It's rarely the model
of life-sciences leaders have scaled AI. Pilots stall at validation, governance, and sign-off — not at the model itself.
Vendor claims about validation, accuracy, and compliance are difficult to independently verify without a technical and clinical evaluator on your side of the table.
FDA, EMA, and ICH guidance on AI is converging fast but remains partly draft — requiring judgment, not just a checklist, to apply correctly today.
Where AI actually creates value in your program
Not every workflow deserves an AI pilot. We help you prioritize the use cases where AI genuinely accelerates — protocol authoring, data cleaning, document generation, biostatistics — and make the build-versus-buy and operating-model decisions that follow.
- ► Use-case prioritization against real operational cost and risk
- ► Build vs. buy vs. partner, decided case by case
- ► The operating model and team structure to run it
"AI drafts. Experts decide. The record proves it."
The principle behind every AI decision we help you make.
A six-step method, not a gut check
Requirements & context of use
Market scan
Scorecard & due diligence
Governed proof of concept
Contract & validation terms
Ongoing oversight
Risk-tiered, mapped to the standards that matter
Every AI use case gets classified into a risk tier — and every tier maps to the specific frameworks a regulator or auditor will actually ask about.
Lower risk
Site feasibility, enrollment forecasting — efficiency tools with no direct GxP output.
Moderate risk
Data cleaning, document drafting — informs GxP records but a human reviews before anything is finalized.
Highest risk
Safety-signal adjudication, benefit-risk decisions — the architectural invariant applies: no AI output becomes a record of decision unsigned.
Mapped against FDA's AI credibility framework, the FDA–EMA AI principles, ICH E6(R3), 21 CFR Part 11, the EU AI Act, ISO/IEC 42001, and the NIST AI Risk Management Framework — so the tier you land in tells you exactly which standard applies.
Grade your AI governance in 2 minutes.
Ten questions across five domains — risk classification, vendor validation, human sign-off, audit trail, and ownership — with an instant graded result and your two biggest exposures named.
Evidence a QA team can actually approve
Every AI use case we govern gets an evidence package built for the person who has to sign off on it — your QA lead, an auditor, or a buyer's diligence team. Model and version used, inputs and outputs, the reviewing expert's identity and credentials, the criteria applied, and the final signed disposition — assembled as the work happens, not reconstructed under deadline.
Decisions made at IND, not retrofitted later
EDC, RTSM, eCOA, CTMS, and safety database integration — architected by the team that built the industry's first unified eClinical platform. Real-time-readiness decisions belong at IND, when the data architecture is still cheap to change, not after protocol lock.
Who leads
Elias Tharakan
Chief Executive & Technology Officer
Architect of the industry's first unified eClinical SaaS platform, powering 1,000+ clinical trials. Twenty years building compliant AI and data-integrity frameworks inside FDA-regulated environments — supported by specialists from our expert network for domain-specific evaluations.
We evaluate vendors against criteria set independently of any commercial relationship, and disclose relevant partnerships to the parties who need to know — see how we handle it on Technology & AI Vendors.
Educate · Evaluate · Execute
AI governance fundamentals briefing
Where the FDA, EMA, and EU AI Act guidance actually lands today — for your board and technology leadership.
AI readiness & governance audit
A bounded assessment of your AI exposure and governance maturity — or an eClinical fit-gap analysis for your current stack.
Framework build-out & fractional CTO
Governance framework build-out, a validation dossier for a specific use case, or ongoing fractional CTO leadership.
Book an AI governance evaluation.
Bring us the vendor decision, the stalled pilot, or the governance gap you need to close.