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Fiverr Pro
English
$
USD
I will build custom autonomous ai agents and rag pipelines
Muhammad Saif
About this gig
Are off-the-shelf chatbots and simple GPT wrappers failing to handle your business logic?
I design and build production-ready, autonomous AI agents and robust Retrieval-Augmented Generation (RAG) pipelines tailored to handle complex workflows, domain-specific data, and dynamic tool execution.
Instead of unreliable prompt chains, I build deterministic, stateful multi-agent systems that reliably reason, call internal APIs, and extract accurate answers from your private documents.
What I Can Build For You:
Autonomous Multi-Agent Systems:Dynamic workflows using LangGraph with cyclical reasoning, human-in-the-loop validation, and fallback mechanisms.
Enterprise RAG Architectures:Hybrid search pipelines combining dense vector search (Qdrant, Pinecone, ChromaDB) with BM25 keyword matching and re-ranking models.
Custom Tool Integration:Agents connected directly to your SQL databases, external REST APIs, CRMs, and email endpoints.
Production-Ready APIs:High-performance, async backends built with FastAPI and clean data models.
Clean Interactive Dashboards:Functional frontends using Streamlit for rapid testing and internal business operations.
Get to know Muhammad Saif
Muhammad Saif
AI Engineer and Systems Architect
- FromPakistan
- Member sinceFeb 2026
Languages
Urdu, English, Turkish
Hi, I'm an AI Engineer specializing in production-grade Autonomous AI Agents and custom RAG pipelines.
I build stateful, deterministic AI systems that solve real business problems without hallucinations.
What I deliver:
• Multi-Agent Workflows: Stateful graphs using LangGraph & tool calling.
• Custom RAG: Hybrid search with Qdrant, Pinecone & accurate document retrieval.
• Backends & UIs: Scalable FastAPI endpoints & interactive Streamlit dashboards.
Let’s turn your complex workflow into a reliable, automated AI solution. Send a message to get started!
FAQ
Will the AI hallucinate or make up false information?
I mitigate hallucinations by implementing strict system prompts, chunk-specific context constraints, citations back to source documents, and re-ranking layers in the RAG pipeline.
Can you deploy the agent on my own server/cloud?
Yes. I containerize the application using Docker, making it easy to deploy on AWS, GCP, DigitalOcean, or your on-premise infrastructure.
Can the agent connect to my internal databases and APIs?
Absolutely. Using structured tool-calling schemas (via Pydantic), the agent can execute SQL queries, trigger webhooks, and read/write data securely.
Do I need to provide API keys?
Yes, you will need to provide your own API credentials (e.g., OpenAI, Anthropic, or vector database keys). I can guide you through setting them up securely using .env files.
