Hivework is a platform for building, running, and sharing AI agents that handle
recurring work too judgment-heavy for traditional workflow automation.
Classic step runners connect apps well and then break the moment a step requires a
decision. "Is this lead worth routing to sales?" is not a filter you can write.
Hivework is built for exactly that gap: the agent reads context from your connected
systems, makes the call, and when it genuinely isn't sure, it stops and asks you rather
than guessing.
Operators build agents on a visual canvas — persona, behavior, tools, and the workflow
graph — or describe the job in plain words and let the co-builder take a first pass. No
code required. Agents connect to the tools teams already run on, including CRM, billing,
support, email, calendars, and document systems. Once built, an agent runs on managed
compute you don't have to operate, and can be shared with teammates as a working link.
Trust is enforced by design, not by policy. Read actions run freely; write actions —
anything that sends, posts, or changes a record — pause for human approval by default,
and anything the runtime can't classify is treated as a write. Credentials are
encrypted at the application layer and never returned to the client. Every run produces
a receipt: what the agent did, what each step cost, what it produced, and what it
refused to do and why.
Built for ops, RevOps, and support-ops owners at small and mid-sized companies who need
internal automation without waiting on an engineering backlog.