Fusion is live · free · last verified 23 Oct 2026 · viability monitor
Fusion
Open-source software factory: AI agents spec, plan, review, and merge code across your own machines
Fusion is worth a serious look if you run a technical team and want a self-hosted pipeline where agents plan, get reviewed, and merge under explicit quality gates rather than free-styling. The standouts are PROMPT.md auto-specification, the Plan → Review → Execute → Review lifecycle, and Command Center cost observability — none of which you get from inline assistants like GitHub Copilot or Cursor, which stay the simpler pick for solo devs who only want suggestions in an editor. It is MIT-licensed and explicitly an early preview, so budget for rough edges and a real git/CLI learning curve.
Verdict generatedVerified 6d ago · liveness 63/100 · cite: rightaichoice.com/tools/fusion
- Full-stack developers automating multi-file features and refactors
- DevOps teams running autonomous code pipelines with quality gates
- Startups prototyping whole projects with AI-generated code and review
- Open-source enthusiasts who want a self-hosted agent orchestrator
- Non-technical users who can't configure git or CLI tools
- Individual developers who only want inline suggestions inside an IDE
- Teams that require a fully managed, closed-source vendor relationship
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Skip Fusion if you want code suggestions inside your editor with no git, worktree, or multi-machine setup — an IDE assistant like GitHub Copilot or Cursor is far less work.
Fusion itself is MIT-licensed at $0, but the model router spends real money per token across Anthropic, OpenAI, Gemini, and Z.ai — the Command Center's USD cost view exists precisely because that bill is yours to carry.
Fusion is MIT-licensed at $0/mo, which puts it in a different bracket from seat-priced IDE assistants or managed agent platforms — your real spend is model tokens, and the model router's cheap-tier routing plus fallback is how you keep that down. Teams already paying per-seat elsewhere can run Fusion alongside an IDE assistant without a second software licence; the trade is that you own the machines and the operations.
In short
Fusion — Open-source software factory: AI agents spec, plan, review, and merge code across your own machines. Best for Full-stack developers automating multi-file features and refactors, DevOps teams running autonomous code pipelines with quality gates, Startups prototyping whole projects with AI-generated code and review. Free to use.
What is Fusion?
Fusion — Open-source software factory: AI agents spec, plan, review, and merge code across your own machines. Best for Full-stack developers automating multi-file features and refactors, DevOps teams running autonomous code pipelines with quality gates, Startups prototyping whole projects with AI-generated code and review. Free to use.
Fusion is an MIT-licensed software factory for AI agents, currently labelled an early preview that ships daily. You describe a task in plain language and triage agents write a PROMPT.md spec with concrete acceptance criteria before any code is written. Work then moves through Plan → Review → Execute → Review, passing configurable pre-merge and post-merge gates for docs, QA, security, performance, accessibility, and UX; when everything is green Fusion squash-merges, and conflicts are resolved by agents inside isolated git worktrees so parallel tasks never collide. It is built for technical teams rather than autocomplete shoppers: a multi-node mesh connects laptops, Mac minis, Linux servers, cloud VMs, and phones with shared board, mission, and settings state, and a model router with cheap-tier routing and fallback spreads work across Anthropic, OpenAI, Gemini, Z.ai, Ollama, Hermes, Droid, Cursor, or any ACP agent. Five independent model lanes — executor, planner, validator, title, and workflow — can be overridden globally, per project, or per task. Large work is organised hierarchically (Mission → Milestone → Slice → Feature → Task), the Command Center exposes tokens, USD cost, autonomy ratio, per-agent output, model mix, and system vitals across eleven views with CSV and OpenTelemetry export, and you can nudge, pause, or re-prompt agents mid-task without losing context. Extras include GitHub issue and PR sync, auto-generated docs, changelogs and runbooks, queryable markdown memory (qmd), inter-agent mailboxes, agent performance reviews that sharpen AGENTS.md, cron-based automations, and a plugin system that runs every Pi extension. It ships via npm (npx runfusion.ai), an install script, or Homebrew.
Key features
- Triage agents auto-write a PROMPT.md spec with acceptance criteria before any code is written
- Plan → Review → Execute → Review lifecycle for every task
- Configurable pre-merge and post-merge gates: docs, QA, security, performance, accessibility, UX
- Multi-node mesh connecting laptops, Mac minis, Linux servers, cloud VMs, and phones
- Model router with cheap-tier routing and automatic fallback across vendors
- Five per-task model lanes: executor, planner, validator, title, workflow
- Hierarchical missions: Mission → Milestone → Slice → Feature → Task with autopilot progress tracking
- Git worktree isolation per task with in-app branches, worktrees, stashes, remotes, and side-by-side diffs
- GitHub issue and PR sync with squash auto-merge and agent conflict resolution
- Command Center observability: tokens, USD cost, autonomy ratio, per-agent output, model mix, eleven views, CSV + OpenTelemetry export
- Steer agents mid-flight: nudge direction, tighten constraints, pause, or re-prompt without restarting
- Auto-generated project docs, changelogs, and task-level runbooks kept current as code ships
- Queryable markdown memory (qmd) shared across sessions, devices, and teammates
- Inter-agent mailbox chat for delegation, clarification, and coordination
- Agent performance reviews that update AGENTS.md with sharper prompts and new skills
Behind the verdict
Fusion's core bet is that the hard part of agentic coding is not generation but verification, and the product is shaped around that. Before a single line of code exists, triage agents turn your rough idea into a PROMPT.md spec with acceptance criteria. Every task then runs Plan → Review → Execute → Review, and configurable gates for docs, QA, security, performance, accessibility, and UX have to go green before Fusion squash-merges. Conflicts get resolved by agents inside isolated worktrees, so parallel tasks do not collide and main history stays linear. The second bet is model and machine neutrality. The router picks per task with cheap-tier routing and fallback, and the five lanes (executor, planner, validator, title, workflow) can be overridden globally, per project, or per task — so you can run a cheap model for titles and drafting and a stronger one for validation. The multi-node mesh lets agents run headless, remote, or on a LAN across laptops, Mac minis, Linux servers, cloud VMs, and phones, with board and mission state synced. The third is observability, which is where most agent tooling goes quiet. Command Center tracks tokens, USD spend, autonomy ratio, per-agent output, model mix, and system vitals across eleven views, with CSV and OpenTelemetry export — enough to actually decide which model runs which lane instead of guessing. Where it bites: this is an early preview that ships daily, and it assumes you are comfortable with git, worktrees, CLI installs, and running your own infrastructure. Setup comes via npx runfusion.ai, an install script, or Homebrew, and you own the operations afterwards. The material available for this review did not state published rate limits or context-window gating, so do not plan around specific numbers. Teams that want a managed, closed-source vendor relationship, or developers who only want inline completion inside an IDE, are better served by Cursor or GitHub Copilot.
Models under the hood
as of 2026-10-22
Limitations
- Fusion is an open-source early preview that ships daily, so expect rough edges and a real learning curve.
- It assumes comfort with git, worktrees, CLI, and self-managed multi-node infrastructure — you run agents across your own machines, so you own the operations.
- Install paths are npx runfusion.ai, an install script, or Homebrew.
- The material reviewed here does not state rate limits or context-window gating, so don't plan around published numbers for either.
- Gate configuration (docs, QA, security, performance, accessibility, UX) is per project and takes tuning before it stops blocking legitimate merges.
as of 2026-10-19
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Is Fusion still active?
Fusion is live · free · last verified 23 Oct 2026 · viability monitor.
Viability score
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
Last calculated: October 2026
How we score →What do users say about Fusion?
What people actually say about Fusion — is it worth it?
Our community sentiment research written Jul 30, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Fusion— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 23 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Fusion 8 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.
- — changed features, summary, limitations, hidden costs, who should skip it, setup time, pricing fit, our verdict, description, switching out, switching in
- — changed limitations
- — changed setup time, description, our verdict, features, hidden costs, limitations, switching in, switching out, who should skip it, pricing tiers, pricing fit, who it suits, summary, use cases
- — changed SSL certificate
- — changed summary, description, pricing tiers, features, our verdict
- — changed domain expiry
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Fusion cost in 2026?
Fusion: Free to use. Pricing last verified 23 Oct 2026.
Plans compared
Every published Fusion tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Open Source | Free | — | Technical teams that want a self-hosted, MIT-licensed agent pipeline and are willing to run their own machines and pay model providers directly.Adds: Starting tier and only published plan: $0/mo, including the full core feature set — triage specs, Plan → Review → Execute → Review, gates, multi-node mesh, model router, and Command Center. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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 MIT-licensed at $0/mo, which puts it in a different bracket from seat-priced IDE assistants or managed agent platforms — your real spend is model tokens, and the model router's cheap-tier routing plus fallback is how you keep that down. Teams already paying per-seat elsewhere can run Fusion alongside an IDE assistant without a second software licence; the trade is that you own the machines and the operations.
Has Fusion's pricing changed?
No plan price for Fusion has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Fusion?
Pick Fusion if you are Full-stack developers automating multi-file features and refactors, DevOps teams running autonomous code pipelines with quality gates, Startups prototyping whole projects with AI-generated code and review, Open-source enthusiasts who want a self-hosted agent orchestrator.
Look elsewhere if you are Non-technical users who can't configure git or CLI tools, Individual developers who only want inline suggestions inside an IDE, Teams that require a fully managed, closed-source vendor relationship, Projects with extremely large monorepos that strain the model router.
Skip it if Skip Fusion if you want code suggestions inside your editor with no git, worktree, or multi-machine setup — an IDE assistant like GitHub Copilot or Cursor is far less work.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Fusion actually fits — and what changes day-one when you adopt it.
You type 'add dark mode toggle to settings panel' into the board, triage writes PROMPT.md with acceptance criteria (toggle persists in localStorage, respects prefers-color-scheme, covered by tests, reviewed before merge), and the task runs Plan → Review → Execute → Review in its own worktree with docs and QA gates.
Outcome: A squash-merged change with tests and an updated changelog, without hand-managing a branch or writing the spec yourself.
You connect a laptop, a Mac mini, a Linux server, and a cloud VM to the mesh, shard a backlog of maintenance tasks across them, and watch token spend, autonomy ratio, and model mix in Command Center, exporting the metrics via OpenTelemetry into your existing dashboards.
Outcome: Parallel agent throughput across hardware you already own, with per-agent cost visible in the same monitoring stack as the rest of your infrastructure.
You model the work as a Mission → Milestone → Slice → Feature → Task hierarchy, let autopilot track progress across hundreds of tasks, and steer individual agents mid-flight — nudging direction or tightening constraints — when a review comes back off-target.
Outcome: A multi-week refactor that stays reviewable and cost-accountable instead of turning into an untracked pile of agent commits.
Use cases
- Turn a one-sentence feature description into a merged change with tests and updated docs.
- Run several agent tasks in parallel across worktrees without branch collisions.
- Orchestrate refactors of a legacy codebase spanning multiple services and milestones.
- Keep continuous review and auto-merge running on incoming pull requests.
- Stand up a new microservice with CI/CD pipeline integration from a written spec.
- Track a mission of dozens or hundreds of tasks across distributed nodes.
- Watch token spend and per-agent output to decide which model runs which lane.
- Automate routine maintenance with cron-based routines and webhook triggers.
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.
Comfortable with git and a terminal: minutes to first task via npx runfusion.ai, an install script, or Homebrew, then a few hours tuning gates and model lanes before the pipeline runs unattended. Non-technical users: not a realistic setup path. Multi-node mesh adds an afternoon of connecting and syncing laptops, servers, and VMs.
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.
- →From working directly in an IDE assistant: keep the editor for inline suggestions and route multi-file work to Fusion's board, where triage writes the spec and gates catch what a chat session wouldn't.
- →From a single-model agent script: point the model router and per-task lanes at your existing providers instead of hardcoding one, and wrap the script's steps in Fusion workflow gates.
- →From an agent-company package: run npx companies.sh add to import roles and skill packs, since Fusion uses the same package format as Paperclip.
- ↗To GitHub Copilot or Cursor: continue in the editor for inline suggestions; Fusion's value is in the review gates and merge automation, so you lose the spec-first lifecycle rather than any code.
- ↗To a managed agent platform: your worktrees and git history carry over unchanged because Fusion commits to standard git branches.
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
What are the best Fusion alternatives?
The closest alternatives to Fusion we list are Cursor, Aidevops and Refact.ai. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Cursor | Freemium | Pricing not published | — |
| Aidevops | Free | Free | — |
| Refact.ai | Freemium | Pricing not published | — |
Alternatives to Fusion
View all
Tools that pair well with Fusion
Common stack mates teams adopt alongside Fusion, with the specific reason each pairing earns its keep.
Cursor
Cursor is an AI coding agent that plans, builds and ships features from your editor, CLI, Slack, GitHub and iOS.
Aidevops
AIDevOps is an open-source AI DevOps harness that plans, builds and verifies code in isolated Git worktrees before merge.
Refact.ai
Open-source autonomous AI coding agent for VS Code and JetBrains that plans, executes, and deploys tasks with step-by-step reasoning.
Fusion vs its closest rival
Fusion's closest head-to-head is with Locus Robotics — Choose Locus Robotics if your bottleneck is physical warehouse throughput — it’s proven AMR automation that boosts productivity 2-3x with minimal facility changes, ideal for high-volume fulfillment centers. Choose Fusion if your bottleneck is software delivery speed — it’s a free, open-source agent orchestrator that turns plain language into production code with rigorous quality gates. They solve completely different problems, so align your choice with your primary operational challenge. Verdict generated
Head-to-head comparisons
Fusion vs Locus Robotics
Choose Locus Robotics if your bottleneck is physical warehouse throughput — it’s proven AMR automation that boosts productivity 2-3x with minimal facility changes, ideal for high-volume fulfillment centers. Choose Fusion if your bottleneck is software delivery speed — it’s a free, open-source agent orchestrator that turns plain language into production code with rigorous quality gates. They solve completely different problems, so align your choice with your primary operational challenge.
GeneratedFusion vs Presto Voice
If you run a QSR chain and want to boost drive-thru revenue with voice AI, Presto Voice is the turnkey enterprise solution. If you're a developer automating code generation, Fusion's open-source orchestrator is free and highly flexible. Choose Presto for operational ROI, Fusion for software velocity.
GeneratedFusion vs Truleo
Truleo and Fusion serve entirely different domains. Truleo is a specialized law enforcement intelligence platform that automates lead generation and report writing across siloed data, while Fusion is an open-source agent orchestrator for software development. If you're a police department, Truleo is your only choice. If you're a developer automating code generation, Fusion's free, open-source approach wins hands down. Choose based on your sector — not comparable in functionality.
GeneratedFrequently asked questions
Used Fusion? Help shape our editorial sentiment research.