FinTech
Achieved 3.1x Insight Growth with an AI MVP for a FinTech Startup
89%
Faster Tasks
54%
Less Manual Efforts
41%
More Precise Forecasting
3.1x
Growth in Insights
This FinTech startup had already connected to banks and accounting platforms. What they lacked was clarity. SME owners were drowning in numbers yet starving for insight. Eventually, we became their AI MVP development partner to build a focused AI-powered MVP that translated financial noise into meaningful guidance.
Country
USA
Duration
3 Months
Industry
FinTech
Services
Idea & Validation Product Design Sprint Prototyping MVP Development AI Integration
Technologies
TensorFlow FastAPI LangChain OpenAI Models Kafka
Problem Statement
- SME founders had access to financial data but lacked clarity on what actions to take.
- Manual spreadsheets and basic accounting tools failed to provide predictive insight.
- The startup needed an AI-powered MVP that translated transactions into decision-ready intelligence
Challenges
- Financial data was scattered across banks, accounting tools, and invoicing systems.
- Traditional dashboards overwhelmed users who were not finance experts.
- Manual categorization consumed time without adding strategic value.
- AI recommendations had to be accurate, explainable, and trustworthy.
Solution
- Conducted idea & validation workshops to narrow down high-impact financial use cases.
- Ran a focused product design sprint to simplify complex financial workflows.
- Built and tested core logic through rapid prototyping before full-scale build.
- Engineered secure API integrations during MVP development to unify financial feeds.
- Implemented AI integration using LangChain and OpenAI models for real-time insights.
- Deployed scalable cloud infrastructure with event-driven recalculations for accuracy.
Result
The delivered AI-powered FinTech MVP repositioned the FinTech startup from a basic financial tool provider to a proactive financial intelligence partner.
- 89% faster month-end task completion for SMEs using the co-pilot.
- 54% reduction in manual categorization efforts across transaction workflows.
- 41% improvement in forecast accuracy, allowing businesses to anticipate liquidity gaps.
- 3.1x increase in insight engagement within the platform, measured through in-app behavioral analytics.
Delivered an AI finance co-pilot that converts transactional data into plain-language business intelligence for SME founders.
Established a scalable architecture during MVP development, ensuring smooth evolution toward full product expansion.