Full Chain · Joint diagnostic by Kombocode and Behavieural

Half an answer isn’t an answer.

When an AI assisted decision gets questioned, say a denied claim, a declined application or a disputed authorization, the question that actually gets asked is never just “was the model right.” It's “can you show me exactly what happened, and can you show me the person's role in it held up.” Most organizations can answer half of that. Almost none can produce both halves as one coherent, defensible record.

Schedule a Briefing Also on Behavieural: the Full Chain page ↗

01Full Chain

How It Works

01

trace Runs First

Kombocode reconstructs the system side of the decision: model version, policy rule applied, override, audit log, appeals replay, and maps exactly where that chain holds and where it breaks.

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02

BOLD Runs Second

Using trace's findings as its evidentiary base, Behavieural reconstructs the human side: what the reviewer actually saw, what they did with it, and whether that was reasonable given the information available at the time.

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03

One Joint Report

Both findings roll into a single record, built for the audience that will actually read it: compliance, legal, or a board.

02Full Chain

What Each Side Answers

trace

trace answers one question: what did the AI system do, and what did the reviewer actually see at the time? It works the technical side of the decision, producing a traceability map and a set of failure pattern findings that show where the system’s record holds together and where it doesn’t.

BOLD

BOLD answers a different question: was the reviewer’s reliance on what trace surfaced actually reasonable? It works the behavioral side, producing a Verdict: Sound, Fragile, or Breakdown, along with a targeted recommendation, built on the technically verified record trace hands it rather than a self reported account of what the reviewer saw.

Together, the two cover the full decision: what the system can prove, and whether the person acted reasonably given what the system actually showed them.

The whole decision in one record.

Full Chain shows whether both sides of an AI assisted decision held up: trace reconstructs what the system did and what the reviewer actually saw, BOLD evaluates whether the reviewer's call was reasonable.

03Full Chain

Who It’s For

A Decision is Already Under Scrutiny

An internal review, a member complaint, a regulatory inquiry, or early signs of an appeal.

You're in a State with Human Review Requirements

Including Colorado's SB 26-189, effective January 2027, where showing that a person signed off isn't enough on its own.

A Single Sided Audit Didn't Close the Loop

You've already run a technical audit or a behavioral audit in isolation and found it didn't fully close out the review.

You Need to Answer Someone Outside Your Org

A regulator, auditor, or appellant's counsel needs a record, not a reconstruction assembled after the fact.

04Full Chain

How It's Scoped

Priced as a complete engagement, reflecting the combined, cross referenced record rather than two separate reports. trace runs first; BOLD follows once the traceability map is in hand, typically the same week. Both products remain independently available, but organizations facing scrutiny on a specific decision get the strongest, fastest answer from the two run together.

05Full Chain

Who We Are

Elena Rodin

Founder & Principal Engineer, Kombocode

Elena is Founder and Principal Engineer of Kombocode, a US engineering consultancy that designs and stabilizes AI systems in regulated environments, where every decision has to survive an audit, a regulator, or a courtroom. Kombocode's deepest work is with healthcare payers and care management companies, in prior authorization, utilization management, claims, and risk adjustment, and its practice now extends to legal tech and financial services, including taking AI products from pilot through audit to production. Elena sets the architecture and leads a team of engineers who build under her direction. Before Kombocode she spent over 20 years as an enterprise architect and engineer at companies including Boeing, AstraZeneca, Bank of America, McKesson Health Solutions, and AmeriHealth Administrators.

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Eugene Chan, PhD

Founder & Principal Strategist, Behavieural

Eugene is the Founder and Principal Strategist of Behavieural, a consultancy that uses behavioral science to solve organizations' hardest trust problems: AI adoption, customer loyalty, brand and reputation. He is Full Professor and Van Norman Chair of Business at Tyndale University, and has previously taught at Toronto Metropolitan University as well as in Australia and the United States. His PhD is from the Rotman School of Management, and he is the author of Managing Brand Crises: A Guide for Navigating the Storm.

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— Contact

Start with trace.

Thirty minutes on the phone. We look at what your system records today and whether a decision could be reconstructed tomorrow.

Book a 30-min technical call

Or directly

Elena.Rodin@Kombocode.ai