Fusion

Fusion

Open-source software factory orchestration for multi-agent code planning, review, and shipping

66/100MonitorFreeFree

Fusion is promising for technical teams wanting a self-hosted multi-agent pipeline with review gates. It's early preview, so expect bugs and a learning curve, but the planning wizard and Command Center are standouts. Solo coders who just want inline suggestions will find Copilot or Cursor simpler.

Verified 6d ago · liveness 66/100 · cite: rightaichoice.com/tools/fusion

Best for
  • Full-stack developers automating multi-file features and refactors
  • DevOps teams orchestrating autonomous code pipelines with quality gates
  • Startups prototyping entire projects with AI-generated code and review
  • Open-source enthusiasts wanting a self-hosted agent orchestrator
Not ideal for
  • Non-technical users who can't configure git or CLI tools
  • Individual developers who just want inline code suggestions in an IDE
  • Teams needing fully managed, closed-source support
Visit Website

Intermediatenpm install: npx runfusion.ai gets a basic single-node setup running in ~10-30 minutes for a developer familiar with git. Multi-node mesh (adding a server, cloud VM, or phone) adds another 15-60 minutes depending on network config. Zero-config installers (npx, curl, brew) speed the first step, but you'll need to configure model API keys and review gates before your first real mission.Web · CLIAPI availableVerified 6d ago
Pricing
Free
FreeFree tier3 hidden costs
Learning curve
Intermediate
npm install: npx runfusion.ai gets a basic single-node setup running in ~10-30 minutes for a developer familiar with git. Multi-node mesh (adding a server, cloud VM, or phone) adds another 15-60 minutes depending on network config. Zero-config installers (npx, curl, brew) speed the first step, but you'll need to configure model API keys and review gates before your first real mission.
Runs on
WebCLI
API available · 10 integrations
Who it's for
Full-stack developer automating a multi-file featureDevOps engineer orchestrating a refactor across servicesStartup founder prototyping an entire project
Live sentiment
Is Fusion actually worth it?

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Skip it if

Skip Fusion if you're not comfortable with git and CLI tools, if you just want inline code suggestions in your IDE, or if you need a fully managed, closed-source product with vendor support — this is a self-hosted, developer-centric, early-preview tool.

The 30-second take
Biggest gripe

Self-hosting requires running your own nodes (laptops, servers, cloud VMs) — compute and electricity costs are on you, and multi-node setups multiply that.

Price reality

Fusion is $0 — fully open source under MIT, self-hosted. That beats Copilot ($10-39/mo per user) and Cursor (from $20/mo) for teams that already have compute and model API keys. You pay for your own model usage; there's no seat cap, no per-user license, and no enterprise tier lock-in. For a small team, the cost is essentially your model API spend.

In short

Fusion — Open-source software factory orchestration for multi-agent code planning, review, and shipping. Best for Full-stack developers automating multi-file features and refactors, DevOps teams orchestrating autonomous code pipelines with quality gates, Startups prototyping entire projects with AI-generated code and review. Free to use.

What people actually say about Fusion — is it worth it?

We scanned public community sources for Fusion on Jul 30, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.

Viability Score

66/100
Monitor

How well maintained and how widely used is Fusion? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this

Recent activity
90
Traction
100
Site health
95
User sentiment
23
What the vendor publishes
20

Last calculated: September 2026

How we score →

Key Features

  • Automatic task specification: triage agents create PROMPT.md with acceptance criteria
  • Plan → review → execute → review lifecycle with pre/post-merge quality gates
  • Multi-node mesh: connect laptops, servers, cloud VMs, and phones
  • Model router with cheap-tier routing and automatic fallback
  • Per-task model overrides for executor, planner, validator, title, workflow
  • Hierarchical missions (Mission → Milestone → Slice → Feature → Task)
  • Git worktree isolation per task with full git UI and side-by-side diffs
  • GitHub issue/PR sync and auto-merge with conflict resolution
  • Command Center observability: tokens, USD cost, autonomy ratio, model mix
  • Steer agents mid-flight: nudge, pause, re-prompt without losing context
  • Planning wizard that asks structured questions to draft PROMPT.md
  • Auto-generated project docs, changelogs, and task-level runbooks
  • Queryable memory (qmd) for persistent agent memory
  • Inter-agent chat for delegation and coordination
  • Automations and cron-based routines

About Fusion

FreeIntermediateAPI availableWeb · CLI

Fusion is an open-source software factory that orchestrates a fleet of AI agents to plan, build, review, and ship code — turning a rough idea into production-ready changes. It's designed for development teams who want more than inline autocomplete: you describe a task in plain language, and triage agents immediately draft a PROMPT.md spec with concrete acceptance criteria before any code is written. The platform runs on a multi-node mesh, connecting laptops, Mac minis, Linux servers, cloud VMs, and even phones, with state synced across all devices. It's model-agnostic, supporting Anthropic, OpenAI, Gemini, Z.ai, Ollama, Hermes, Droid, Cursor, or any ACP agent, and a smart model router picks the cheapest suitable model per task with automatic fallback. Per-task overrides give you five independent lanes (executor, planner, validator, title, workflow) to control exactly which model does what. Fusion's workflow is Plan → Review → Execute → Review, with configurable pre-merge and post-merge gates for docs, QA, security, performance, and accessibility. When every gate passes, Fusion squash-merges automatically; conflicts are resolved by agents in isolated worktrees, so history stays clean and parallel tasks never collide. The mission manager breaks large work into Mission → Milestone → Slice → Feature → Task, letting you track progress across hundreds of tasks at a glance. The Command Center gives real-time observability into tokens, USD cost, autonomy ratio, per-agent output, and model mix — with CSV and OpenTelemetry export for deeper analysis. You can steer agents mid-flight by nudging, pausing, or re-prompting without losing context, and agents can chat with each other through inter-agent mailboxes, delegate, and clarify. Fusion also ships with planning mode that asks structured questions rather than guessing, and a documentation system that auto-generates docs, changelogs, and runbooks. Queryable memory (qmd) gives agents persistent, markdown-based memory across

Behind the Verdict

We're cautiously optimistic about Fusion. It's not another code generator; it's an orchestration layer that treats the entire dev workflow as an assembly line of agents. If you're running any serious multi-file features or refactors, the ability to have triage agents spec out PROMPT.md files before code is written — that planning wizard is genuinely clever — can save you from the usual AI mess of starting mid-refactor. The multi-node mesh is the real differentiator: you can throw a Mac mini, a cloud VM, or even a phone into the mix, sync state, and let agents work where it's cheapest. That's a level of flexibility that single-assistant tools don't offer. When should you pick Fusion? If you're technical, comfortable with git and CLI, and you're building a product where you want agents to churn through multiple files and keep quality gates — docs, tests, security — enforced automatically. It's ideal for startups prototyping entire features, or DevOps teams that want to automate routine PR workflows with human sign-off at the right points. The Command Center gives you cost, token, and autonomy ratio metrics — that's the kind of observability that enterprise teams demand before they let agents run loose. When should you pass? If you're a solo developer who just wants inline suggestions while typing, this is way too much. Fusion is a full lifecycle tool with a board, missions, and a lot of moving parts. Non-technical users will drown in git and CLI setup. It's early preview — expect rough edges, bugs, and the occasional agent that goes sideways. You'll need to babysit it at first. There's no fully managed cloud offering, so you're on your own for infrastructure and support. Compared to the closest alternatives: GitHub Copilot and Cursor are great for generating code

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Real-world workflow fit

Concrete scenarios for the personas Fusion actually fits — and what changes day-one when you adopt it.

Full-stack developer automating a multi-file feature

You type 'Add dark mode toggle to settings panel'. Triage agents write a PROMPT.md spec with acceptance criteria. The system plans, executes, reviews, and merges the change in isolated worktrees, running docs, QA, security, perf, and a11y gates before auto-merging.

Outcome: The feature ships with tests and documentation, history stays linear, and you only step in at review gates — minutes of oversight instead of hours of implementation.

DevOps engineer orchestrating a refactor across services

You create a Mission → Milestone → Slice → Feature → Task hierarchy for refactoring a legacy codebase. The agent fleet works across your laptop, a Linux server, and a cloud VM, with state synced and work sharded.

Outcome: Progress tracks across hundreds of tasks in the Command Center; you watch cost, autonomy ratio, and per-agent output in real time, stepping in to steer agents mid-flight when needed.

Startup founder prototyping an entire project

You describe a new microservice in plain language. Fusion's triage turns it into a spec, agents plan and build it with CI/CD integration, and auto-generated docs and changelogs keep pace.

Outcome: A working microservice with test suite, documentation, and clean git history lands in hours — letting a small team ship at the speed of a much larger one.

Use Cases

Models Under the Hood

AnthropicOpenAIGeminiZ.aiOllamaHermesDroidCursorACP

as of 2026-09-14

Limitations

  • Fusion is an early preview, open-source software factory that requires self-hosting or manual node setup.
  • It is built on Pi and integrates with Hermes and Paperclip 01, with zero-install execution via npm.
  • The documentation does not provide specific rate limits or context window gating.

as of 2026-08-28

Verification history

We have re-verified Fusion 4 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.

  1. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  2. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  3. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  4. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it

Free to cite with attribution — this page re-verifies continuously.

12-month cost

Project the real annual outlay, including the implied monthly cost when only an annual tier is published.

Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly

Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.

Plans compared

For each published Fusion tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.

Open Source

$0/mo

Ideal for

Technical developers and engineering teams who self-host their tools, want autonomy with observability into AI agent cost and performance, and are comfortable with git/CLI. This is the free entry point — you pay only for your own model API usage.

What this tier adds

Starting tier: $0/mo, open source under MIT — includes the full multi-node mesh, planning wizard, review gates, Command Center, and model router; no paid tiers above it.

Hidden costs & gotchas

What the public pricing page doesn't put in bold. Captured from pricing-page footnotes, contract terms, and recurring complaints.

  • Self-hosting requires running your own nodes (laptops, servers, cloud VMs) — compute and electricity costs are on you, and multi-node setups multiply that.
  • Because you bring your own model API keys (OpenAI, Anthropic, Gemini, etc.), you pay model usage costs directly — Fusion's router picks cheap tiers, but high-volume fleets can rack up API bills.
  • Early-preview maturity means you may spend time debugging, patching, or contributing fixes yourself instead of relying on vendor support.

Where the pricing makes sense

The company stage and team size where Fusion's pricing actually pencils out — and where peers do it cheaper.

Fusion is $0 — fully open source under MIT, self-hosted. That beats Copilot ($10-39/mo per user) and Cursor (from $20/mo) for teams that already have compute and model API keys. You pay for your own model usage; there's no seat cap, no per-user license, and no enterprise tier lock-in. For a small team, the cost is essentially your model API spend.

Setup time & first value

How long it actually takes to get something useful out of Fusion — broken out by persona, not the marketing-page minute.

npm install: npx runfusion.ai gets a basic single-node setup running in ~10-30 minutes for a developer familiar with git. Multi-node mesh (adding a server, cloud VM, or phone) adds another 15-60 minutes depending on network config. Zero-config installers (npx, curl, brew) speed the first step, but you'll need to configure model API keys and review gates before your first real mission.

Switching to or from Fusion

How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.

Migrating in
  • From GitHub Copilot or Cursor: import your existing repos via git; Fusion's worktree isolation and review gates replace inline suggestions with an autonomous pipeline — paste a repo URL and describe your first task.
Migrating out
  • To GitHub Copilot or Cursor: Fusion's git-first design means your repos, branches, and commits are standard git — just clone and open them in any IDE.
  • To a managed CI/CD platform (e.g., GitHub Actions): export your review-gate config as workflow steps; Fusion's auto-merge and gate logic map to standard CI checks.

Integrations

GitHubAnthropicOpenAIGeminiZ.aiOllamaHermesDroidCursorACP

Resources & Guides

Tutorials & Learning

YouTube returned 6 videos for “Fusion”, and we withheld 6: 6 could not be judged, because “Fusion” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Fusion.

Official links

Tools that pair well with Fusion

Common stack mates teams adopt alongside Fusion, with the specific reason each pairing earns its keep.

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Frequently Asked Questions

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