GxP SOP AI Assistant
For Pharma Manufacturing
GxP-validated AI assistant that answers operator and QA questions from SOPs, batch records and product-quality reviews - with 21 CFR Part 11 audit trails and full validation documentation.
Quick Answer
NeoBram builds GxP-validated SOP and batch-record AI assistants for pharma manufacturing - answering operator, QA and production questions from SOPs, MBRs, BMRs and PQRs with full 21 CFR Part 11 audit trails, GAMP 5 validation, and integration with Werum PAS-X, Siemens Opcenter, LIMS and QMS.
Why This Matters
SOPs Are The Backbone. And Nobody Reads Them.
A typical pharma site has 2,000-10,000 controlled SOPs, work instructions, MBRs and policies. Operators and QA staff routinely re-train, re-read, and re-search for the same answer - or skip the step because finding it is too slow.
A GxP-validated AI assistant gives instant cited answers from the controlled document set, in the operator's language, with every interaction logged for audit. Deviations, batch-record questions and CAPA research that took 30-60 minutes complete in seconds.
We deploy with full GAMP 5 / CSV validation - URS, functional spec, IQ/OQ/PQ, change-control plan, 21 CFR Part 11 audit trails, on-premise or validated private cloud. The assistant is positioned as a decision-support tool with citations, not as a controlling system.
Our Tech Stack
Production-Grade Tools We Deploy
Foundation models
Validated RAG stack
GxP validation
Source systems
Architecture Deep-Dive
How We Build It
Cited SOP & MBR Q&A
Operators, QA and supervisors get instant answers from the controlled document set - every response cites the exact SOP, section and revision. Stale or obsolete documents are filtered out.
- Citations to SOP number, section and approved revision
- Always-current approved revisions only
- Refusal to answer when context is insufficient
- Multilingual - operators ask in their language
Deviation, CAPA & PQR research
QA and production investigators query the full history of deviations, CAPAs, change controls and PQRs to find precedent, root cause patterns and effective corrective actions.
- Search across TrackWise / Veeva QMS deviations
- Pattern detection across similar past events
- Effective-CAPA recommendation from precedent
- Annual PQR data assembly and summarisation
21 CFR Part 11 audit trail
Every question, retrieved source, generated answer and operator action is logged immutably with user, timestamp, model version and dataset hash - audit-ready for FDA, EMA, MHRA, CDSCO.
- Immutable, append-only audit trail
- Cryptographic linkage of model + dataset + answer
- Periodic audit-trail review reports
- Inspector-ready export of all interactions
Multilingual operator interface
Operators across global sites use the assistant in their native language while source SOPs remain in English (or local approved language). Translation is shown with source alongside.
- 30+ languages including Hindi, Mandarin, Spanish, Japanese
- Source-language answer always available beside translation
- Voice input via on-prem Whisper
- Tablet, HMI and desktop access
Data Security, Governance & Safety
Enterprise AI demands enterprise-grade security. Every solution we deploy follows strict data sovereignty, safety, and compliance standards.
Data Sovereignty
- Your data stays in your infrastructure - always
- Deploy on your cloud (AWS, Azure, GCP) or on-premise
- No data leaves your environment
- Full compliance with regional data residency requirements
Model Safety & Guardrails
- NVIDIA NeMo Guardrails for content safety
- PII detection and redaction with Presidio
- Prompt injection defense and input sanitization
- Hallucination detection and factual grounding
Access Control & Audit
- Role-based access control for all AI systems
- Immutable audit logs for every interaction
- SOC 2 Type II, ISO 27001 compliance frameworks
- GDPR, HIPAA, and industry-specific regulations
Responsible AI
- Bias testing with Fairlearn and AI Fairness 360
- Model explainability via SHAP and LIME
- Transparency reports for stakeholders
- Continuous fairness monitoring in production
FAQ
Frequently Asked Questions
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