Case Study
AI Fintech Company Delivers Real-Time Trading Insights with AWS Generative AI
Solutions
Industries
About the Customer
The AI Fintech Company provides a SaaS auto-trading platform for everyday investors. It’s designed to help trading communities scale easily with hands-free financial intelligence. By delivering real-time, AI-driven insights across global exchanges, our customer empowers traders to act faster, stay compliant, and grow smarter without operational complexity.
Challenge
Our Customer’s Key Business Objectives
The AI Fintech Company aimed to enhance its analytics capabilities and platform performance by focusing on:
Delivering real-time trading insights with minimal latency from multiple financial sources.
Automating analyst-driven narratives and regulatory reporting to reduce manual workloads.
Building a compliant, scalable infrastructure that processes 10,000+ transactions per second.
Key Amazon Web Services Used
Amazon Bedrock
Amazon Elastic Container Service (ECS)
Amazon Kinesis Data Streams
Amazon Timestream
Amazon Athena
AWS Glue
Amazon Simple Storage Service (S3)
AWS Lambda
Amazon CloudWatch
AWS Identity and Access Management (IAM)
AWS Secrets Manager
Amazon EventBridge
Solution
How Cloudelligent Solved the AI Fintech Company’s Challenges
Cloudelligent implemented an AWS-native Generative AI architecture to help our customer deliver real-time, AI-powered financial intelligence at scale.
1
Real-Time Data Ingestion and AI-Powered Processing
To support fast-paced financial decisions, Cloudelligent built a real-time ingestion pipeline using Amazon Elastic Container Service (Amazon ECS) and Amazon Kinesis. The AI Fintech Company processes over 10,000 TPS, pulling data from sources such as Polygon and EDGAR. Amazon Timestream stores this time-series data for instant querying. This data streams in real time using Amazon Kinesis Data Streams, processes with AWS Lambda, and is stored in Amazon Timestream for instant access and time-series analysis.
2
AI-Powered Natural Language Querying
Cloudelligent enabled the AI Fintech Company’s users to ask natural language questions via a web-based interface. These requests are routed through AWS Application Load Balancer to a backend running on Amazon Elastic Container Service (Amazon ECS). Queries are then passed to AWS Lambda, which sends them to Amazon Bedrock. Using foundation models, Amazon Bedrock translates the natural language into optimized SQL queries. Depending on the data needed, the system queries either Amazon Timestream for real-time data or Amazon Athena for historical data stored in Amazon Simple Storage Service (Amazon S3). The AI solution then generates clear, human-readable insights for end users.
3
Historical Data Enrichment and Contextual Insights
To enhance the system with historical insights, Cloudelligent used AWS Glue to pull financial filings from sources such as SEC-API/EDGAR. The data is cleaned, enriched, and transformed through batch processing. Final datasets are stored in Amazon Simple Storage Service (Amazon S3), while metadata is organized using the AWS Glue Data Catalog for improved discoverability and data management.
4
Security, Compliance, and Observability
Security and observability are central to the solution. AWS IAM enforces role-based access, while AWS Secrets Manager secures and rotates credentials. Amazon CloudWatch tracks latency, ingestion, and model performance, ensuring 99.99% uptime. The architecture is built to support compliance with SEC Rule 17a-4 and MiFID II, giving our customer full visibility and control as it scales from its current 10,000 TPS to support up to 1 million TPS.
Results & Benefits
Transforming how trading intelligence is delivered.
Cloudelligent’s AWS-powered solutions enabled our customer to deliver real-time insights, reduce operational costs, and scale securely across global markets. Key outcomes include:
Accelerated Trade Insight Delivery
Cloudelligent helped the AI Fintech Company reduce trade insight latency from 15 minutes to under 2 minutes, enabling faster, more responsive decision-making within their trading intelligence platform. The system now processes over 10,000 transactions per second with the flexibility to scale further, supporting high-frequency trading demands and dynamic market conditions seamlessly across global regions.
Enhanced Compliance and Intelligent Insight Delivery
Leveraging AWS-native services such as Amazon Bedrock and Amazon IAM, our customer strengthened its compliance with regulations such as SEC Rule 17a-4 and MiFID II. The platform securely manages data access, ensures governance, and generates AI-driven financial narratives, improving insight accuracy while meeting rigorous regulatory standards.
Cost Optimization and Operational Efficiency
The modernization initiative decreased cloud infrastructure costs by 35 – 50% by optimizing infrastructure and automating workloads. Cloudelligent’s solution also freed up over 2,000 analyst hours annually, accelerated platform release cycles from 2 to 6 updates per year, and eliminated system outages. This resulted in boosted agility, resilience, and client satisfaction.
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