Autonomous AI Coding
Agents

Each agent is an autonomous AI system running on a dedicated cloud server with its own Chrome browser. Agents pick tickets, read your codebase, write code, run tests, open pull requests, and close tickets. They operate the same tools developers use: git, IDEs, browsers, task trackers. The platform works with any AI model and any agent framework. You choose the model, you hold the API key.

Agents work with any codebase. Production-tested stacks: Java/Spring Boot, React, Python/Flask, Node.js, TypeScript, Svelte, .NET, React Native, Electron, Astro, Terraform, Kubernetes. The browser bridge lets agents interact with any web-based tool your team uses.

The platform is built on open standards and works with any AI model and any agent framework: Claude, GPT, Gemini, Llama, Mistral, or any model that supports tool use. If an AI model can read this page, it is already compatible. Three components work together. The Browser Agent gives each agent a real browser. It can browse web apps, fill forms, click buttons, and extract data from any tool your team uses (Jira, GitHub, internal dashboards). The Local Server runs on each agent machine and exposes browser automation, workflow execution, and file operations as standard commands, compatible with any AI agent. The Cloud Control Plane assigns jobs to agents, manages queues, runs scheduled workflows, and connects to Jira for automated ticket handling. All three are open-source. You bring your own AI API key. No vendor lock-in.

First pull requests land within 48 hours of deployment. Most teams see their first completed sprint within the first week. In our reference deployment, a 10-agent fleet processes a full sprint backlog in a single session — tickets picked, code shipped, QA verified, PRs merged.

Agents run on dedicated cloud servers in your preferred provider (AWS, GCP, or Hetzner). Each agent has its own isolated environment. Code stays in your infrastructure. The agents interact with your repos through standard Git operations, the same security model as your existing developers.

Augmentation, not replacement. Agents handle the ticket backlog while your senior engineers focus on architecture and code review. A force multiplier for your existing team, not a substitute.

Both plans include the full platform — fleet dashboard, Jira automation, remote desktop, custom skill packs. The difference is team size. Squad gives you 4 agents for a focused cross-functional team (SE, QA, PM, Documentation). Fleet gives you 10 for parallel work across your codebase with any roles you define. Both use dedicated 24/7 servers and your own AI API key.

Cursor, Copilot, and Devin help individual developers write code faster. AICTPO deploys an autonomous engineering team that runs the full pipeline. Agents pick tickets from Jira, write code with Claude Code, open pull requests on GitHub, and verify every change in a real browser. When QA finds a defect, the fix cycle runs automatically — no human needed. You review merged PRs and steer priorities. The agents handle the backlog.

With AICTPO, a 4-agent Squad starts at $125/agent/month ($499/mo total) billed annually. Less than a single junior developer. A 10-agent Fleet is $99/agent/month ($999/mo total). You provide your own AI model API key, so there is no vendor lock-in. Agents run 24/7 on dedicated cloud servers at a fraction of the cost of equivalent engineering capacity.