Governed AI case-to-outcome platform

Evidence in. Approved outcome out.

Your systems already hold the records. What none of them owns is the case that crosses them — who decided, on what evidence, with what authority, and whether it actually closed. TeamIntel is the layer that owns that, on top of the stack you have.

The case flow

Six steps. Two of them are gates, and neither gets skipped.

Not by you, and not by us. The gates are the point: an analysis that has to survive contradiction, and a decision made by a person you can name.

STEP 01

Evidence & Provenance

Facts, documents and system records are ingested with their source, date and confidence attached — and a conflict between two sources stays visible as a conflict.

STEP 02

Case Engine

One business outcome becomes a case with an owner, a deadline and a state. It stays open across every system involved until it closes.

STEP 03

Rules & Specialist Agents

Deterministic checks settle arithmetic and policy. Specialist agents take the ambiguity, and disagree in the open where the evidence does not settle it.

GATE 1
STEP 04

Authority & Approvals

A named person, role and threshold govern the decision. The approval is recorded with its rationale. Nothing material runs without this step.

GATE 2
STEP 05

Controlled Actions

Drafts, tasks and writes execute only inside approved boundaries, in your systems, against an action log that records what ran and on whose authority.

logged · signed
STEP 06

Outcome Memory

The result — accepted, corrected or rejected — updates confidence, rules and what the case is allowed to do unattended next time.

01 Evidence & Provenance

Facts, documents and system records arrive with source, date and confidence attached. Where two systems disagree, the conflict stays visible as a conflict.

Leaves behind: Evidence bundle, per-fact source links

Evidence, not assertion

02 Case Engine

One business outcome becomes a case with an owner, a deadline and a state. It stays open across every system involved until it closes.

Leaves behind: Case state, owner, deadline, priority

Case, not chat

03 Rules & Specialist Agents

Deterministic checks settle arithmetic and policy, where a language model is the wrong instrument. Specialist analysis takes the ambiguity, and disagreements stay visible rather than averaged away.

Leaves behind: Rule output, finding, stated confidence

Rules and agents do different jobs

04 Authority & Approvals — GATE

A named person, role and threshold govern the decision, under your signing authority. The approval is recorded with the reasoning that produced it.

Leaves behind: Approval record with rationale

“The system decided” is not an answer

05 Controlled Actions

Drafts, tasks and writes execute inside approved boundaries and nowhere else, in your systems.

Leaves behind: Action log with execution evidence

Draft freely, execute narrowly

06 Outcome Memory

Accepted, corrected or rejected — the result updates confidence, rules and how much the pattern may do unattended next time.

Leaves behind: Outcome record and correction history

Autonomy is earned per pattern, and revocable

Operations View

Leaders see cases, not agent activity.

Ready, at risk, blocked, closed — with the owner and the deadline against each. A dashboard of model calls tells you the machine is busy. It does not tell you whether the work is moving, and that is the only question this view answers.

Leaves behind: Portfolio queue and the business measures behind it

Where this gets real

Bring one recurring case that crosses three systems.

Platform — evidence, cases, authority, action and outcome memory · TeamIntel