How We Build Agentic AI for Business Operators

Why Operators, Not Engineers, Need to Drive AI Automation

In every major insurance carrier and financial institution, the tension is the same: the people who know the work aren’t the ones shaping how it gets automated.

Talk to a claims adjuster or loan officer, and they’ll tell you exactly how a decision should be made, what documents matter, and where the real edge cases hide. But in traditional AI deployments, these subject matter experts (SMEs) are locked out of the loop.

Automation decisions are routed through engineering teams, meaning every adjustment requires a sprint ticket, every exception becomes a blocker, and every bit of institutional knowledge sits trapped in someone's head or an outdated SOP binder.

The result?

AI that acts like a black box. Decisions get made without context. Models issue approvals or rejections without citing the policies they’re meant to reflect. And when something breaks, business users are stuck waiting for a fix they can’t make themselves.

One underwriting team at a national P&C carrier told us they were forced to submit 12 separate Jira tickets to get their AI tool to stop flagging standard reinsurance terms as anomalies. The engineers managing the tool didn’t know what "swing rate coverage" meant, let alone why it shouldn’t trigger a denial. It took three weeks to patch the issue, which is three weeks of false flags and wasted reviews.

That kind of lag isn’t just frustrating. It’s costly. It delays payouts, disrupts customer experience, and erodes trust in automation.

AgentFlow flips this dynamic entirely.

We built AgentFlow for SMEs, not as an afterthought, but as the primary operators. Here, business users configure how agents behave, define what "done" looks like, and provide direct feedback when the agent needs course correction.

If a claims manager wants to reweight confidence thresholds, they do it in the AgentFlow dashboard, not in a GitHub repo. If an underwriter sees poor classification logic, they update the schema themselves.

This isn’t self-serve as window dressing. It’s control that matches the real-world complexity of regulated decisions, designed for the people who own the outcome.

When operators drive automation, the results align with the business. Not only do workflows reflect actual policy logic, but changes happen in hours, not weeks.

Decisions get faster. Oversight gets easier. And AI becomes a tool for acceleration, not a source of friction.

How AgentFlow Is Built for SMEs

AgentFlow is not a tool that engineers hand off to the business. It’s a system designed for the people doing the work.

In the following sections, we break down the specific ways AgentFlow gives subject matter experts end-to-end control, from building workflows to improving performance.

Self-Serve Configuration Features

From the moment a subject matter expert logs in, AgentFlow feels familiar. A claims manager looking to streamline triage can use Instant to spin up a working agent in minutes, using templates tuned for common insurance workflows.

A loan officer handling complex underwriting policies might opt for Configure, which lets them shape every decision rule and escalation path to match their institution’s logic.

No one files a ticket. No one waits for engineering.

They simply drop in the documents, observe how the agent performs, and provide feedback directly on the screen. If they need to route incoming documents via email, that’s built-in. If they want an API integration for structured systems, it’s already available.

Alignment With Real Business Workflows

AgentFlow isn’t generic. It ships with agents already aligned to critical finance and insurance workflows, from FNOL intake and claims adjudication to loan origination and policy approval.

That means the logic matches the work from day one, and SMEs only need to tune the details.

In one deployment, a regional bank replaced its rule-based loan screening tool with a fully configured agentic workflow. The business team didn’t have to reinvent anything; they just adjusted the pre-built templates to fit their credit policy and started seeing results in under two weeks.

Intuitive Features For Easy Management

Business users don’t want to learn new software; they want to manage work. AgentFlow makes that simple.

Drag-and-drop uploads support all major file types. Feedback boxes appear directly in agent outputs. And for compliance teams, version control and rollback features ensure that every change is trackable.

The experience feels more like managing a document portal than an AI system, but with the power to shape automation under the hood.

SME Oversight

Oversight isn’t optional, especially in regulated environments. AgentFlow Monitor gives business teams real-time visibility into what agents are doing, how confident they are, and whether actions align with expected policies. Execution logs show the full history of every decision.

From day one, your governance team can trace how each outcome was made. Read more about our approach to human-in-the-loop automation.

SME Feedback

Every time an SME flags an issue or coaches the agent, that input is captured. Over time, this creates a continuous learning loop. Agents stop making the same mistakes. Performance improves. And trust builds.

In one insurance deployment, the team used SME feedback to reduce false positives by 70% within the first month. What began as a support tool quickly became a core teammate, trained by the very experts it was designed to assist.

How We Can Further Support SMEs

Not every organization is ready to build agentic AI workflows from scratch, and they shouldn’t have to be.

Even with intuitive tools, there’s a deeper challenge: translating decades of human intuition into repeatable logic.

The nuances of an underwriter’s decision-making or the judgment a senior claims handler applies to edge cases aren’t always written down. They live in conversations, judgment calls, and post-it notes stuck to monitors. And when those people retire or move on, that operational knowledge walks out the door.

That’s why we don’t just ship software, we embed alongside your teams.

Our full-service deployment model mirrors the Palantir-style field approach. We work directly with frontline SMEs, sitting in on adjudication calls, dissecting loan packages, and walking through exception queues.

We ask the questions only a seasoned practitioner would know to ask: What triggers escalation? What do you look for in the footnotes of a reinsurance treaty? What counts as a red flag on page 3 of a borrower’s tax return?

We codify those answers into agent logic. We transform back-of-the-envelope rules into machine-executable playbooks that align with your existing SOPs and regulatory constraints.

At one regional bank, our team spent three weeks shadowing their underwriting leads. By the end, we had built a full-stack agentic system that automated pre-approval checks, prioritized exceptions, and routed only the true edge cases to human review. It didn't just reduce cycle times, it preserved the underwriting DNA that made their credit decisions so reliable in the first place.

This is more than a service, it’s a safeguard. A way to ensure that institutional expertise doesn’t get buried in SharePoint folders or lost to turnover. With our help, your SMEs don’t just supervise automation. They shape it and leave behind a legacy that scales.

Start Shipping High-Value Agentic Work

If you're a leader in finance or insurance, ask yourself: Do your business operators have real control over your automation initiatives?

With AgentFlow, they can.

Book a demo to see AgentFlow live in action and learn how it can help you automate your business operations.