Problem

Moby Analytics addresses the labor-intensive, repetitive work embedded in external financial audits. Auditors spend substantial time collecting evidence, matching documents to transactions, extracting figures, performing checks, and documenting workpapers—work that Moby characterizes as manual and that can take days for detailed testing. Economically, the pain is the cost and limited scalability of skilled audit labor: repetitive processing consumes hours that auditors could otherwise devote to exceptions, judgment, and client advice.

The clearest use case is automating Tests of Details. An audit team can provide supporting documents, contracts, and a sample file, then have Moby match evidence to transactions, extract and analyze the data, and produce grounded proof for each value. The platform also targets general-ledger analysis and financial-statement tie-outs, with the goal of turning document-heavy procedures into reviewable work completed in minutes rather than days.

Product / Service

Moby is an AI-powered Excel add-in, so auditors continue working in the spreadsheet environment where audit evidence and sign-off already live. Its AI agents can be created and deployed without code, using prompts and audit expertise; the agents sort, match, and analyze documents, link figures back to their sources, and return clean, documented Excel workpapers that follow the firm’s methodology. Moby also emphasizes secure implementation through team training and workflow adoption.

The delivery model is a per-user subscription with an Essential plan priced at €29 per user per month and a custom enterprise plan from 50 licenses, with additional capacity and enterprise controls available. In practice, auditors upload evidence and files, run a test or analysis, and review the resulting workbook. The benefit is faster preparation with a visible audit trail: Moby reports support for up to 200 documents or 4,000 pages in minutes, general-ledger analysis in about three minutes, and figure-level links for statement tie-outs.

Market

Moby competes in AI-enabled audit automation and financial-audit analytics, particularly tools that operate inside existing spreadsheet workflows. DataSnipper is the clearest named direct competitor: Moby explicitly positions itself as a DataSnipper alternative while emphasizing AI-assisted extraction, document matching, and financial-statement tie-outs in Excel. The broader competitive set includes audit-management and analytics platforms, but Moby’s differentiation is its no-code, auditor-configurable agents and its focus on producing documented Excel workpapers rather than requiring a separate workflow environment.

The company appears to be an early commercial-stage startup rather than a scaled incumbent. It is listed by Y Combinator as an active Spring 2025 company, its product is available through Microsoft AppSource, and its website publishes paid plans and enterprise sales. Company data also lists a $500,000 pre-seed round dated February 2025 with Y Combinator as investor. No public revenue figure or customer count was confirmed in the available evidence, so the strongest traction signals are product availability, active YC backing, and a defined monetization model—not publicly demonstrated revenue scale.