Proof criteria
Define what evidence must exist before and after AI touches a decision path.
Clear pass/fail for production readiness.
AI Readiness · Proof & Observability
Proof, testing, and observability for governed AI systems
Make AI behavior measurable, reviewable, and recordable before it runs in high-trust operations.
Overview
The problem
Teams deploy models without test plans, observability, or proof records — then cannot explain outcomes under review.
BBI approach
BBI applies evidence-first AI, Proof Ledger discipline, and human-in-the-loop gates to define what must be tested, logged, and observable.
Measurable outcome
A proof and testing framework tied to real workflows — not generic MLOps buzzwords.
Framework pillars
Testing strategy
Scenario tests for data drift, edge cases, and human override paths.
Reduced surprise in operations.
Observability design
Signals for decision quality, latency, failures, and review queue health.
Operators see system behavior in context.
Auditability
Record chains suitable for internal governance review — without overclaiming external certification.
Leaders can defend how AI is used.
How BBI works
AssessDecision & risk scope
DiagnoseProof gaps
PrioritizeTest & log plan
ImplementObservability hooks
VerifyRun proof tests
Record proofLedger & build records
Proof & outcomes
What gets measured
Test coverage, observability signals, review rates, and proof completeness.
Evidence produced
Test reports, Proof Ledger entries, and client-safe build records.
Decision improved
Production promotion, human-only mode, or rollback — based on evidence.
Before you book
Questions buyers ask first
What happens when I book a call?
You answer a short form about the workflow, your role, and your timeline. Based on fit, you are offered a discovery call or pointed to self-serve resources, right on the page.
What should I bring to the first conversation?
One workflow, decision, or exception that already costs time or carries risk, and the name of the person who owns it. A full AI strategy is not required.
What if AI does not belong in that workflow?
That is a finding, not a failure. The diagnostic ends in a written go / no-go that names what would have to change before the answer becomes yes.
How is pricing set?
Pricing depends on scope, evidence needs, workflow complexity, and review requirements. BBI does not quote implementation work before understanding the workflow and its risk boundary.
Start with one workflow
Bring one workflow. BBI will help you decide whether AI belongs there — with evidence, human review, and governed execution.