AI diligence infrastructure

Determine what’s real before capital is committed.

Kaptrix provides evidence-backed AI diligence using deterministic scoring, artifact-based analysis, and traceable reporting.

Built for

Institutional teams underwriting AI exposure.

  • Private equity

    Substance-focused diligence on AI-heavy platforms and add-ons.

  • Growth equity

    Technical qualification across an AI investment pipeline.

  • Corporate development

    Acquisition-grade evaluation of AI capabilities and exposure.

  • Technical diligence teams

    Structured evidence and risk artifacts for operator-led reviews.

Methodology

Built on a repeatable, evidence-anchored framework.

Kaptrix applies a deterministic, versioned framework for evaluating AI systems beyond demos and narratives. Every score is tied to specific artifacts. Every conclusion is traceable to source documents. Unsupported claims surface as explicit diligence gaps.

Confidence is a function of evidence coverage, not model certainty.

The framework was developed through repeated internal AI evaluation workflows prior to productization. Practitioner identities remain confidential during qualified engagements. A detailed methodology overview, scoring structure, and calibration approach are available for qualified review.

Methodology v1.0 — overview of scoring logic, calibration approach, trigger conditions, and audit structure. Available for qualified review.

Six weighted dimensions

  • 01Product Credibility
  • 02Tooling & Vendor Exposure
  • 03Data & Sensitivity Risk
  • 04Governance & Safety
  • 05Production Readiness
  • 06Open Validation

How Kaptrix works

Upload. Score. Trigger. Read.

  1. 01

    Upload

    Upload technical, commercial, governance, and operational artifacts.

  2. 02

    Score

    Evidence is mapped against six weighted diligence dimensions.

  3. 03

    Trigger

    Low-confidence areas, unsupported claims, and concentrated risks are surfaced for review.

  4. 04

    Read

    Generate institutional-grade reports, audit trails, and remediation plans.

Outputs

  • AI Diligence Report
  • Technical Risk Register
  • Confidence Audit Trail
  • 30/60/90 Action Plan

Scoring is deterministic and human-calibrated. Every conclusion maintains a traceable evidence lineage from source artifact to committee-ready output.

What you receive

Institutional-grade diligence artifacts.

  • 01

    Master AI Diligence Report

    Composite scoring across six dimensions with evidence-linked findings, red flags, and dimension-level conclusions.

    A single defensible record of what the evidence supports and what remains unproven.

  • 02

    Technical Risk Register

    Ranked technical, vendor, data, and governance risks with affected area, likelihood, and remediation.

    Quantifies post-close exposure before capital is committed.

  • 03

    Confidence Coverage Report

    Per-finding evidence coverage and confidence tier with the artifacts each conclusion is anchored to.

    Separates score from certainty so committee discussion targets real diligence gaps.

  • 04

    IC Memo

    One-page committee memo with composite score, conviction statement, top risks, and recommended next steps.

    Aligns the deal team and committee on the same evidence record.

  • 05

    100-Day Action Plan

    Prioritized 30/60/90-day remediation tied to specific risks and dimensions with owners and dependencies.

    Converts findings into the operating plan for the first hundred days post-close.

Before you write the memo.

Determine whether the AI system is real, governable, scalable, and commercially defensible before capital is committed.