“The best agentic solution in the world is only as good as the interface that lets a human see what it did. Triage and Analysis agents can process a claim in seconds — but if nobody can see the reasoning, catch a miss, and correct it, you haven’t shipped AI. You’ve shipped a black box with better marketing.”

Bill Faley, Data & AI Consultant · Evolution Analytics

As we think about agentic AI solutions, the specifics may vary but the general pattern remains the same: intake information, evaluate potential next steps, and settle upon a course of action. With this paradigm, the conversation eventually runs into the same question from the business side: “what happens when it’s wrong?” A Triage agent can read an intake description and assign a category in seconds. An Analysis agent might summarize a timeline, flag risks, and recommend next steps just as fast. None of that matters if the team that owns the queue can’t see how the agent got there — or has no way to correct it when it doesn’t.

That’s the piece of WIRE we wanted to be sure incorporated the human element. It didn’t have to be glamorous, but it did have to be efficient. What has been developed is a Streamlit in Snowflake (SiS) reviewer interface that sits directly on top of the Triage and Analysis output. It isn’t a dashboard bolted on after the fact. It’s the surface where a claims analyst and three Cortex-powered agents — Triage, Analysis, and a Notes Summary agent that folds the analyst’s own feedback back into the record — work the same queue, together.

Figure 1: Without a review surface, a wrong triage call ships quietly — and the fix, if it happens at all, leaves no trace.

A simulated walkthrough of the Reviewer: opening the flagged claim, seeing the Triage and Analysis output in context, and overriding the call.

How it works

The Reviewer app runs against WIRE’s own Snowpark session — no separate host, no connection string, no additional auth system to configure. The work-item list queries a view directly, sorts by triage category and priority, and flags anything the Triage agent marked urgent. Opening a work item pulls the Triage agent’s category, confidence, and reasoning alongside the Analysis agent’s summary, risk callouts, and recommended actions. A milestone timeline shows how the item has moved — opened, assigned, vendor arrived, estimate received, resolved — so a reviewer isn’t just seeing the agent’s opinion, they’re seeing it in context.

-- Reviewer overrides the agent's category, with a reason
CALL main.override_triage(
  'claims', 'CLM-2044',
  'PRIORITY CLAIM', 'HIGH',
  'Vendor confirmed total loss on reinspection.');

Lessons learned

A fair question is why this needed a custom app at all — why not let reviewers query the output tables in Snowsight, or override a category with a plain UPDATE statement? We considered it; it’s how the earliest prototypes worked. It’s also how you lose the thing that makes human review worth doing: a trail. WIRE’s “Override Triage” procedure writes the human reviewer’s category, confidence, and reason into columns that sit next to the agent’s own, so the detail view can show both side by side — nobody must guess which value is “real.” The bigger payoff came from closing the loop in the other direction. Every message a reviewer types into a work item’s chat — a question, a correction, context the agent didn’t have — is saved as feedback against that item. Before the Analysis step re-runs, a Notes Summary agent folds that feedback back in, so a reviewer’s judgment call today actually changes tomorrow’s summary, instead of sitting in a transcript nobody rereads.

For a claims team, this is the difference between “the AI decided” and “we decided, with the AI’s help”. This distinction is often the difference that gets a pilot signed off by legal and approved for production. For a Snowflake architect, the benefit is how little in the way of new infrastructure they have to worry about. The review surface, the override trail, and the feedback loop all run on objects the Native App (WIRE) already owns. In addition, it is governed by the same roles that protect the data underneath it. In short, we feel that the WIRE, with its Reviewer interface, is the perfect encapsulation of our stance on agentic AI solutions: a vehicle to accelerate and improve business workflows while still allowing users to control the outcomes from the driver’s seat.

The reviewer’s decision doesn’t just get logged — it becomes part of what the next agent run reads.

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