From Requirement to Production Software,
Autonomously.
An AI engineering organization of 13 specialized agents — planning, designing, coding, testing, securing and shipping software end-to-end.
Watch the agents ship a feature.
Pick a requirement and play the pipeline. Each agent produces real artifacts — tickets, code, tests, deployments.
Customers should be able to pay via Stripe-hosted checkout with order confirmation emails.
- ›EP-101 · Stripe Integration
- ›EP-102 · Order Confirmation
- ›EP-103 · Refund Flow
Given a cart, when user clicks Pay, a Stripe session opens; on success, order moves to PAID and email is sent.
Not a copilot. An AI engineering org.
The platform is designed AI-first: multi-agent reasoning, graph-grounded knowledge and event-driven autonomy.
Specialized Agents
Each agent is purpose-built — not a single prompt. Roles like BA, Architect, Security, DevOps act like real teammates.
Agent Orchestration
LangGraph + LangChain choreograph hand-offs. Agents plan, critique and re-plan with shared memory.
Knowledge Graph + RAG
Neo4j stores relationships; Pinecone powers semantic recall. Every decision has provenance.
Continuous Learning
Agents improve from review feedback, code-review outcomes, and production telemetry.
13 agents. One delivery pipeline.
Every stage of the SDLC has a dedicated AI specialist with clear responsibilities and outputs.
Product Manager Agent
Roadmaps, feature prioritization, product insights.
Business Analyst Agent
Parses requirements into epics, stories & acceptance criteria.
Architecture Agent
System design, tech stack selection, DB & API schemas.
Design Agent
Responsive UI generation via Figma with designer approval flow.
Development Agent
Full-stack code generation pushed to GitLab repositories.
Unit Testing Agent
Jest & Playwright suites for APIs and UI components.
QA Agent
Test plans, regression runs, end-to-end validation.
Security Agent
SAST, dependency scans, secrets detection, API hardening.
Performance Agent
Load testing, bottleneck detection, scaling guidance.
Refactoring Agent
Detects code smells, applies patterns, improves maintainability.
Technical Debt Agent
Tracks outdated libs, low coverage, raises improvement tickets.
Documentation Agent
API docs, developer guides, release notes in Confluence.
DevOps Agent
CI/CD via GitLab, deploys to AWS & GCP, staging environments.
Requirements in. Production out.
A structured AI-driven pipeline with human approvals at design review, merge requests and QA validation.
A four-layer AI architecture.
Modular, event-driven and cloud-native. Available as monolith for speed, or microservices for scale.
AI Agent Layer
Autonomous agents executing SDLC tasks via LangGraph / LangChain.
Intelligence Layer
Neo4j knowledge graph + Pinecone vector store for semantic recall.
Orchestration Layer
Kafka-driven events, task scheduling and agent coordination.
Infrastructure Layer
Kubernetes, Docker, AWS & GCP for deployment and scaling.
Why this is different.
A coordinated AI workforce — not another code assistant. Governed, traceable and production-grade by design.
13 Specialized AI Agents
A coordinated AI engineering org, not a single chatbot. Each agent owns its SDLC stage.
End-to-End Autonomy
Requirement → architecture → code → tests → security → deploy. One continuous pipeline.
Human-in-the-Loop Governance
Approval gates at design review, MR merges, and QA sign-off keep humans in control.
Knowledge Graph + RAG
Neo4j + Pinecone link requirements, code, tests and deploys for full traceability.
Event-Driven Orchestration
Kafka + LangGraph route work between agents in real time with full observability.
Built-in Security & Compliance
Continuous scanning, secrets detection, and policy enforcement on every commit.
Ship software at the speed of thought.
See the platform deliver a full feature — from requirement document to deployed application — in a single live demo.