Autonomous AI that executes the full engineering workflow
CoderFlow enables autonomous AI development in complex, decades-old environments where most AI coding tools struggle. Turning potential productivity gains into repeatable outcomes that can run in production.
CoderFlow runs autonomous agents that finish engineering work inside your infrastructure
Agents evaluate their own output using concrete signals—successful builds, tests, and expected runtime behavior—not just generated text.
Compile, test, detect failure, retry, and converge autonomously—reducing dependence on constant human prompting.
Designed for real enterprise environments, not single-repo, greenfield projects.
Multiple agents can propose alternatives, with automated evaluation explaining tradeoffs and selecting validated results.
Humans review verified outcomes in controlled environments instead of driving every step of the AI.
Developers orchestrate objectives and approve results—shifting their role from writing and debugging code to reviewing ready-to-commit, validated outcomes.
Finished Work, Not Suggestions: Coding assistants generate drafts, CoderFlow delivers verified results ready to commit.
All delivered as a persistent, governed enterprise platform—not an ephemeral browser session.
On-premise or private cloud deployment. All execution—builds, tests, validation, and Git operations—stays inside your network.
Only the necessary code snippets are sent to cloud models (Claude, OpenAI, Gemini). No full repositories, credentials, or bulk data leave your environment.
Agents act as secure intermediary. Cloud models never touch your IBM i, repos, databases, or servers. Execution remains local, with only minimal context passed to models.
Least-privilege access, isolated execution, and fully auditable workflows.
All secrets, service accounts, and Git credentials stay local and are never exposed to LLMs.
Role-based access controls, complete audit trails, standardized compliance templates, and developer approval gates.
Agentic coding shifts development from writing code to orchestrating autonomous agents and reviewing their verified outcomes.
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