Step / 01
Context from the twin
Your agents read the business context Signal holds: the P&L, the open decisions and their owners. Today this is a read-only feed.
Solution · Early access · Bring your own agents
Your agents, held to the same standard as ours.
Many companies already run agents for pricing, planning or reporting, and few can say what those agents changed in the P&L. Signal gives them the business context they lack. With our team, their recommendations go through the same review, approval and measurement as any other decision.
Step / 02
The same approval path
What an agent recommends enters as a draft decision and goes through the same review and independent approval as any other.
Step / 03
The same measurement
Each agent decision is registered with a control group before it starts, so its effect on the P&L is read back the same way.
Step / 04
One log for people and agents
Agent decisions and human decisions sit in the same log, so you can see which ones paid back.
Status
What is ready and what we are building.
CapabilityWhat it doesStatus
Context feed
Read-only access to the twin's business context for your agents.
Available
Recommendations as drafts
Agent output enters the decision lifecycle for review and approval.
With our team, inside an engagement
Measured agent decisions
Pre-registered control groups and readback for agent-driven decisions.
With our team, inside an engagement
Self-serve connectors
Connect an agent without our team in the loop.
In development
We do not say an agent moved the P&L until its decision has been read back against a control group.
Your agents in. Results in the P&L out.
It reads
- 01Your agents' recommendationsPricing, planning, reporting
- 02The decisions they touchAnd the P&L lines behind them
- 03Who approvesRoles and independence rules
- 04The control groupFixed before the start
It returns
- 01Business contextFrom the twin, for your agents
- 02Reviewed, owned decisionsWith due dates
- 03A measured effectWith its interval
- 04One logAgents and people side by side
Bring your
agents
A Value Tree shows which of your agents sit on decisions worth measuring.