Custom Software Built by AI Agent Teams

Autonomous AI agents are ongoing systems that run continuously, performing jobs like research, content production, or data analysis on a daily or weekly basis. Agentic development is project-based: we use AI coding agents to build you a piece of software, deliver it, and you own it. One is a service you subscribe to, the other is a product you purchase.

Yes, completely. You own the code, the documentation, and every asset we produce. It deploys to your infrastructure, runs on your servers, and is fully maintainable by your team or any competent developer. We don’t lock you into a proprietary platform or ongoing dependency.

The same thing that happens with human-generated code: we find them and fix them. Our process includes automated testing, senior engineer review, and production validation before delivery. AI agents are actually quite good at writing tests for their own code, which catches many issues before they reach you. Post-delivery, we include a support window for any bugs discovered in normal use.

Yes. AI coding agents can read, understand, and extend existing codebases. This makes them well-suited for adding features to an existing application, refactoring legacy code, or building integrations between systems you already run. We’ll need access to your repository and documentation about the current architecture.

Most modern web and application stacks: React, Next.js, Node.js, Python, TypeScript, PostgreSQL, MySQL, MongoDB, Redis, AWS, Supabase, Docker, and many more. AI coding agents have been trained on virtually every popular framework and language. If your stack is uncommon, we’ll tell you upfront whether agentic development is a good fit.

Cursor and Copilot are AI-assisted coding tools: a developer writes code with AI helping on individual functions and suggestions. Agentic development uses coordinated networks of AI agents that handle entire implementation workflows, from writing code to generating tests to building configurations. The difference is like having an AI helper pass you a screwdriver versus having an AI construction crew build the house while you review the blueprints. We also bring 27 years of production architecture experience to the planning phase, which is what makes the output reliable and deployable.

It means AI agents wrote every line of application code, every configuration file, every test, and every schema. Humans directed the work: defining requirements, making architecture decisions, reviewing output, and validating the final product. Humans contributed judgment and expertise. Agents contributed implementation. The Voice Intelligence Platform case study is a concrete example of this in practice.

Project-based, scoped after an initial discovery conversation. Most projects fall between $1,000 and $25,000+ depending on complexity, number of integrations, and the level of custom architecture required. Simple tools and single integrations tend toward the lower end. Multi-system platforms with complex business logic tend toward the higher end. We’ll give you a fixed quote before any work begins.