Evidence assurance for AI-assisted and consequential workflows
I help teams make one important workflow inspectable, reconstructable, and defensible. That holds whether the scrutiny is regulatory, operational, commercial, or technical. Start with a free diagnostic and a fixed-scope design sprint when formal work is justified.
Explicit scope, approved sources, human control, versions, failure states, and limitations.
Illustrative assessment
Buyer-readiness review for a synthetic regulated-technology vendor
Useful wherever an output must be reconstructed or defended, including outside life sciences
Primary offer
A CAD 8,000 fixed-scope design phase for one named workflow: versioned evidence map, gap and failure-mode register, recommended controls and review gates, prioritized hardening plan, and at most one non-production proof of concept. Production implementation and validation stay outside the fee.
Common entry point
Start with a short written description of one workflow. Plain language is enough; leave confidential data out. That written request is the intake. When a live walkthrough helps, we book about 45 minutes and trace one representative output only far enough to decide whether the paid design sprint is justified.
Free written outcome is always short: proceed, not a fit, or insufficient access. No free evidence map, gap register, control design, remediation plan, or workshop deliverable, for written notes or live calls.
After the design sprint
These are not equal peer products on the homepage. They appear after the flagship problem is clear, or when the diagnostic routes there.
A separately scoped design-and-implementation pilot for one bounded workflow. Use it when build is justified after the design sprint, or when the path is already clear enough to pilot. Pricing confirmed after diagnostic.
Implementation pathBuyer-readiness claims audits and decision-focused research sprints when the problem is claim support or a consequential research question rather than one workflow’s evidence chain.
View secondary offersIllustrative assessment
Buyer-readiness review for a synthetic regulated-technology vendor
A shared evidence grammar
Reviews are designed to serve both the person using the result and the reviewer who needs to inspect how it was produced.
Independent perspective
Public LinkedIn recommendation from peer collaboration, with relationship context. Not a client engagement.
During our technical deep-dive into backend systems, his critique of data governance, log-guarding protocols, and system auditability was incredibly sharp and practical.
Tool-supported, human-reviewed
CAL helps structure claim-level review, retain evidence and reviewer records, and test the consistency of automated judgments. A completed run is not automatically a valid run, and candidate evidence is not automatically support.
It does not certify a product, create regulatory approval, replace human judgment, or turn retrieval coverage into ground truth. Run validity, calibration, human review, and limitations remain explicit.
Start with one workflow and a short non-confidential description. That is enough to decide whether a free diagnostic and the design sprint are the right next steps.