Overview

Our client is a global technology company building AI powered digital products for enterprise users, but as their platform ecosystem grew, they faced challenges in managing multiple services and tenants within a single scalable architecture while maintaining performance and reliability. They wanted to build an AI driven core platform using the MCP framework to support a multi tenant, multi service environment, enable seamless AI integration across services, and create a high performance, future ready system that could scale with their business needs.

Technical Stack

  • MCP Framework
  • Node.js
  • Next.js
  • Python
  • OpenAI API
  • Docker & Kubernetes
  • PostgreSQL
  • AWS

    • Industry

    Information & Technology (IT)

  • region

    • Region

    USA

  • project-size

    • Project Size

    Non-Disclosable

Highlights

Designed a multi-tenant, multi-service architecture with MCP framework

Integrated AI capabilities for intelligent automation and decision support

Built scalable APIs for service-to-service communication

Delivered enterprise-grade reliability, performance, and monitoring

Challenges & Solutions

Client required a robust core architecture supporting multiple tenants and services.

  • Solution: Bacancy’s architects designed a modular multi-tenant architecture using the MCP framework, ensuring easy onboarding of tenants without code duplication.

AI models needed to be integrated across services without impacting system performance.

  • Solution: We built AI microservices in Python, orchestrated with Kubernetes, and connected via lightweight APIs to maintain performance while scaling AI features.

Ensuring platform reliability and resilience for enterprise adoption.

  • Solution: Implemented failover strategies, auto-scaling, and monitoring pipelines with AWS CloudWatch and ELK stack, ensuring uptime and resilience.

Rapid MVP delivery with future scalability in mind.

  • Solution: Bacancy’s LLM and AI developers delivered a scalable MVP within tight timelines, with a modular design supporting quick enhancements and new feature rollouts.

Core Features

  • Multi-tenant, multi-service architecture
  • AI-powered microservices with LLM integration
  • Secure role-based access and dashboards
  • Real-time monitoring and auto-scaling infrastructure
  • no.-of-resources

    • No. of Resources

    04

  • time-frame

    • Time Frame

    January 2025 – August 2025

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