Analyze
A revenue-growth analyst on your numbers
Grounded in the company’s own data — scenario comparisons, P&L bridges, and risk flags, live in conversation.
Compare the Q4 scenarios and show me the bridge.
P&L bridges · scenario runs · live
AI agents that do real work on your business.
enact agents read your data, reason with full context, and act on your behalf — analyzing revenue scenarios, finding growth opportunities, and running the follow-up work. You review and approve; they finish.
688 opportunities surfaced · 24,600+ SKUs · every action logged
Example agent run: the agent reads third-quarter revenue from the warehouse, builds a profit-and-loss bridge, flags margin risk in three accounts, drafts a follow-up scenario, waits for your approval, and — once you approve — sends the finished work to the finance workspace. Every action is logged to an audit trail.
Not another chatbot
Most AI assistants generate and summarize.
That’s where enact starts.
enact agents are grounded in your data, remember what they’ve learned, and ask before they act. Less admin about the work — more work actually finished.
Three agents, already on the job
Agents already doing the work.
Discover
A growth cockpit for a commercial VP
Surfaced hundreds of concrete growth opportunities from messy source systems — ranked, explained, and ready to act on.
Where are we leaving growth on the table?
688 opportunities · 391 accounts · 24,600+ SKUs
Operate
Agents running the day-to-day
Ongoing operations — cases, tasks, approvals, and durable memory across fourteen workspaces. Humans stay in the loop.
Keep the follow-ups moving. Ask me before anything ships.
14 workspaces · approvals · humans in the loop
688
growth opportunities surfaced
391
accounts analyzed
24,600+
SKUs read from source systems
from one Discover deployment — live for a commercial VP
The enact runtime
An agent is only as good as what’s underneath it.
Most AI products skip this layer. enact is built on it: every agent grounded in your data, durable memory that compounds, and every action wrapped in approvals and audit.
▚Grounding
Every agent reads from your systems — warehouses, files, source apps — with access you scope and control. No hallucinated numbers; answers trace back to your data.
▞Durable memory
Agents remember decisions, context, and outcomes across sessions and workspaces. The tenth week of work builds on the first.
▣Approvals & audit
Actions wait for a human yes. Everything that happens — every read, every write, every send — is written to the log.
Agents ask before acting.
You decide what they can access.
Every action is logged.
For developers — the same runtime is what you build on: grounding, memory, approvals, and audit as primitives, not another chat wrapper.
Talk to the teamHow it works
Delegate outcomes, not tasks.
01 · CONNECT
Point enact at your data
Files, warehouses, and the systems you already run. Access is scoped by you, from day one.
02 · DELEGATE
Say what you need
Not how to do it. Agents plan the work, ground it in your data, and run it end to end.
03 · REVIEW & APPROVE
Get finished work
You get an outcome and a decision to make. Approve, and the follow-through ships — logged.
Built for both sides of the house
Business asks. Engineering trusts.
Business teams
Finished analysis, executed follow-ups
No prompt engineering, no babysitting. You review outcomes and approve actions — the agents handle the work in between.
Request a demoDevelopers
A real runtime to build on
Grounding, durable memory, approvals, and audit as primitives. Build agents that survive contact with production — and with compliance.
See the runtimeSee enact on your data.
Thirty minutes, a live agent on a problem like yours. You bring the question; the agent finishes the work.