Capture
Receive an item from an approved channel, assign a durable identifier, preserve the original content, and detect duplicates before processing.
A reusable pattern, not a claimed client case study.
System pattern 01
Intake, triage, and routing agent system.
A reference architecture for AI assisted intake, classification, information checks, routing, drafting, and human escalation.
Operating context
The problem this pattern is built to handle.
Many operational queues begin the same way: a request arrives in free text, the sender omits important details, and somebody must understand it before the real work can start. The queue may be support tickets, vendor requests, applications, incidents, sales inquiries, or internal service requests.
An intake agent can prepare that work without being allowed to decide everything. It can extract structured fields, classify the request, ask for missing information, retrieve the right policy, recommend a route, and draft a response. Rules and human approval remain around the cases where classification or consequence demands it.
This page is a reference architecture.
It does not claim a named or anonymous client result. A real implementation begins with representative work, verified integrations, and an agreed evaluation set.
System flow
Four stages, one accountable path.
Model interpretation sits inside a durable workflow. Each stage has a known input, output, and failure route.
Interpret
Extract fields, classify intent and urgency, identify missing information, and attach supporting evidence from permitted sources.
Decide
Apply deterministic rules and policy checks to the structured result. Route uncertain, sensitive, or high impact cases to review.
Act
Create or update the target record, prepare a response, notify the owner, and write a trace that explains what happened.
Control layers
Autonomy is bounded by design.
Controls are matched to the action and its consequence. A prompt instruction is not a substitute for software enforcement.
Typed outputs
The interpretation step returns a validated schema instead of prose, so downstream systems receive known fields and values.
Evidence attached
Recommendations include the policy, source, or request detail that supports them. Reviewers do not need to reconstruct the context.
Bounded authority
Automatic routing is limited to approved categories and thresholds. The agent cannot invent a destination or exceed its allowed actions.
Queue ownership
Every failed or escalated case has a named queue and priority. A fallback that nobody owns is just a hidden failure.
Measurement
Measure the operation, not the theatre.
Agent quality has to connect to the completed workflow. Model accuracy, tool success, and adoption are diagnostic measures, not the final outcome.
- Time from arrival to a correctly owned case
- Classification and routing quality by category
- Missing information detected before handoff
- Rework caused by incomplete or incorrect preparation
- Escalation rate and reviewer agreement
Suitability
Conditions for a credible first release.
- The queue receives repeated but varied requests.
- Routing rules and accountable owners can be defined.
- Representative historical cases are available for evaluation.
- The first release can prepare or recommend before taking consequential action.
If these conditions are missing, the right first move may be process design, data work, or integration cleanup instead of an agent.
FAQ
Questions about this system pattern.
Specific answers beat vague reassurance. If your question depends on the workflow, we will say so.
Can an intake agent work with email and ticketing systems?
Yes, when suitable APIs, webhooks, or controlled integrations exist. The system can receive the original item from one channel and create or update the authoritative record in another.
Does the agent reply automatically?
It can, but authority should be granted by category and consequence. A common first release drafts replies and automates only acknowledgements or other low risk, policy defined messages.
How do you evaluate routing quality?
Use labeled historical cases, category specific precision and recall, reviewer agreement, downstream reassignment, and operational rework. A high overall accuracy can hide poor performance in an important low volume category.
Start with the workflow
Bring us the process that keeps breaking.
We will map the work, identify the right automation boundary, and tell you plainly whether an agent belongs there.
Discuss the workflow