AI agents that do the work, not the demo.

A chatbot answers questions. An agent takes actions, like updating records, sending emails or making decisions, within the rules you set.

Yes. We build remote MCP servers that expose your app’s actions as a short list of tools, behind OAuth, narrow scopes and confirmation steps for anything that moves money or contacts customers. One server works in Grok, Muse custom connectors, Claude and Cursor.

We measure before we trust. Every agent ships with an evaluation set of real cases, confidence thresholds that send uncertain cases to a person, approval steps for actions that move money or reach customers, and an audit log of each decision.

Most engagements start with a 2-week Discovery Sprint ($5,000 fixed fee, credited to your build), followed by a fixed-price build ($25k–$120k per project, 6–16 weeks) or a dedicated team (from $12k per month). The build price is fixed after discovery and billed in milestones tied to demoed features. Model usage is a separate running cost, paid to the model provider from your own account, which we estimate in discovery.

A prototype agent running on your real data takes about two weeks, inside the Discovery Sprint. A production agent with integrations, evaluations, guardrails and monitoring is a fixed-price build of 6–16 weeks, depending on how many systems it touches.

Usually Python with LangGraph for orchestration, MCP for tool access, and models from Anthropic, OpenAI or Google, called directly or through AWS Bedrock or Azure OpenAI. Postgres holds agent state and audit logs. The model stays swappable.

Build in-house when you already employ ML and infrastructure engineers and the agent is core to your product. Hire a team to get the first agent into production at a fixed price, with the code living in your repository from the start so your engineers can take it over.

You do. Code lives in your repository from day one, the IP is yours, and the agent runs in your cloud or on endpoints you control. Model calls go through business API terms that exclude training on your data, with zero data retention where the provider offers it.

Agents need monitoring and regular re-evaluation, because models, prompts and your data change. Every build includes 30 days of support; after that, a monthly retainer or dedicated team covers monitoring, eval runs, model upgrades and new tools.

Yes, if people in the EU use it or its output is used in the EU, even when your company is in the US or UK. You are usually the provider, because the agent runs under your name. Since August 2, 2026 an agent that talks to people must tell them it is an AI at the first interaction, unless that is obvious. High-risk uses such as hiring or credit scoring carry further obligations from December 2, 2027. We build the disclosure, approval steps and audit logs in, and write the provider and deployer roles into the contract.