Problem

Wealth-management firms spend substantial time converting messy, heterogeneous client and prospect information into usable portfolio analysis and proposals. Brokerage statements, alternative-investment files, balance sheets, tax documents, scans, faxes, screenshots, and spreadsheets often require analysts to copy data manually, reconcile errors, classify securities, and move information between disconnected systems. The economics are painful: SCS Financial says a single prospect’s 100–1,000 pages of investment data previously required two to four people, while Chicago Partners was spending 1,000–4,000 hours a year on manual entry. This delays advice, consumes expensive analyst capacity, and makes it harder for advisors to scale client acquisition and deliver a personalized experience.

The killer use case is turning a prospect’s financial-document package into a reliable, actionable proposal during the sales or onboarding process. Instead of waiting days for statements to be reviewed and holdings to be rekeyed, an advisor can quickly understand the client’s current allocation, risks, tax position, and held-away assets, then use that information to produce a tailored recommendation. The same workflow also supports ongoing client service, where faster access to accurate data improves responsiveness and frees advisors to spend more time on relationships and higher-value analysis.

Product / Service

Powder is an AI-agent platform for wealth-management document analysis, data extraction, and proposal generation. Users can drop in PDFs, images, faxes, scans, and spreadsheets; Powder’s generative-AI parser converts them into structured data, organizing portfolios by account, entity, tax status, and asset classification. It then enriches the extracted information with allocation, risk, implementation, tax, financial-planning, and other analyses, and can generate a presentation-ready proposal deck. The system is designed to replace manual copying and pasting while providing checks intended to improve accuracy.

The delivery model combines a hosted workflow with data export and API integration. Firms can download or port extracted data into their existing systems, or embed Powder natively through endpoints for file upload, processing status, webhooks, and extracted data. Powder offers per-user subscription tiers, including document parsing and prospect insights in lower tiers, deeper portfolio and tax analysis in professional plans, and enterprise options such as custom integrations, account management, retention policies, and service-level agreements. The benefit is measurable operational leverage: customer case studies report roughly 95% reductions in manual data entry, turnaround times reduced from days to minutes, and substantially more prospect capacity.

Market

Powder competes in fintech and investment technology, specifically the emerging category of AI-powered wealth-management workflow automation and financial-document intelligence. It sits between document-processing infrastructure and advisor-facing proposal, portfolio-analysis, and client-service software. Its adjacent competitive set includes proposal-building tools such as Zephyr and broader financial-data and analytics platforms such as YCharts, FactSet, Bloomberg, and Yahoo Finance; the available evidence identifies those platforms in the context of Koyfin’s comparable market rather than presenting a formal list of Powder’s direct competitors. Powder’s differentiation is the combination of unstructured-document parsing, wealth-specific analysis, proposal generation, and API-based integration into an advisor’s existing stack.

The company is clearly beyond the pre-launch stage. Powder was founded in 2023, launched its product, raised a $5 million seed round in July 2024 from investors including Y Combinator, General Catalyst, Funder’s Club, and Elefund, and reported a growing list of wealth-management clients including Catalytic Wealth, EPIQ Capital, and IEQ Capital. Its later published case studies cite SCS Financial, with $42 billion in assets under management and more than 2,000 prospect-document packages per year, Chicago Partners, with $6.5 billion in AUM and reported 25% client growth, and Koyfin, where Powder’s API reduced document-processing turnaround by 98% and supported a projected 10,000 documents annually. The evidence demonstrates commercial adoption and customer outcomes, but it does not disclose revenue, so revenue scale and profitability cannot be determined.