Finance built to predict, not just report.

Financial reporting tells you what happened last month; financial intelligence tells you what it means and what's likely to happen next. Propeller combines human judgment, benchmarked data, and AI-driven pattern recognition to turn your numbers into forward-looking guidance, catching a cash flow issue before it hits your board deck rather than explaining it after the fact.

When Propeller's team solves a cash burn or trade spend problem for one client, that solution gets refined and deployed across every similar company we work with. Your data is analyzed against patterns from hundreds of businesses at your stage, so issues that would normally surface as a surprise in next month's report often show up as an early warning instead. This is the compounding effect of scale: the more companies we serve, the sharper the foresight gets for all of them.

Client data is never shared in a way that identifies another company: aggregation happens under a governance framework built on explicit consent, role-based access, and privacy-preserving benchmarking. You get the value of comparison against hundreds of peer companies without your specific numbers ever being exposed to them, or theirs to you.

AI can automate the mechanical parts of accounting and reporting: the strategic judgment, stakeholder relationships, and cross-functional synthesis that finance actually requires can't be automated the same way. Someone still needs to own the integrated view, make the high-stakes calls, and be accountable for the recommendation, not just the output. Propeller's model pairs AI's pattern recognition with human judgment specifically so the automation is safe and the guidance is trustworthy.

A financial data lake is a continuously updated repository of financial and operational data pulled from your core systems — accounting, banking, payroll, billing — that powers benchmarking and pattern detection you couldn't get from your own numbers alone. The Propeller Data Lake reflects 18 years of client history and $4B+ in annual transaction volume, which means even an early-stage company gets benchmarking depth that would otherwise only exist at much larger, more mature organizations.

A dashboard shows you your own data; Propeller's financial intelligence shows you where you stand against hundreds of similar companies and what typically happens next. The difference is context: a metric that looks fine in isolation can signal trouble when benchmarked against peer trajectories, and catching that requires both the comparative data and a person who knows how to read it for your specific situation.

No: your ERP is your choice, and Propeller's intelligence layer works on top of whatever systems you already run. The benchmarking, forecasting, and pattern recognition aren't tied to a specific software stack; they're built from how your data behaves, not what platform it lives in.