Intelligent AI Agents for Business Support & Customer ServiceMuhammad Hassan
We offer a comprehensive AI agent solution that integrates Azure for hosting and DevOps, Flask APIs for microservices, OpenAI and Gemini for advanced LLM capabilities, and vector databases for semantic search. Our end-to-end approach includes custom model fine-tuning, production deployment, and thorough documentation and training, ensuring businesses can effectively leverage AI for customer support and data-driven insights.
What's included
Azure-Based Infrastructure Setup
Provision and configure Azure resources (App Service, Azure Functions, Azure Storage, etc.) to host and scale your AI agent system. This includes setting up Azure DevOps pipelines for continuous integration and delivery
OpenAI LLM Integration
Integrate OpenAI’s large language models (e.g., GPT-4) to enable natural language understanding and generation for chatbots, customer support automations, or knowledge base Q&A. Includes prompt engineering and performance tuning.
Flask API for Chatbot & Microservices
Develop a lightweight Flask backend that exposes RESTful endpoints for AI-based services. This API will handle incoming requests, coordinate with various ML/LLM modules, and return responses to frontend or third-party systems.
Gemini Integration for Advanced AI Features
Leverage Google’s Gemini or similarly advanced AI platforms for enhanced reasoning, multi-modal features, and complex analytics. Integrate Gemini’s APIs into your existing pipeline for superior accuracy and performance.
Vector Database Implementation
Deploy and configure a vector database (e.g., Milvus, Pinecone, or similar) to store and retrieve embeddings. This database supports semantic search and allows your AI agents to quickly identify relevant information from large corpuses.
Starting at$30 /hr
Tags
Azure
Flask
Google Gemini
LangChain
AI Agent Developer
AI Chatbot Developer
AI Developer
Service provided by
Muhammad Hassan proKarachi, Pakistan
- $50k+
- Earned
- 10
- Paid projects
- 5.00
- Rating
- 119
- Followers
Intelligent AI Agents for Business Support & Customer ServiceMuhammad Hassan
Starting at$30 /hr
Tags
Azure
Flask
Google Gemini
LangChain
AI Agent Developer
AI Chatbot Developer
AI Developer
We offer a comprehensive AI agent solution that integrates Azure for hosting and DevOps, Flask APIs for microservices, OpenAI and Gemini for advanced LLM capabilities, and vector databases for semantic search. Our end-to-end approach includes custom model fine-tuning, production deployment, and thorough documentation and training, ensuring businesses can effectively leverage AI for customer support and data-driven insights.
What's included
Azure-Based Infrastructure Setup
Provision and configure Azure resources (App Service, Azure Functions, Azure Storage, etc.) to host and scale your AI agent system. This includes setting up Azure DevOps pipelines for continuous integration and delivery
OpenAI LLM Integration
Integrate OpenAI’s large language models (e.g., GPT-4) to enable natural language understanding and generation for chatbots, customer support automations, or knowledge base Q&A. Includes prompt engineering and performance tuning.
Flask API for Chatbot & Microservices
Develop a lightweight Flask backend that exposes RESTful endpoints for AI-based services. This API will handle incoming requests, coordinate with various ML/LLM modules, and return responses to frontend or third-party systems.
Gemini Integration for Advanced AI Features
Leverage Google’s Gemini or similarly advanced AI platforms for enhanced reasoning, multi-modal features, and complex analytics. Integrate Gemini’s APIs into your existing pipeline for superior accuracy and performance.
Vector Database Implementation
Deploy and configure a vector database (e.g., Milvus, Pinecone, or similar) to store and retrieve embeddings. This database supports semantic search and allows your AI agents to quickly identify relevant information from large corpuses.
$30 /hr