Agents that work inside your processes, alongside your teams, grounded in the same context.
vs the work AI should do
Reading a thousand documents in the time it takes to open one. Pre-filling forms. Spotting the pattern that breaks across a hundred submissions.
Approvals, exception calls, escalation judgments — decisions only a human can be accountable for. AI prepares, humans decide, the record proves it.
SELF IMPROVING
Every run makes your agents sharper, without anyone writing test cases. The more you run, the better your agents get.
grading
Moxo runs the whole process, so it grades the real result — the document signed unchanged, the review nobody reopened.
Built-in evals, tracing, and live monitoring
Agents graded on outcomes, not answers. A reviewer reopens what your agent approved — Moxo saw that, and your agent learns from it.
Every run traced end to end: what the AI saw, what it recommended, what the human decided.
Supervisor agents watch the work live, flagging anomalies before they reach a human step — or a client.
context graphs
Every run writes to a living context graph — people, decisions, outcomes. It never leaves your perimeter, and every workflow gets smarter for it.
AGENT FOUNDRY
Design agents grounded in your operation, bring your own, and put supervisors on the steps that matter most.
Learn more →
By the numbers
98.3%
SLA adherence
83%
Avg cycle time reduction
4.7×
increase in throughput
"When I saw Moxo, it was like, 'Wow, was this built for us?' Our processing time is cut in half. The fact that we're able to scale to different services at a rapid rate has been huge for us."
Evan James, CEO at Peninsula Visa
On outcomes. Moxo runs the process, so it sees whether the work held up — not whether the answer looked right.
No. Your context graph stays inside your perimeter — never pooled, never used to train anyone else’s Moxo.
Supervisor agents catch issues and escalate to a human. Decision tracing reconstructs exactly what the AI saw and recommended.
Yes. Every run is traced — agent actions, model recommendations, human decisions — with live monitoring by supervisor agents and outcome-based evaluation built in.
