What we build
Decisions, engineered — not guessed.
Four kinds of decision work we build for you — each grounded in your logic and data, and each reviewable by a person where it matters.
Agentic workflows
Multi-step AI that reasons, calls your tools and APIs, and works a task to completion — not a single prompt, but a system that plans and acts.
- Plan → act → check loops
- Tool & API calling
- Grounded in your data (RAG)
Routing & triage
Classify what comes in and send it the right way — by topic, priority, risk, or intent — so the right work reaches the right place automatically.
- Intent & topic classification
- Priority & risk scoring
- Auto-assignment & escalation
Rules & policy logic
Decisions grounded in your actual policies, not a black box. We encode the logic so outputs are consistent, explainable, and easy to change.
- Your rules, made executable
- Consistent, explainable calls
- Editable without a rebuild
Human-in-the-loop gates
A person approves or overrides before anything irreversible happens. The safeguard that makes an AI decision something you can stand behind.
- Approve / override steps
- Full reasoning trail
- Confidence-based routing
Why you can trust it
An automated decision you can stand behind.
Automating a decision only helps if you can trust the output. Four properties we build into every decision system — the same ones that let institutes publish ScribeAI results to their students.
Grounded
Every decision is made against your real data and rules — retrieved and cited — so answers are relevant to your world, not generic.
Auditable
Each call carries its reasoning trail: what was seen, why it decided, what it did. Nothing happens in a black box.
Human-overseen
A person holds the final say wherever the stakes are real. AI proposes; your team approves. By design, not as an afterthought.
Adaptive
The system improves as it runs — corrections feed back, edge cases get handled, and behavior tightens over time.