Multi-agent AI for engineering teams

Requirement in.
Pull request out.

Forge runs a structured agent loop against your local repo — planning, designing, implementing, reviewing — and opens the PR. Your codebase, remembered across every session.

Average requirement-to-PR: 18 minutes
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PRs shipped with Forge
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Engineering teams
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Avg. requirement-to-PR
0 hrs
Avg. hours saved per sprint
Why Forge

Built for the teams
that move fastest.

Zero ramp-up.

Forge reads your repo structure, git history, and existing patterns before touching a line of code. No context-setting. No hand-holding. Just work.

🧠

It gets smarter.

Every session. Every override. Every architectural decision. Captured, stored, retrieved automatically. The next session starts where the last one left off.

🔁

You review. It ships.

Approve the plan. Come back to a reviewed, tested, ready-to-merge PR. That's the entire workflow. No babysitting, no context switching.

Two hours.
Compressed to eighteen minutes.

Without Forge Manual
09:00
Read the ticket Parse the Jira description, hunt for context
09:15
Re-explain the codebase to your AI Again. Like you did last week. And the week before.
09:45
Debug broken context The AI referenced the wrong file. Again.
10:30
Write tests, docs, handle edge cases Manually. Every single time.
11:00
Open the PR Two hours after you started
Total time ~2 hours
With Forge Automated
09:00
forge run PROJ-1234 Forge fetches the ticket. Memory loads automatically.
09:02
Review the implementation plan Approve or edit, then step away.
09:08
Forge builds, tests, and reviews Three-pass review: functional, quality, security.
09:18
PR is open Ready to merge. Memory updated for next time.
Total time ~18 minutes
Under the hood

Five agents. One PR.

A structured pipeline where each agent has a single, well-defined job — no ambiguity, no wasted cycles.

🗺️
Planner
~30s
Analyzes the requirement, scopes the work, asks clarifying questions
🏗️
Architect
~45s
Designs the solution — signatures, models, integration points — without writing code
⚙️
Implementer
5–10 min
Executes the design via Claude Code against your actual repo
🔍
Reviewer
~2 min
Three-pass review: functional correctness, code quality, security
🚀
PR
~10s
Opens the pull request. Memories extracted and stored for next session.
forge run PROJ-847
$ forge run PROJ-847
Loading session memory...

FACT Uses PostgreSQL + SQLAlchemy ORM
FACT Test suite requires real DB (no mocks)
DECISION Auth via JWT, not sessions — ADR-003
PREF snake_case for all internal variables
OVERRIDE Never use bare except clauses (2x flag)

5 memories loaded — starting planner

PLANNER Analyzing PROJ-847...

Built by your team.
Remembered by Forge.

Most AI tools start from scratch every time. Forge builds institutional memory — architectural decisions, team preferences, past corrections — and loads it automatically at the start of every session.

  • 📌
    Facts & decisions

    Tech stack choices, ADRs, integration constraints — captured once, cited across sessions forever.

  • 🔄
    Override capture

    When you correct Forge, it learns. That mistake doesn't happen in session two. Or ever again.

  • 📈
    Compounds over time

    The longer you run Forge, the less you explain. Every sprint adds context. The curve bends fast.

Teams already running Forge.

"We went from 3-day PR cycles to same-day. The memory feature is what made the difference — it actually understands our codebase the way a senior engineer would."

🧑‍💻
Staff Engineer
Series B fintech, 60-person eng team

"New engineers are opening PRs on day one. Forge already knows our conventions, our test requirements, our architecture. Onboarding used to take three weeks."

👩‍💼
VP Engineering
SaaS platform, 180-person company

"The reviewer agent caught a security issue we would have missed. It's not just fast — it's thorough in ways humans at velocity simply can't be."

👨‍🔬
Principal Engineer
Infrastructure team, public tech company

The teams moving fastest
aren't waiting.

Get Forge running against your repo in under two minutes.

pip install forge-cli