Multi-agent architecture for AI-powered software development.

Forge coordinates specialised AI agents into production pipelines — with validation, traceability, and reproducibility built in.

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The problem

AI-assisted development today is fragile. You prompt a model, review the output manually, paste it into your codebase, and hope it integrates cleanly. The gap between raw LLM output and production-ready code is entirely manual. Scale that across a real development operation and you've built yourself a bottleneck, not a workflow.

There's no orchestration layer. No validation pipeline. No way to coordinate multiple AI agents across different stages of a software build — architecture, implementation, testing, documentation — and ensure they produce consistent, quality-checked results.

Teams are building production software on tools designed for single-shot prompting. The gap between "AI demo" and "AI in production" is a systems problem. It requires agent coordination, validation gates, artifact traceability, and automated repair flows. Most AI tools don't offer any of these.

What Forge does

Route

Direct tasks to specialised AI agents based on the work type. Forge selects the right models and tools for each pipeline stage — architecture, code generation, testing, documentation.

Coordinate

Orchestrate multi-agent pipelines where each stage feeds the next. Manage dependencies between agents, handle failures gracefully, and ensure consistent data flow across the build.

Validate

Run structural, semantic, and quality checks on every output. Validation reports accompany every artifact — code, tests, documentation — proving it meets your standards before it ships.

Package

Bundle validated artifacts into deployment-ready formats. Tested code, documentation, configuration — whatever your delivery pipeline needs, Forge prepares it.
The architecture

Forge pipelines coordinate specialised AI agents through a strict architectural model. Each agent produces traceable artifacts that flow through validation before delivery.

Input Specification

Structured specifications. Requirements, constraints, and quality rules — not open-ended prompts.

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Agent Orchestration

Route to specialised agents. Coordinate stages. Track every decision.

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Validation Layer

Structural, semantic, and quality checks at every stage.

Artifact Packaging

Format for delivery. Include validation certificates and run traces.

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Delivery

Production-ready output. Full run traceability. Deploy with confidence.

Product vision

Forge Knowledge

Converting organisational expertise into structured AI systems.

Forge Knowledge is the product layer built on Forge's AI infrastructure. It takes expertise, documents, and workflows from organisations and structures them into validated AI systems — training content, operational playbooks, AI agents, and knowledge products.

The Code Build Engine is the first domain pack built on this infrastructure. More domain packs will follow as the platform matures.

First domain pack

Code Build Engine

Our first domain pack. Multi-agent pipelines for software development — from specification to tested, documented code.

The Code Build Engine is a specialised Forge pipeline for software development. Give it a specification — requirements, architecture constraints, quality standards — and it coordinates AI agents across planning, implementation, testing, and documentation to produce validated, deployment-ready code.

Explore the Code Engine
Early pilot

Forge is in early pilot. We're working with teams building AI-powered development workflows who need validation, traceability, and reproducibility across their pipelines. If that sounds like you — let's talk.

Request pilot access