A governed evidence platform and the advisory practice that operates it — for AI and emerging methods used in scientific, clinical, and regulatory decisions.
For biopharma and TechBio, federal and NAM programs, and health systems.
Twenty minutes with practice leadership — one system, one decision, one evidence question. No demonstration until the decision is named.
Scientific AI can perform well on every benchmark and still lack the evidence that it is trustworthy for the specific decision being made.
A model described as 'human-relevant' or 'predictive' names an ambition, not a bounded decision. Without an explicit boundary, no study can confirm or refute it.
The cost · Vague intent leads to uninterpretable trial or assay outcomes.
Performance is routinely benchmarked against the legacy method the model was built to replace — simply because historical data sits there, regardless of whether it represents true clinical truth.
The cost · Flawed baselines distort genuine clinical and safety gains.
Results hinge on undocumented preprocessing, unversioned model checkpoints, or an isolated lab. External reviewers and partners cannot independently execute the work.
The cost · Failed audits and rejected regulatory submissions.
Validation is treated as a one-time static certificate. When patient populations drift or upstream foundational models update, nothing re-tests the initial claim.
The cost · Silent degradation in clinical utility and safety.
“Was the method inadequate — or was it never specified well enough to tell?” Ambiguity at the boundary is the expensive failure in life sciences.
One scoped engagement, applied to one consequential model, method, or decision — with defined outputs and a clear path to portfolio governance. Each stage earns the next.
20 minutes
Fixed scope
Annual
Standing
“Thought leadership earns the conversation. The conversation identifies the decision. The engagement is built around that decision.”
How an engagement worksEach link constrains the next. A break anywhere means the decision at the end is unsupported — however strong the model at the start.
In a clinical setting: a sepsis-risk model’s Context of Use names the wards and populations it may score. Governed use blocks it everywhere else. Outcome evidence asks whether clinicians changed their decisions — and whether patients did better.
Link 1 of 7 · Model
The computational method, biological algorithm, or multi-agent system under consideration.
Architecture, training lineage, weights, feature embeddings, and base assumptions of the computational or surrogate model.
Verified through: Lineage tracking, parameter provenance, and code reproducibility.
NIST AI RMF 1.0 (Map), ISO/IEC 42001
Most platforms start at governed use. Celbridge starts with Context of Use — and keeps revalidation running after go-live.
The Celbridge Trust Platform runs the evidence chain as living infrastructure — deployed in your VPC, enforced at runtime, recorded immutably.
Leadership sees the whole AI portfolio through evidence, not dashboards of vanity metrics.
Electronic records structured for 21 CFR Part 11 discipline and audit-readiness.
A cheaper or newer route must earn its traffic with empirical evidence.
Governance operated inside real health systems, federal translational programs, and enterprise AI platforms — not written about from the outside.
Engagement references are named under NDA; private reference conversations are available on request.
Meet the leadershipCo-Founder, President & CEO
Leads Celbridge's role as an NIH Complement-ARIE performer; ran enterprise AI governance across a 180-tool health-system portfolio; published the non-compensatory evidence framework the Trust Platform operationalizes.
Co-Founder & Head of Product
15+ years shipping enterprise AI and SaaS platforms from concept to scale; leads the Celbridge Trust Platform.
Co-Founder & Head of Engineering
Engineering executive in AI-driven software and cloud delivery; leads private/VPC implementation and enterprise integration.
One system, one Context of Use, one evidence chain, one value baseline. A scoping conversation identifies the decision worth assessing — before you commit to broader infrastructure.
Not ready for a call? Read what eight weeks of this work looks like