AI support for corporate chats
#Fintech #AI #Python #AWS #Flask #Microservice
Project definition
Location
Client
Project type
Industry
Service list
API Design and Technical Specification
Back-end Development of Microservices
DevOps Infrastructure Setup (AWS, Docker, DNS)
Security System Integration (OAuth2 via OKTA)
Logging and Monitoring Configuration
Development and Execution of Unit and Integration Tests
Team size
S-Size (1–3 engineers)
Budget
$50,000 – $250,000
Task
Natural language processing features in corporate chat (translation, grammar correction, rephrasing, summarization) suffered from high latency (>600 ms) and the need for manual adjustments. This negatively impacted the convenience and speed of communication within teams.
Solution
Ftech-IT developed and implemented containerized RESTful microservices based on AWS EC2 with automatic scaling.
Impact
The new AI service revolutionized corporate communication by making cross-language collaboration instant and accurate. We slashed AI response times by over 65% - from a sluggish 600 ms to under 200 ms - enabling real-time translation and editing in chat. With grammar and translation accuracy now exceeding 90%, employees saw a 40% drop in manual corrections, leading to smoother teamwork, faster decision-making, and significantly higher satisfaction across global teams
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High Chat Volume Processing
The solution handles thousands of chat interactions monthly, boosting team productivity by automating candidate screening and cross-language support
Superior Accuracy
AI-powered grammar and translation now exceed 90% correctness, aligning with enterprise benchmarks for robust task automation and minimizing error rates in business communication
Real-Time Collaboration
Response times dropped by over 65%, from 600 ms to below 200 ms, enabling instant chat translation and real-time editing for seamless global teamwork
Measurable User Satisfaction
Manual corrections fell by 40%, and surveys reported marked improvements in decision speed and satisfaction, raising engagement across diverse employee groups
Development Process
We developed a suite of containerized RESTful microservices deployed on AWS EC2 with auto-scaling. The solution leveraged Python 3.x and scikit-learn for natural language processing tasks such as translation, grammar correction, and summarization. AWS services, including Amazon Translate, Elastic Load Balancer, CloudWatch, and Route 53, ensured performance, monitoring, and scalability. Authentication and identity management were handled with OKTA, while GitHub Actions supported CI/CD workflows. The architecture delivered low-latency, accurate AI-powered chat features that seamlessly integrated into the client’s corporate communication platform
Technologies
AI support for corporate chats
AI-powered corporate chat solution delivering instant translation, grammar correction, and summarization
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