Product

AI-Assisted SDLC

Stop vibe coding. Ship with structure.

Enterprise AI coding workflow optimization that replaces ad-hoc prompting with structured SDLC questionnaires. Every role — from Business Analyst to Tester — gets guided AI interactions that produce consistent, auditable, high-quality code. For a 50-developer team: 40% less rework, 60% faster AI onboarding, and $780k+ in annual developer time saved.

Request a Pilot Talk to Sales
// the_problem

Enterprise developers are vibe coding.

✕ Coding without clear requirements or architecture
✕ Each developer prompts AI differently — variable results
✕ Knowledge doesn't flow between SDLC phases
✕ AI learns per-developer, not per-team
✕ No audit trail for AI-generated code
✕ Compliance gaps that block enterprise adoption
// five_phases

Structured Workflows for Every Role

Our SDLC platform guides each role through phase-specific questions that capture the right context at the right time.

01

Business Analyst

Requirements, acceptance criteria, user stories

02

Architect

Tech stack, patterns, data flow, security

03

Senior Developer

Code patterns, error handling, standards

04

Developer

Implementation details, edge cases, dependencies

05

Tester

Test strategy, coverage, key scenarios

Context flows automatically: BA → Architect → Senior Dev → Developer → Tester

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How It Works

SDLC-First Questionnaires

Structured questions for each role in the development lifecycle. No more ad-hoc prompting — every AI interaction is guided by proven workflows.

Phase-specific question sets capture the right context at the right time, from requirements through testing.

Context Threading

Information flows automatically between SDLC phases. Architects get BA requirements. Developers get architecture decisions. Testers get both.

Zero manual handoff. Every phase inherits the decisions and constraints from upstream.

Organizational Learning

Prompts improve based on team outcomes, not individual behavior. When a prompt structure reduces review iterations by 40%, the whole team benefits.

Powered by DSPy optimization — your AI prompts get smarter with every sprint.

Compliance & Audit Trail

Full traceability: code → prompt → requirement. Every AI-generated artifact is logged with who, when, what phase, and what outcome.

Enterprise-grade audit trail powered by Langfuse. Export to JSON, CSV, or PDF.

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Works Where You Work

VS Code Extension

IDE-native sidebar with guided questionnaires and AI chat

Built on Continue.dev

Desktop App

Standalone Electron app with full feature set and local SQLite storage

Electron + React + Vite

CLI

Interactive terminal UI for quick workflows and CI/CD integration

Node.js TUI

MCP Server

Model Context Protocol server for Claude, Cursor, and any AI assistant

Works with Claude Desktop
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Technology Stack

Continue.dev

VS Code integration, AI chat

Langfuse

LLM observability & audit trails

DSPy

Automatic prompt optimization

Electron

Desktop app framework

TypeScriptReact 18ViteTailwind CSSZustandPythonFastAPIPostgreSQLRedisSQLiteDrizzle ORMpnpm + Turborepo
// how_we_deliver

See the work behind the platforms

Four client systems built by the same team — IT support, field-service scheduling, insurance sales and contractor compliance. Real numbers wherever clients have released them.

Read the case studies How a 4-6 week sprint works

Stop vibe coding.
Start shipping with structure.

Run a pilot and see how our SDLC platform transforms your team's AI coding workflow.

Request a Pilot