 90-day method is the right fit.

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