How it works
One layer between every team and every model.
Context is checked before you prompt, the right template is retrieved, the run goes to the cheapest capable model, and what worked is remembered for next time.
Check
Before a prompt is sent, M365, Drive, Notion, and Confluence are scanned. If the doc already exists, you see it instead of generating a new one.
Retrieve
The right template surfaces from your team's library, enriched with your personal style preferences and org-wide context. Variables pre-fill where possible.
Run
The task is routed through the available model path, the projected cost is shown up front, and execution guardrails are applied before the run starts.
Remember
Users choose whether a winning prompt should be saved. Approved prompts become reusable assets instead of silently entering memory.
A request, end to end
- 1
Employee types a task
"Write an onboarding SOP for new engineers."
- 2
Classifier detects context
Doc type: SOP. Department: Engineering. Complexity: standard.
- 3
MCP scans connected systems
SharePoint search returns a similar SOP from last quarter. User chooses to update or generate new.
- 4
Memory and the registry retrieve the template
The team's approved engineering-SOP template loads with variables auto-filled from the request.
- 5
Token optimizer runs the model
Context stripped, model selected, cost projected. Response streams back.
- 6
Audit and indexing
Output scanned for secrets, missing steps, stale TODOs. The user can save the prompt deliberately before execution, then admins govern what becomes shared.