How Rogo Serves 35,000 Finance Professionals with Claude-Powered AI Workflows

Rogo is built on the premise that applying AI to finance is fundamentally different from applying it anywhere else. Finance demands bespoke tools where the gap between "looks right" and "is right" is enormous—a gap that depends on context, specialty, firm, industry, team, and even individual senior preferences. "General models may understand standard financial line items from a 10-K, but they often miss nuances like which ratios matter most, which peers are appropriate, or how information should be presented," said Strib Walker, Head of Product at Rogo.

Rogo serves this market at scale—35,000+ financial professionals generating 50,000+ queries per day. The platform goes beyond point capabilities: it helps institutions operationalize AI inside their firms. The centerpiece is Felix, Rogo's agent orchestrator for end-to-end financial workflows. Felix takes on the kinds of multi-step assignments that define the work—building decks, financial models, and complete documents with the structure, formatting, and rigor the work demands. Claude Opus 4.7 and Sonnet 4.6 are integrated across the platform, powering core research, analysis, and artifact generation; Claude is one of several frontier models Rogo routes dynamically within Felix.

Rogo chose Claude for two specific strengths. The first was long-context reasoning over the documents that define financial work—data rooms, multi-year filing sets, transcript archives, internal research libraries. The second was artifact creation. In Rogo's internal benchmarks against real financial workflows, Claude showed strong improvements in PowerPoint generation, which matters because PowerPoint and Excel are the primary formats financial work is actually consumed in. Rogo evaluates models against three criteria: measurable improvement on internal finance benchmarks, production-grade quality on artifact generation graded by former finance practitioners, and compliance with the security and privacy requirements of its institutional customer base.

The collaboration between Rogo's former bankers and investors and its AI researchers reflects the rigor required. The team works together on model evaluation, prompting, artifact pipelines, and workflow design, mapping how work is actually done on the desk onto what frontier models like Claude can do. A user working in Felix begins with raw inputs—financials, documents, a banker brief, or data room materials. Research is conducted, financial data substantiated, supporting materials built, and then the deck or model is populated. The output is structured at institutional quality, not a generic approximation. "We needed a system that could produce structured PowerPoint and Excel output at institutional quality, not a generic approximation of it," Walker said.

Rogo is extending Felix and the broader platform deeper into the full arc of a deal process, from origination through execution. "Claude's strengths in long-context reasoning and artifact generation are a part of what makes that possible," Walker said, "and we expect the workflows we take on to get longer and more complex."