Dolmen

An Agentic Expense Review Workspace for Complex Administrative Work

We created an agentic workspace that helps administrative teams handle complex, multi-step workflows such as expense review and internal approvals with greater clarity, speed and consistency. Built for document-heavy processes and fragmented information systems, it uses agent support to guide work, surface risks and reduce cognitive load, while increasing throughput, shortening processing times and improving decision quality.

A Guided Workflow for Expense Decisions

The expense workflow pictured above is defined step by step: read the policy, review the claim, match receipts to each line, decide eligibility, then produce an approval table. Each step is implemented as an agent action, so the agent interprets rules, structures the data and proposes decisions, while reviewers step in where judgement is needed. This creates a transparent, repeatable path from “new claim” to “approved, adjusted or rejected”, with the agent doing the heavy lifting.

Built to Support Upskilling Inside the Workflow

The workspace connects to the organisation’s LMS, allowing users to deepen their skills at the moment they need them. When the agent detects an unfamiliar policy rule or edge case, it links to short, targeted learning modules rather than interrupting the workflow. Staff can review a quick lesson, return to the claim or request and apply the new knowledge immediately, turning learning into a natural extension of daily work.

Designed for Teams Handling Sensitive, High-Stakes Work

Whether reviewing routine expense claims, processing internal requests or validating compliance documents, agentic systems take the grind out of evidence-based admin work. Expense reviewers see claims pre-grouped by policy risk, receipts and invoices matched to each line, and clear flags where amounts, categories or dates don’t add up. It gives organisations with operational depth and strict reliability requirements a way to run safer, faster approval flows: humans stay responsible for the decisions, while agents surface the right context, highlight edge cases and remove the friction.

Interested in exploring agentic workflows?
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