AI that moves at biotech speed — from discovery to commercialization
Discovery and commercialization are gated by documents, data, and timelines — and you don't need a company-wide AI mandate to start moving. We build AI that compresses those cycles inside your validated, governed environment: matching patients to trials, accelerating regulatory work, and giving lean biotech and enterprise pharma teams alike a live view of portfolio risk and return. Start with one high-value workflow, prove it, then scale.
Why AI mattersin Life Sciences.
In life sciences, breakthroughs are gated by documents, data, and time. AI matters when it compresses those cycles without compromising scientific or regulatory rigor.
Our point of view is value first, measured in dollars and timelines. The teams that win with AI are the ones that can move — so we prove ROI in a single workflow, no company-wide mandate required, then scale. We amplify your scientists and reviewers rather than replace them, and build inside your validated, governed environment.
- 01Time is the costEvery month of delay is value lost.
- 02Documents gate everythingTrials and submissions drown in paperwork AI can read.
- 03Rigor can't slipSpeed only counts inside a validated process.
- 04Data is the assetDecades of research, finally searchable.
How we workin Life Sciences.
One method, tuned to your context: we design the whole system — people and AI — rank every move by ROI across four lenses, and build in iterative cycles that compound value.
Design the whole system
We map discovery-to-commercialization workflows end-to-end, designing where AI drafts and where qualified reviewers approve — with the change management to bring scientists and regulatory teams along.
Quantify the value
We score each opportunity across four lenses — timeline, cost, scientific and regulatory rigor, and risk — prioritizing the document- and data-heavy cycles where AI compresses months into weeks.
Tailor to your context
We build inside your validated, governed environment, integrating with your CTMS, regulatory, and data platforms rather than replacing them — with full traceability for audit and inspection.
Iterate and compound
We deploy a focused workflow, measure against your timelines and quality gates, and iterate each cycle — compounding speed without compromising rigor.
The AI opportunityin Life Sciences.
faster regulatory document prep
highest-value AI use cases mapped per function
target ROI within 90 days
Photo: Pexels
Purpose-built applicationsfor Life Sciences.
Intelligent Clinical Trial Matching
An AI agent scans patient records, trial eligibility criteria, and site capacity in real time — automatically surfacing the best candidates and reducing enrollment timelines by months.
CRFT builds the matching engine, integrations, and investigator portal.
Regulatory Submission Accelerator
Compress months of regulatory document preparation into weeks — AI drafts, cross-references, and validates submissions against FDA and EMA requirements automatically.
CRFT engineers the document intelligence pipeline from ingestion to submission-ready output.
R&D Portfolio Intelligence
A live dashboard tracks the ROI trajectory of every compound in your pipeline — flagging risk signals, budget overruns, and competitive shifts before quarterly reviews.
KNTRL provides real-time portfolio visibility and optimization signals.
AI Opportunity Mapping — Biotech & Pharma
A structured assessment finds the highest-value AI use cases for your team — whether you're a lean preclinical biotech or an enterprise pharma — each with projected returns, so you start with proof, not a company-wide program.
SPRK delivers the diagnostic and ROI-backed activation roadmap.
Sourcing Feels Faster. Is It Actually Working?
Your team says AI is helping. Sourcing feels faster. The analysts are more efficient. But when your LP asks what it's actually producing, you don't have a number you trust. That gap — between AI activity and AI value — is where most PE firms are stuck right now. Operational ROI is the first place to close it: not by chasing more AI activity, but by mapping the workflow, setting a real baseline, and proving that time saved actually became value created.
Pablo Cruz Pou · August 17, 2026 · 17 min read
The Accountability Gap: What Private Equity Gets Wrong About Measuring AI
A four-lens framework for capturing the full spectrum of AI value — and risk — across every dimension that matters to PE sponsors, operators, and boards.
Pablo Cruz Pou & Fritz Desir · May 30, 2026 · 17 min read
The Agentic Enterprise: A Field Report
What we learned putting AI agents into real operations — where they earned their keep, and where they quietly fell over.
Fritz Desir · May 28, 2026 · 3 min readLife Sciences,answered.
We design for your validated environment from day one — defining where AI drafts and where qualified reviewers approve, with full traceability for audit and inspection readiness.