In Practice

The challenge

A 45-person structural engineering firm was carrying a backlog problem it couldn't hire its way out of. Project initiation — the stage between winning a contract and billable work beginning — consumed two to three weeks of senior staff time per project: chasing client documents, reformatting submissions for internal templates, manually populating QA checklists. The firm had looked at generic AI tools but found nothing that addressed its specific document types or fit its existing project management system.

The approach

The Assessment identified project initiation as the single highest-leverage point: it was consuming approximately 18% of senior staff capacity without producing billable output. Galeo modeled the impact of automating document intake, classification, and template population against the firm's average project volume and billing rates. The Benchmark Project would implement an intake automation system integrated directly into the firm's existing project management platform — not a standalone tool. The system would classify incoming client documents, flag missing items, and populate internal project initiation templates automatically. Once a benchmark validates the reduction in non-billable initiation hours, the Rollout extends the same discipline to QA documentation and project close-out reporting.

The result

Modeled outcome: the firm could recover approximately 14 hours of senior engineer time per project. At a volume of 30–35 project initiations per year, that's roughly 420–490 hours annually — the equivalent of a quarter-time senior hire, capacity a firm could choose to reinvest in growth rather than headcount.

The challenge

A regional insurance brokerage with 28 producers ran its client renewal process entirely manually: each renewal required a producer to pull loss run reports, compare prior-year coverage, update submission templates, and coordinate with multiple carrier contacts. The process took four to six hours per renewal. At over 400 renewals annually, this was consuming producer time that should have gone toward new business development and client relationships.

The approach

The Assessment surfaces renewals as the dominant time sink — and identifies a pattern that makes automation tractable: the process is highly repetitive, document-heavy, and dependent on data that already exists in the brokerage's AMS. Galeo would build the Benchmark Project around a single carrier relationship (the highest-volume carrier) and automate the full submission workflow: loss run extraction from the AMS, coverage comparison against prior year, template population, and submission packaging — integrated directly into the existing AMS so producers work from the same interface.

The result

Modeled outcome: for the carrier in scope, average renewal handling time could drop from 4.5 hours to under 45 minutes. A documented ROI case like this is typically strong enough to justify extending the approach across a full carrier panel within existing operating budget.

The challenge

A specialty insurance MGA writing admitted and non-admitted lines saw its underwriting triage process become a bottleneck as submission volume grew. Triage — the stage between submission receipt and underwriter assignment — was performed manually by two senior underwriters, consuming roughly 30% of their week reviewing submissions they would ultimately decline or redirect without writing. New business was being delayed, and the senior underwriters wanted to spend their time underwriting.

The approach

The Assessment finds that 70–75% of declined submissions share a small set of identifiable characteristics — coverage type, geography, loss history patterns — that appear in the submission documents before an underwriter ever opens the file. Galeo modeled the impact of automating first-pass triage against current submission volume and decline rate. The Benchmark would implement a triage system that classifies incoming submissions against appetite criteria and routes them accordingly: likely writes to the appropriate underwriter, likely declines flagged for a 60-second review, and edge cases escalated for full review. Critically, the system produces an explanation for each classification decision, visible to underwriters, so they can override with confidence and the system can be corrected over time. A Managed Operations Partnership would follow the Rollout to handle monthly reporting, system calibration as appetite criteria evolve, and quarterly roadmap reviews.

The result

Modeled outcome: senior underwriters could recover approximately 28% of prior triage time within the first quarter. Submission-to-assignment speed would improve, and the explainability layer means underwriters can trust the system rather than route around it.