The problems aren't new. AI is just generating broken code faster than your reviewers can read it. Without engineering discipline in place, you're paying to add technical debt at machine speed.
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Here's what's happening in legacy codebases right now. AI refactors a function without seeing how three other services depend on it. The code passes review, the deploy goes green, the integration breaks at 2am. Every undocumented workaround in the system becomes a confident new bug.
Every AI-generated function that skips a security review ships 2.74x more flaws than the code it replaced. Your vulnerability backlog is growing faster than your agents can type.
Ninety-five percent of GenAI pilots delivered nothing the CFO could measure. Not because the models failed. Because the codebases they operated on weren't ready for them.
Eight out of ten organizations with deployed agents have already had boundary violations. Unauthorized access, unscoped mutations, cascading failures. The governance gap is real, documented, and widening.
Armakuni builds the engineering foundation first: five AK Way practices that make AI safe to use at scale, plus an agentic orchestration layer that enforces them. The foundation makes AI useful. The orchestration makes it trustworthy.
The orchestration layer is infrastructure you own. Bedrock, Step Functions, IAM, CloudWatch, Audit Manager. Deployed into your AWS Organizations under your IAM, your governance, your audit trail. When the engagement ends, your engineers walk away with the repo, the runbooks, and the commit history.
Five engineering practices that determine whether AI agents make your team genuinely faster or just generate more code for your team to debug. The difference is the AK Way.
Without test-first discipline, AI speed becomes risk your team inherits. Every AI-generated function passes a test contract before it reaches a branch. The test exists before the code does. If the test fails, the PR never opens. Change failure rate drops because broken code stays out of the pipeline.
Your legacy systems weren't designed for agents to operate on. Decades of coupling mean a refactoring agent can't tell boundaries from implementation details. Clean architecture maps the environment so agents operate within defined scopes. Your team stops discovering surprise dependencies in production.
Agents that operate without traces are agents your team can't debug. Observability instruments every action across every agent in the pipeline. When something breaks, the trace shows exactly what happened. Your mean time to recovery improves because the investigation step disappears.
Ungoverned agents with production access are the single biggest risk in agentic modernization. Boundary controls enforce bounded authority, audit trails, and human approval gates. Your team gets provable compliance and the confidence to scale agent usage without scaling risk.
Without measurement, you can't tell improvement from activity. DORA metrics baseline your delivery performance on day one and track it continuously. If deploy frequency, lead time, change failure rate, and recovery time don't improve, the approach changes.
The orchestration layer is thin on purpose. It wires AWS primitives you are already paying for into a single governed flow. No new runtime. No new vendor.
Runs every code-author, test-author, and review agent. Scoped per task, logged per invocation.
Strict PII, secret, and prompt-injection filters at every model call. Policy, not prayer.
Encodes the TDD gate, Inspector scan, and human approval as one state machine. No gate, no merge.
AWS Transform handles the refactor at scale. CloudWatch and X-Ray trace every diff and decision into one log group. Full chain of custody per PR.
Least-privilege per agent, SCPs at the OU level, Control Tower baseline everywhere. Blast radius is a setting, not an argument.
Every AI-authored diff is reviewed by a second agent and scanned for CVEs before the human reviewer ever sees it.
Kudos to Armakuni for demonstrating the speed, precision, and partnership needed to turn a high-speed challenge into a success story.
The Armakuni team demonstrated an impressive ability to earn customer trust and deliver against lofty expectations with the customer C-Suite. Ruben and team maintained consistent communication with the customer, even after initial projects were put on hold for half a year.
95% reduction in downtime across live auction events, so the platform stays available through the moments that drive revenue rather than failing exactly when bidders are most engaged
Four intake channels collapsed into one governed system. Email, fax, encrypted uploads, and paper all enter the platform now. Operations staff work from one interface. Document intake is observable, consistent, and auditable from day one of production.
Median outcomes across recent Evolve engagements where teams ran the AK Way practices and the orchestration layer was deployed in their AWS account.
Your modernization can't start with assumptions. Compass scans your entire portfolio and gives you the picture nobody else has built: what's in there, what it costs you, and what's ready for AI.
Output: a sequenced roadmap built from data, not opinion.
Evolve executes Compass's roadmap. AK Way practices first, agentic orchestration second, then governed AI agents modernize your environment in priority order.
The orchestration layer stays in your AWS account when we leave. Yours outright.
Your engineers bring a real codebase. Ours run Compass on it live. In 90 minutes you'll see the five assessment layers operating on real code, not a prepared demo or a vendor pitch.
A live legacy modernization, start to finish. You'll see TDD catching AI-generated failures before they ship, the orchestration layer stopping an agent from exceeding its scope, and DORA metrics moving in real time. You walk away knowing exactly how governed agentic modernization works and whether it fits your environment.
The testing and CI/CD pipeline your modernized stack actually needs once AI agents are writing code. Bring a real codebase. We wire up TDD harnesses that catch AI-generated regressions, governed PR gates, and DORA metrics that prove the program works.
Thirty-year COBOL cores, monthly regulator cycles, and an AI roadmap the CTO already signed. The orchestration layer keeps every AI action audit-ready for the PRA, FCA, and SEC.
PHI cannot leave the account. Guardrails and SCPs keep every Bedrock call inside HIPAA boundaries. Evolve has modernized claims, scheduling, and EHR-adjacent systems without a single cross-account spill.
Peak-season refactors where a bad deploy costs a weekend of revenue. Canary gates inside Step Functions hold agents to the same release calendar your SREs already run.
Systems where a bad change takes a production line offline. Inspector and Config drift checks run before any Evolve agent touches a service that talks to the shop floor.
Billing stacks that cannot go dark. Evolve targets the adjacencies first, strangles the core last, and keeps the whole carrier graph visible in CloudWatch the entire time.
Award-winning LMS provider for enterprises and mid-size organizations earned C-Suite trust on a regulated edtech platform with the AK Way governance documented for the regulator.
Read use case →
Gavel modernised a live video auction platform with microservices migration and multi-gateway payments shipping in production.
Read use case →One of the largest US payment technology and prepaid solutions companies rebuilt a GLBA- and HIPAA-compliant document platform with policy-as-code on every AWS service.
Read use case →One of the largest cinema networks in the U.S. turned a high-speed application-integration challenge into a success story with AK Way speed and partnership.
Read use case →SMS campaign automation platform for e-commerce and restaurant brands shipped governed agentic modernization with the orchestration layer transferred to their team on exit.
Read use case →Award-winning LMS provider for enterprises and mid-size organizations, the identity platform, One of the largest cinema networks in the U.S., SMS campaign automation platform for e-commerce and restaurant brands. Specific numbers. Named stakeholders.
All case studies →BFSI, healthcare, retail, manufacturing, telco. Constraints by industry. Response by orchestration.
All industries →
Engineering essays, AK Way deep-dives, AWS Premier Partner specializations.
Read insights →Active AWS competencies and service-delivery designations behind modernization work.
Most CTOs know they have tech debt. Almost none know what it costs. Two weeks. Fixed fee. You get the number, the roadmap, and the business case.
Your first conversation is with the solution architect who would run the engagement.