What is Factory?
Factory is an AI software development platform that deploys autonomous agents across every stage of the software development lifecycle for engineering teams and enterprises. It produces working code, automated pull request reviews, test results, documentation, deployment outputs, and incident reports. Engineering teams use it to run a continuous feedback loop from signal intake through triage, planning, code generation, validation, shipping, and monitoring. Factory works across the terminal, IDE, browser, desktop app, and CLI. It supports SaaS, hybrid, on-premises, and air-gapped deployment. The platform operates across every major programming language and more than 100 development frameworks.
Features & Benefits
- Autonomous AI Agents (Droids): Deploy AI software development agents that generate code, review pull requests, run tests, write documentation, and resolve incidents across the full SDLC.
- Missions: Plan and execute complex, multi-step AI software development tasks over hours or days by decomposing work into parallel tracks.
- Automated Code Review: Connect repositories so agents post inline review comments on every pull request or merge request automatically.
- Automated Security Review: Run STRIDE-based security analysis on every pull request, with severity ratings, CWE references, and suggested fixes posted as inline comments.
- Triage Automation: Ingest signals from bug reports, customer feedback, internal conversations, and business requirements, then convert them into planned tasks.
- Documentation Generation (AutoWiki): Analyze the codebase and generate structured, browsable documentation that updates on every push.
- Droid Computers: Give each agent a persistent machine with instant cloud provisioning, bring-your-own-hardware registration, and local model support on your own GPU.
- Multi-Agent Sessions: Run agents across multiple projects at once, monitor progress, and switch between active sessions without losing context.
- Computer Use: Let agents control desktop applications, browsers, and terminals to navigate staging environments, run commands, and pull data from external tools.
- Agent Readiness Tracking: Measure repository maturity and track autonomy progress over time.
- Model Independence: Choose models per task based on cost, performance, and speed, or use Factory Router to select the best model automatically or by rule.
- Skills: Build reusable agent capabilities that work across every Factory surface and check in to the repo for team-wide access.
- Custom Droids: Create specialized subagents with their own prompts, tools, and model configurations.
- Hooks: Enforce policies and automate setup, validation, and post-edit workflows.
- Plugins: Package and share commands, skills, and tools across the team.
- IDE Integration: Connect agents inside VS Code, JetBrains, Zed, and terminal-first editor workflows.
- Cross-Platform Access: Start tasks on desktop, check progress from a phone, and review diffs on a tablet with sessions synced across desktop, web, CLI, and IDE.
- Sovereign Deployment: Deploy fully in the cloud, hybrid, on-premises, or completely air-gapped with no external network access on AWS, Azure, or GCP.
- Integrations: Connect to project management, issue tracking, communication, monitoring, and source control tools.
- Dedicated Compute Allocation: Assign dedicated compute resources that scale to organizational demand.
- Global Language Support: Operate in over 40 languages across every major programming language and framework.
What can Factory do?
- Automate pull request code review
- Generate production code from requirements
- Run automated security review on pull requests
- Triage bug reports and convert them to tasks
- Generate and update codebase documentation
- Execute multi-step software development tasks autonomously
- Monitor deployed software and process incidents
- Run agents in CI/CD pipelines
- Connect AI agents to project management tools
- Deploy AI development agents in air-gapped environments
- Run parallel AI agent sessions across multiple projects
- Automate test validation on new code changes
Real-World Applications
Engineering teams managing large volumes of pull requests can use Factory to run AI software development agents that post inline review comments on every submission automatically. Each comment includes context from the codebase, making the review cycle faster without adding reviewer headcount. Teams already using Factory report significant reductions in the time engineers spend on routine review work.
Enterprises in regulated industries like financial services, healthcare, and government may find Factory’s sovereign deployment options relevant. AI software development can run fully on-premises or in an air-gapped environment with no external network access. Compliance requirements around data handling stay met while the organization still runs autonomous coding, testing, and documentation workflows.
Organizations dealing with incident response backlogs can use Factory to connect monitoring signals directly into the development loop. When deployed software generates an incident, agents can trace it back to the responsible change, surface context, and begin resolution workflows. That kind of AI software development integration across the SDLC reduces the gap between detection and fix.
Product and engineering teams working on large migration projects may benefit from Factory Missions, which break complex AI software development tasks into parallel tracks that agents execute over hours or days. Rather than scoping work manually and assigning it to engineers, teams can define the objective and let agents decompose and execute the work, with humans maintaining oversight at key checkpoints.
