40% Faster Trading: Building a Stable AI Platform for 100k+ Investors
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Client name
AI Software Company
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Industry
Fintech
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Location
US
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Size
50 employees
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Duration
from 2024 – present
An innovative US-based company specializing in developing AI and blockchain-based solutions for the financial sector. Their technologies are already used by over 50,000 users and 12 institutional clients in the asset management sector.
Challenges
When the client approached us, they had two core products:
For individual investors: a web and mobile platform where users receive personalized investment recommendations through real-time AI-driven market analytics.
For businesses: a tool for automating financial processes that integrates AI into document management and customer data handling.
The client aimed to build a real-time cryptocurrency and stock trading platform, providing advanced analytics of real-time market data.
Their core challenges stemmed from:
Real-Time Data Processing Limitations
Existing systems struggled to deliver fast, reliable access to live market data, causing delays in price updates and trade execution.
Unstable Transaction Infrastructure
Occasional service failures due to technical debt and lack of automated testing in critical paths.
ML Integration Complexity
Difficulty in embedding predictive analytics and AI signals into the trading platform without compromising performance. Models often failed to adjust to real-time market shifts.
Scalability Gaps
The legacy architecture could not respond to the increasing operational load.
Security Vulnerabilities
Weak user authentication and unencrypted transaction workflows exposed risks for data breaches and unauthorized trades.
API Management Overload
Integration of multiple financial APIs created conflicts in data formats, authentication protocols, and rate limits.
Need for Custom Visualization
Traders used complex charts with specific design requirements. Existing libraries lacked customization, so we had to build proprietary rendering components.
Multi-Format Response Streaming
The client needed to interpret real-time AI-generated data in dynamically-changing formats (texts, diagrams, and data tables), also ensuring stable mobile app performance.
Solution
We developed two mobile applications and a web platform in close collaboration with the client’s technical team:
Mobile app for individual investors
Provides personalized investment recommendations, real-time trading capabilities, AI-powered chat support, and portfolio analytics.
Mobile app for business clients
Focuses on automating financial workflows, AI-driven document processing, and client data management.
Web platform
Serves as a unified interface for all types of users.
Backend Development & Architecture Ownership
We led the design and implementation of core backend services, laying the foundation for a scalable architecture. Our team developed business logic for key APIs using FastAPI.
Microservices Infrastructure
To meet performance and scaling requirements, we implemented a microservices-based architecture. Services communicated asynchronously via AWS SQS. Serverless components powered by AWS Lambda handled specific event-based logic.
Contextual AI Assistant Integration
It was key to enable instant access to an AI helper from any screen without disrupting user experience. That is why we developed a global state management system to handle task interruptions (e.g., pausing chart analysis).
Caching & Performance Optimization
For rapid response and reduced backend load, we integrated Redis as a high-speed caching layer. This significantly improved performance for frequently accessed endpoints.
Machine Learning Integration
Together with the Anadea’s DL team, we incorporated predictive models into the core platform. All accessible via our backend services, they were powered by agentic AI recommendations, price movement predictions, and a conversational AI chat interface.
Feature Delivery
Our work enabled key user-facing features such as:
- Real-time price tracking
- Asset trading (buy/sell)
- Detailed trade analytics
- Integrated notification system (email and push)
- Robust account and security management, including two-factor authentication.
External Systems & API Integrations
We ensured seamless communication with third-party financial APIs like Alpaca, and leveraged various ML pipelines for prediction and recommendation engines.
AI Chat Integration
Implemented an AI assistant accessible from any screen. It analyzes financial queries (“Buy this stock?”, “Portfolio review”) and delivers responses in user-friendly formats: charts, tables, or text recommendations.
Chat Performance Optimization
Enabled instant rendering of AI responses. Complex outputs (charts/images) can be rendered seamlessly within the chat for real-time analysis.
Custom Data Visualization
Built intuitive data visualization tools, overcoming standard library limitations. Developed chart formats preferred by traders that also display mission-critical data.
Ready to Build the Future of AI-Driven Finance?
Services
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Backend Development
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Frontend development
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Mobile app development
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Solution architecture for chat service
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ML integrations
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Support and maintenance
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UX/UI design
Dedicated Team
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3
Backend developers
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2
Frontend developers
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1
ML engineer
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1
DevOps engineer
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2
UX/UI designers
Tech Stack
Python
React Native
FastAPI
MySQL
Redis
PostgreSQL
AWS
SQS
Lambda
CloudWatch
EC2
Claude
OpenAI LLM
Firebase
Python
React Native
FastAPI
MySQL
Redis
PostgreSQL
AWS
SQS
Lambda
CloudWatch
EC2
Claude
OpenAI LLM
Firebase
Business Value
The AI-powered trading platform was built in line with our client’s vision—making goal-oriented investing accessible to individuals and businesses, while overcoming infrastructure and scalability challenges.
Here’s how it transformed their operations:
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Real-Time Market Reactions
The client can now track prices in real-time and perform trading faster having optimized backend and Redis caching.
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Zero Downtime Under Load
Resilient microservices infrastructure ensures seamless trading during peak market hours.
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Smarter Investment Decisions
Integrated ML models deliver predictive signals and personalized recommendations.
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Stronger User Trust
End-to-end security with 2FA and JWT authentication builds user trust and confidence.
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Faster Product Iteration
Modular backend and clear API structure sped up development and experimentation.
Contact us
Let's explore how our expertise can help you achieve your goals! Drop us a line, and we'll get back to you shortly.
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