AI-Assisted Architecture Governance
Moving ARB and technology review from manual gatekeeping to traceable decision intelligence.
Advisory and proof-of-value work on intelligent intake, review routing, decision memory, and human-in-the-loop governance — for teams scaling architecture review beyond what manual process can carry.
Engagement model
Advisory (day-rate) or fixed-scope PoV
Availability
Remote, CET overlap · 1–2 days/week to start
Currently
Building ARB Copilot; selective advisory alongside it
Focus
Where this is useful
- ARB / technology review modernizationIntake, qualification, routing, exception handling, ADR and evidence trails.
- LeanIX / CMDB decision layersTurning the inventory into a decision foundation, not just a system of record.
- Decision traceabilityCapturing why a call was made, what was accepted, and where overrides occurred.
- Cloud, data & security governanceAligning review across integrations, data sensitivity, AI usage, and regulatory scope.
Thesis
EA 2.0, briefly
"The inventory gives you structure. It doesn't give you the decision layer on top."
"Augmentation over automation — the system handles triage and evidence; the architect makes the call."
"Every override is a signal, not a loss — that's how implicit judgment becomes traceable."
ARB Copilot — Proof of Value
2–4 WEEKS · FIXED SCOPE
What it demonstrates
- Intake qualification — full ARB, lightweight triage, or standard process
- Review routing across architecture, security, data, and integration domains
- Decision-memory design using prior ADRs, waivers, and override rationale
What gets delivered
- Target-state ARB flow mapped to the client's own inventory
- 2–3 worked scenarios run end to end through the model
- Executive readout — value case and what scaling it requires
Runs above an existing LeanIX, ServiceNow CMDB, or equivalent inventory — no replacement of existing tooling. Scoped as a fixed package rather than day rate, designed to sit against a defined budget line.
Financial Services
Operational risk and control architecture, payments and credit decisioning.
Healthcare
Compliance mapping and data-flow governance under multi-region regulation.
Aviation & Payments
Platform rationalization under strict audit and continuity requirements.
Public Sector
Dependency mapping for large-scale digital consolidation programs.
© 2026 Hari Krishna Bodapati. EA 2.0 is the author's independently developed framework.