Solutions · AI Partnership

AI that knows your science: and keeps it yours

We fine-tune foundation models on your proprietary data and deploy retrieval-augmented generation for pharma, life sciences and healthcare, grounded, cited, and built for regulated environments.

GxP · HIPAA · GDPR aware Fine-tuning + RAG Your IP stays yours FHIR · HL7 · CDISC ready

Meet Maya, your AI Assistant

Your data → your modelPrivate & grounded

Audit-logged retrievalYour IP stays yours

Why partner with us

Domain AI, done the regulated way

Built by a team that ships validated lab software for a living.

Domain-specific fine-tuning

LLMs adapted to pharma R&D, clinical workflows and regulatory content, accurate on your vocabulary.

RAG for regulated data

Retrieval pipelines with security, audit logging and citations, answers you can trace to the source.

Compliance by design

ISO 27001, HIPAA, FDA 21 CFR Part 11 and EU Annex 11 shaped into the pipeline, not bolted on.

Multimodal inputs

Structured lab data, documents, PDFs, DICOM and sensor streams, all usable for tuning or grounding.

Co-development programs

IP-retaining fine-tunes, joint pilots and validation studies, we build with you, not at you.

Interoperability first

FHIR, HL7, CDISC and LOINC standards baked into preprocessing and retrieval.

Choose the right tool

Fine-tuning or RAG? Flip to compare

The two main paths to domain AI, and when each one wins. We usually blend both.

Fine-tuningRAG

Best for FINE-TUNE

Teaching the model your vocabulary, style and specialized tasks.

Answering from living documents with citations and access control.

Data needed FINE-TUNE

Curated example pairs, hundreds to thousands.

Your existing SOPs, STPs, protocols and records, as they are.

Freshness FINE-TUNE

Frozen at training time; retrain to update.

Always current, answers follow the source documents.

Traceability FINE-TUNE

Knowledge is baked in; harder to attribute.

Every answer cites the exact passage it came from.

Time to value FINE-TUNE

Weeks, data prep and training runs.

Days, index, retrieve, evaluate.

Governance FINE-TUNE

Model versioning and eval sets per release.

Document-level permissions and audit-logged retrieval.

Where it lands

Use cases we build together

Proven starting points

Clinical literature summarization & insight extraction
Regulatory document Q&A. SOPs, STPs, dossiers
Pharmacovigilance case triage with retrieval grounding
R&D knowledge assistants (wet lab + in silico)
Medical device manuals & LIMS data made conversational
Med-info drafting with human approval flows

Models we tune

Open-source families. LLaMA, Mistral, Falcon, plus enterprise API models via adapters, with instruction tuning and task-specific heads.

LLaMAMistralFalconAPI adapters

The RAG stack

Vector databases, hybrid search, query rewriting and an evaluation harness, so quality is measured, not assumed.

PGVectorPineconeWeaviateHybrid search

Engagement models

Joint research, dedicated implementation projects, white-label builds for CROs and labs, or long-term strategic partnership.

Good questions

What partners ask us first

No. Your data and the resulting fine-tunes are yours, contractually and architecturally. We deploy in your environment or an isolated one, and nothing you share is used for anyone else.

Open-source families like LLaMA, Mistral and Falcon when you want full control, and enterprise API models via adapters when that fits better. The pilot phase includes an evaluation harness so the choice is made on measured quality, not fashion.

The same way we build our lab software: audit trails, access control, documented validation and human-in-the-loop approval where the risk requires it. Your QA/RA team is in the loop from the Validate stage onward.