Four jobs the harness does for you
Start with the one that hurts most. They share the same foundation.
Ground agents
Agents misread terms like "active customer" or "approved spend" because nobody told them which definition applies. The ontology and semantic layer give every agent and every person the same answer.
Automate workflows
Let agents file, route, approve within limits and update systems. Each step runs through dry run and checks first, so automation stays inside rules you can read.
Continuous learning
Overrides and near misses become proposed rule changes with evidence attached. Stewards approve, reject or adjust. The rule set improves without drifting unnoticed.
Audit and assurance
Show who or what asked, which rules fired, who approved and what changed. Ask what the policy said on a given date and get an answer.
Where it fits
| If you have | The harness adds |
|---|---|
| Agents calling tools directly | A gate with checks, approvals and a record between the agent and the tool |
| Policies in documents | The same policies as versioned data an engine can enforce |
| Workflow or BPM tools | Agent-aware rules and a shared role model. It can sit alongside them, and the overlap is real. |
| Data catalog or governance tooling | Enforcement at action time, not only description of the data |
Put a boundary around what your agents can do
We are onboarding a small group of early access teams. Tell us what you want to ground, automate or audit.
Request early access