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Personalized Financial Categorization with AI-Powered SaaS on AWS

Traditional financial management tools struggle to personalize categorization at scale, often locking users into rigid category structures. NeenOpal, leveraging AWS and OpenAI, built a FinTech SaaS platform that integrates seamlessly with services like Plaid, Stripe, and Bill.com to automate income and expense categorization. By using lightweight LLMs, we enabled user-defined financial categories with real-time AI-powered classification, creating a personalized, scalable, and cost-efficient solution.

Personalized Financial Categorization with AI-Powered SaaS on AWS
98%KPI Arrow
Accuracy in Transaction Categorization
80%KPI Arrow
Faster Deployment of Custom Categories
10+KPI Arrow
Data Integrations with Leading FinTech APIs
50%KPI Arrow
Reduction in Manual Categorization Effort

Customer Challenges

Despite leveraging multiple FinTech tools, businesses faced persistent obstacles in achieving accurate and personalized financial categorization. Traditional approaches lacked flexibility, were costly to maintain, and failed to unify fragmented financial data.

Manual and Rigid Categorization

Manual and Rigid Categorization

Predefined static categories failed to capture diverse user needs across geographies.

No Personalization Across Users

No Personalization Across Users

Users couldn’t define their own categories, limiting flexibility in financial planning.

Expensive Model Retraining

Expensive Model Retraining

Changing categories required ML model retraining, making the process costly and time-consuming.

Data Fragmentation Across Tools

Data Fragmentation Across Tools

Financial data came from multiple APIs, Plaid, Stripe, Bill.com, etc., in inconsistent formats.

Low NLP Model Affordability

Low NLP Model Affordability

Large language models were overkill, while traditional models lacked flexibility.

Solutions

NeenOpal built an AI-powered financial SaaS platform on AWS, integrating lightweight OpenAI models to classify transactions dynamically. Users could define their own expense categories, and the system would auto-classify based on natural language descriptions from transaction metadata.

Each user submits their own categories, e.g., “Dining Out,” “Groceries,” “Treats”, which are used for real-time classification using GPT-based APIs.

01

The solution integrates Plaid, Bill.com, Stripe, and more, normalizing data across different platforms.

02

Instead of heavy ML pipelines, OpenAI’s low-cost models classify transactions contextually, cutting infrastructure and retraining costs.

03

Built using AWS Lambda, S3, API Gateway, and RDS, the solution is serverless and scales with usage, optimizing cost and performance.

04

Why choose NeenOpal?

With 85,000+ hours of cloud and AI expertise, NeenOpal is a go-to AWS Partner for SaaS innovation. Our deep FinTech understanding combined with agile ML engineering enables rapid, cost-effective product development tailored to real user needs. We enable early-stage SaaS products to scale fast with lean AI/ML strategies and robust cloud architectures.

Services Used

Plaid
Plaid
Bill.com
Bill.com
Stripe API
Stripe API
 OpenAI GPT-4-mini
OpenAI GPT-4-mini
AWS Lambda
AWS Lambda
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
Amazon API Gateway
Amazon API Gateway
 AWS CloudWatch
AWS CloudWatch
Amazon Cognito
Amazon Cognito
AWS Certificate Manager
AWS Certificate Manager
Python
Python
React
React
Django
Django

Benefits

By adopting this AI-driven approach, financial platforms gained measurable improvements in speed, flexibility, and cost-efficiency. The solution empowers SaaS teams and end users alike to reimagine transaction classification.

Conclusion

NeenOpal’s AI-enhanced FinTech SaaS, powered by AWS and OpenAI, delivers a highly customizable transaction classification engine. It transforms traditional financial tracking by empowering users to define what matters most to them. The result? Faster deployments, smarter insights, and a truly personalized financial experience, delivered at scale.

Authors

Urwah Farooqi

Data Analyst

LinkedIn

Madiha Khan

Content Writer

LinkedIn
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