Factory AI (Droids)

✓ Editorially verified

Agent-native platform that runs the whole software development lifecycle with autonomous Droids.

Freemium· Pro $20/user/mo · Plus $100/user/mo · Max $200/user/mo · Business (up to 150 seats, custom) · Enterprise (unlimited seats, custom, on-prem/air-gapped available)CodingModel-agnostic: GPT-5, Claude Opus/Sonnet, Gemini, plus open-weight models

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Best for

Mid-to-large engineering teams that want supervised autonomous agents across the full SDLC — planning, coding, PR review, release and incident response — with enterprise controls like SSO, ZDR and on-prem deployment.

Skip if

Solo developers on a tight budget or hobbyists who just want inline autocomplete in their editor — a cheaper IDE assistant like Copilot or Cursor is a better fit.

Factory is an agent-native software development platform built around 'Droids' — long-running AI coding agents that work across the full SDLC rather than just autocompleting inside an editor. Engineers interact with Droids through a desktop app, CLI, and SDK, and can dispatch work to cloud or local background agents that ingest context from repositories, tickets, docs, incidents, and observability signals. A Droid can be pointed at a Jira/Linear ticket, planned, coded, self-reviewed, opened as a PR, validated against tests, and shipped, with the platform tracking cycle time, deployment frequency, token efficiency and incident metrics on an analytics dashboard. Factory is deliberately model-agnostic and routes work across GPT-5, Claude Opus/Sonnet, Gemini and open-weight models depending on the task, with a 'Best of all' selection layer. It ships as SaaS, hybrid cloud, on-prem, or fully air-gapped, and offers Droid Computers — Factory-managed sandboxed cloud environments for the agent to execute in. Typical workflows include large-scale refactors, framework/version upgrades, backlog burn-down, on-call triage of production incidents, spec-to-PR feature work, and documentation drift. Target customers are mid-to-large engineering orgs that want to move beyond IDE autocomplete into supervised autonomous agents — Factory publicly cites Blackstone, Adyen, Wipro, Groq, You.com and Chainguard among users. Business and Enterprise tiers add SSO/SAML, zero data retention, audit logging, customer-managed encryption, data residency, dedicated compute with partitioned inference, and sub-organizations for platform teams that need to govern multiple product groups.

Editor's take

Factory is one of the more credible attempts to move AI coding beyond autocomplete into a governed, agent-run SDLC. The multi-surface story (desktop, CLI, SDK, cloud agents) and the on-prem/air-gapped options make it a rare option for regulated shops. Pricing and setup only pay off if you actually let the Droids run work end-to-end; treated as a fancy autocomplete, it's overpriced.

— The AI Tool Bible editorial team

Pros

✅ Covers the whole SDLC — triage, planning, coding, validation, release, docs, monitoring — not just inline code completion
✅ Model-agnostic routing across GPT-5, Claude Opus/Sonnet, Gemini and open-weight models, with BYOK on higher tiers
✅ Multiple surfaces: desktop app, CLI, and SDK, plus cloud or local background agents
✅ Deployment flexibility including SaaS, hybrid, on-premise and air-gapped installs suitable for regulated enterprises
✅ Droid Computers provide managed sandboxed environments so agents can actually execute, test and iterate
✅ Enterprise-grade controls: SSO/SAML, ZDR, audit logs, customer-managed encryption, sub-organizations, priority SLAs
✅ Analytics dashboard exposes cycle time, deployment frequency, MTTR and token efficiency for governance

Cons

⚠️ No free tier — paid subscription starts at $20/user/mo and higher tiers jump quickly to $100 and $200
⚠️ Positioned for engineering orgs; solo hobbyists get less value than from a plain IDE assistant
⚠️ Autonomous multi-step agents still require human review for non-trivial changes and can burn tokens on wrong paths
⚠️ Underlying model behaviour depends on external providers, so quality and latency shift as those models change
⚠️ Newer platform relative to Copilot/Cursor, so ecosystem of third-party integrations and community recipes is smaller

Use cases

Autonomous ticket-to-PR feature workLarge-scale codebase refactorsFramework and dependency version upgradesBacklog burn-down with background agentsOn-call incident triage and remediationAI-driven code review and validationDocumentation generation and drift repairTest authoring and coverage expansionLegacy code modernisationEngineering metrics and cycle-time analytics