Engineering
The AI-Infused Lifecycle. The engineering practice behind our platforms.
We embed senior engineers, paired with our agent catalog, inside enterprise delivery teams — and ship software under the same governance the regulator will ask about. Not Copilot. A different operating model.
Our engineers built AgentAnywhere by using it. The same agents, the same tooling, the same discipline — that is what we bring to your delivery teams.
The framing
We call it the AI-Infused Lifecycle. AILC for short.
Most of the conversation about AI in software delivery is about autocomplete inside the editor. AILC is the rest of the lifecycle — requirements, design, test, release, governance, operations — re-organized around an agent catalog that runs under your policies, on your tools, with humans accountable at every decision point.
It is the discipline we built our own platform under. It is the discipline we deploy with the customers who cannot afford AI theater.
How the practice works
Engineers own the outcome. The agents do the heavy lifting.
The pods
Senior engineers paired with our agent catalog. Outcome ownership stays with the people. Pace gets compressed by an order of magnitude.
The agent catalog
The catalog we ship with is the catalog we deploy on. Every agent in production has been used on our own work first — including the work that built AgentAnywhere.
Editor-native
Our software engineering agents live in VS Code, the editor your team already uses. Generation, refactoring, review, test scaffolding — under the policies you set.
The squad model
Six roles. Each paired with the agent that augments the work.
Every pod we embed maps the same way. The roles are familiar. The agents are ours. The accountability stays with the human.
- 01
AI Architect
AI Agent Factory
Orchestrates the lifecycle. Picks the agents, sets the policies, owns the through-line from requirement to release.
- 02
Business Analyst
Requirements Traceability & Verification Agent
Each requirement is captured, mapped to a control, and traced through the build. Regulatory alignment (RBI, Basel, AML) is built in from day one, not retrofitted.
- 03
Product Owner
Backlog Grooming Agent
Prioritization informed by usage data, market signal, and the regulatory deadline calendar. Less politics. Less guessing.
- 04
UX Designer
UX 2 UI Agent
From a design system to working interface code, in the same engagement. Consistency by construction, not by review.
- 05
AI-Enhanced Developers
API Builder & Code Generator
Senior engineers, paired with code-generation and API-construction agents that respect your stack and your security posture.
- 06
AI QA Engineer
Test Coverage Agent + AI Functional Tester
Coverage goes up. Regression cycles get shorter. The defect signal arrives before release, not after.
The agent catalog
Agents on both sides of the release line.
Pre-launch agents shape what gets built. Post-launch agents keep the deployment honest. Both halves of the lifecycle share the same governance posture.
Pre-launch · Build
AI agents inside the SDLC.
Requirements Traceability & Verification Agent
Every requirement maps to a control and a test.
Backlog Grooming Agent
Prioritization with the data and the deadlines.
UX 2 UI Agent
From design system to working interface code.
API Builder
Service contracts and the code that honors them.
Test Coverage Agent + AI Functional Tester
Coverage by construction; regression in minutes, not days.
Post-launch · Operate
AI agents inside operations and compliance.
Monitoring & Metrics Agent
Real-time signal across the live deployment.
Governance Policy Agent
Proactive policy enforcement, not after-the-fact review.
Audit Trail Agent
Immutable evidence for every AI action — auditor-ready.
Intelligent Log Analyzer
Anomaly detection on the production log surface.
Trust, by construction
Speed without losing trust. Both, by design.
Proactive governance
Policies enforce themselves inside the lifecycle — at requirements, at code review, at release. Compliance is the default state, not the audit response.
Continuous observability
Real-time monitoring, anomaly detection, and immutable audit trails for every action an agent takes. Trust is a feature, not a posture.
Regulatory alignment
RBI, Basel, AML, PCI, KYC, and HIPAA — the controls are mapped, the evidence is captured automatically, and the auditor finds the file already prepared.
Runs inside the toolchain you already run.
AILC integrates with the SDLC tools the enterprise has already standardized on — no re-platforming, no rip and replace.
- Jira
- Jenkins
- SonarQube
- GitHub
- Bitbucket
- Azure DevOps
VS Code Extension
The agents your team already works alongside, in the editor your team already uses.
Our VS Code extension is the same toolchain we deploy on. It respects the policies you set — no model leaks, no silent telemetry, no shadow agents. Available to engineering customers as part of the AILC engagement.