A custom AI agent is the right tool when the work isn't a single prompt or a single pipeline - it's a small project that has to happen reliably, at volume, with judgement. Research a prospect across twelve sources and write a one-page brief. Reconcile a vendor invoice against three systems and flag the discrepancies. Draft a contract red-line, cite the clauses, and route it for review.
We do not ship "a chatbot." We ship a scoped agent: a clearly-bounded loop that perceives, plans, acts, and reviews, with an allow-list of tools, a step budget, a spend cap, an auditable trace, and a human-in-the-loop where the stakes warrant one.
Bounded autonomy is the whole game. The agent is allowed to be smart; it is not allowed to be unobservable, unstoppable, or unbounded. Every Praxis agent ships with a kill switch, a replay tool, and a runbook your team can use to inspect any decision after the fact.
[ 03.2.B ]What we build
- Research agents. Multi-source briefs on prospects, candidates, vendors, or markets - with citations, structured output, and a one-pager you can hand to a partner.
- Drafting agents. Long-form documents in your voice and your structure: contracts, RFP responses, case files, exec summaries.
- Operator agents. Persistent agents that drive real systems: book the meeting, file the ticket, open the PR, post the update, on a schedule or on demand.
- Reviewer agents. The other side of the loop: agents that grade, redline, and flag - against your style guide, your policies, your contracts.
- Internal copilots. A team-shaped chat surface that knows your wiki, your CRM, and your codebase, with retrieval that doesn't hallucinate.
[ 03.2.C ]How we work
Engagements run 8 to 14 weeks. Discovery (2 weeks) maps the task end-to-end with an operator, defines the eval set, and writes the scope contract. Build (4 to 10 weeks) is the founder writing the loop, the tools, the guardrails, and the eval harness against real data. Handoff (2 weeks) sits with your team, transfers credentials, walks through the trace explorer, and rehearses the kill switch.
Every agent runs on your models, your credentials, your infrastructure. We hand back the prompts, the tools, the eval set, and the diagrams. You can fork, modify, and extend without us in the loop.