Back to blog
Improved an AI Financial Intelligence Platform
Dallas, TX
Project Overview
Strategy & Advisory
AI Products & Platforms
Commercialization & Growth
AI Infrastructure
Data Mantis set out to build an AI-powered financial intelligence platform for CPAs and e-commerce operators that could unify fragmented data from Shopify and QuickBooks into a single, actionable source of truth. Existing accounting and analytics tools required manual reporting, complex reconciliation, and extensive interpretation, limiting the speed and quality of financial decision-making.
SFAI Labs partnered with the founding team to design a value-driven AI product strategy that aligned technical architecture, compliance requirements, and commercial positioning. Through rapid discovery and validation cycles, we identified high-impact use cases centered on KPI reporting, reconciliation, and strategic financial advisory.
Within eight weeks, SFAI Labs delivered a scalable AI platform blueprint integrating automated data ingestion, KPI generation, vectorized knowledge retrieval, and multi-model orchestration. The system enabled CPAs and business owners to query financial performance, assess risk, and generate strategic insights in real time.
The solution positioned Data Mantis to accelerate product development, onboard early customers, and establish itself as a category leader in AI-powered financial intelligence for e-commerce businesses.
Key Takeaways
Product Clarity accelerates execution
Decision Intelligence improves CPA workflows
Fast Validation reduces platform risk
Scalable Systems enable expansion
Commercial Focus strengthens positioning
Challenge
Data Mantis needed to unify heterogeneous commerce and accounting data across Shopify and QuickBooks while maintaining regulatory and compliance constraints. CPA workflows required full traceability from sales to bookkeeping, reliable reconciliation across payouts and deposits, and rapid responses to high-stakes financial questions without excessive token cost or latency.
Strategy
SFAI Labs defined a product strategy centered on CPA workflow priority, standardized KPI representations, and a scalable retrieval architecture. We mapped core use cases (reconciliation, profitability, sales tax audit, unpaid invoice matching, payout reconciliation) and designed an approach that maximizes KPI retrieval first, then selectively retrieves raw data only when computations are required.
Solution
SFAI Labs designed an AI system blueprint that converts raw Shopify and QuickBooks exports into structured tables and normalized KPI reports, then applies context retrieval to support natural-language financial Q&A. The architecture supports multi-tenant scaling, caching of report tables for latency, and a pathway for model switching without rebuilding the full prompt and retrieval stack.
Execution
Week 1: Market Research and Use Case Design
Week 2–3: Platform Architecture and data model design
Week 4–5: Context Retrieval design and query routing strategy
Week 6–7: Integration strategy and scalability planning
Week 8: Commercial Blueprint and launch readiness planning
Results
Faster CPA insight delivery
Reduced manual reconciliation
Improved reporting consistency
Business Value
The engagement enabled Data Mantis AI to reduce CPA time spent on non-value-add reporting and reconciliation while improving the quality and speed of client-ready insights. The resulting foundation supports faster onboarding, repeatable workflows, and future expansion into additional financial and operational data sources.
Why SFAI Labs
SFAI Labs combined AI Product Strategy with platform architecture and commercialization planning to create a scalable, defensible product direction. Our lab model prioritized high-impact CPA workflows, validated technical feasibility for latency and scalability, and aligned product execution to market positioning and growth.
