AI Agent Development for Education & EdTech

Most agent projects stall at the demo. Ours ship because we start from the failure modes, what the agent must never do, who approves what, and how every action gets traced, and build the capability around those constraints.

In education & edtech, student data protection and academic integrity constrain what may be automated at all. That single fact reshapes how ai agent development has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is content adaptation by level, usually integrated against LMS. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.

Multi-model by default, so a provider outage is a routing decision rather than an incident. You own the code, the models where they are open-weight, and the documentation to run it without us.