You will get RAG Pipeline Chat with Your Corprate Data Contnet-Internal-Routine Tasks
Project details
You need a secure, reliable way for your team to query internal company files (PDFs, compliance docs, technical data) using AI, but you cannot risk data leaks or hallucinated answers. I build production-ready, multi-tenant RAG systems engineered to solve these exact enterprise bottlenecks.
What You Get in Your Environment:
• Clean Data Pipelines: Advanced chunking and embedding generation using LangChain and LlamaIndex to process your complex corporate documents accurately.
• Fast Search Setup: A fully optimized Pinecone vector database configured for instant context retrieval and semantic search.
• Ironclad Privacy: Strict user isolation powered by Upstash Redis. Chat histories and data views are separated on a per-User-ID basis, ensuring zero cross-leakage between departments.
• Cost Control: Depending on your preference or the available resources like (GPT-4o/OSS) combined with custom prompt guardrails to block injections and keep your token expenses highly efficient.
• 100% Grounded AI: Zero hallucinations. The model answers using only your verified data.
• 70% Faster Discovery: Your team gets an instant, interactive internal oracle.
What You Get in Your Environment:
• Clean Data Pipelines: Advanced chunking and embedding generation using LangChain and LlamaIndex to process your complex corporate documents accurately.
• Fast Search Setup: A fully optimized Pinecone vector database configured for instant context retrieval and semantic search.
• Ironclad Privacy: Strict user isolation powered by Upstash Redis. Chat histories and data views are separated on a per-User-ID basis, ensuring zero cross-leakage between departments.
• Cost Control: Depending on your preference or the available resources like (GPT-4o/OSS) combined with custom prompt guardrails to block injections and keep your token expenses highly efficient.
• 100% Grounded AI: Zero hallucinations. The model answers using only your verified data.
• 70% Faster Discovery: Your team gets an instant, interactive internal oracle.
Programming Languages
JavaScript, Python, TypeScriptCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$2,200
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 10 days | 20 days | 35 days |
Number of Revisions | 3 | 5 | 5 |
Number of Pages | 3 | 7 | 15 |
Design Customization | - | ||
Content Upload | |||
Responsive Design | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
integration to an existing system
(+ 10 Days)
+$500About Mohammad
Al Automation Expert | Content Automation | LLM | RAG | Multi-Agent
Riyadh, Saudi Arabia - 12:10 am local time
I build complete and (STABLE), production-ready AI products and AI Agents
I don’t do— wrappers, clones, generic chatbot templates.
From architectural design to full-scale cloud deployment, I manage the entire engineering pipeline to deliver a seamless, fully integrated solution.
If you are looking to move past simple AI prompts and build a robust, scalable backend that drives real business value, let’s talk.
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📖 CORE SOLUTIONS I DELIVER
• Production-Grade RAG Pipelines
Enterprise-level document ingestion and retrieval systems ensuring high accuracy. I build custom pipelines that extract, chunk, embed, and retrieve data with precise citations from your knowledge base, making your proprietary data actionable.
• Advanced Multi-Agent Systems & Workflows
Complex business logic requires more than a single LLM call. I architect autonomous agent networks capable of parallel processing, tool utilization, structured output validation, and intelligent synthesis into a single, cohesive output.
• Smart Model Routing & Cost Optimization
AI shouldn't break your budget. I design dynamic routing architectures that utilize cost-effective or local models (like Ollama or Mistral) for high-volume, standard operations, while intelligently escalating to premium APIs (Claude 3.5 Sonnet, GPT-4o) only for critical tasks.
• Full-Stack AI SaaS Integration
I build the entire ecosystem around the AI engine. This includes high-performance async backends (FastAPI), secure authentication, session state management (Redis), database schema design (PostgreSQL), seamless Stripe payment gating, and responsive frontends.
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🛠️ PROVEN CASE STUDIES (From My Portfolio)
1. Parallel LLM Inference Engine (Multi-Agent Architecture)
• The Challenge: Sequential LLM calls for complex multi-agent workflows were causing severe latency, leading to a poor user experience.
• The Solution: Built a highly concurrent architecture using FastAPI and Redis to execute 7 simultaneous Claude API calls across independent behavioral axes. Implemented custom synthesis and scoring layers to merge independent agent insights into one validated response, reducing total latency by over 60%.
2. Automated Content Pipeline (Script to Post Automation)
• The Challenge: Content creators needed an automated, hands-off pipeline to turn raw text scripts into fully assembled, ready-to-publish assets.
• The Solution: Developed an automated pipeline utilizing Playwright and API interception for data gathering, and leveraged FFmpeg assembly via Python backend scripts to auto-generate and manage media assets.
3. Telegram AI Bot & Advanced Automation
• The Challenge: Businesses needed an immediate, intelligent, and conversational touchpoint on messaging platforms that went beyond basic button menus.
• The Solution: Built a production-grade Telegram bot powered by Claude and FastAPI. Integrated advanced browser automation and scheduled pipelines to scrape data, handle session management, and push contextual, AI-driven responses back to users in real time.
4. Fitness Data Integration & Behavioral Mapping
• The Challenge: Extracting and normalizing fragmented user activity data across different wearable ecosystems to feed into a personalized AI tracking system.
• The Solution: Architected a secure OAuth 2.0 authentication flow with Strava and Google Fit. Structured a data pipeline to ingest, clean, and map behavioral data points into a centralized database, allowing downstream LLM agents to deliver tailored lifestyle insights.
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🚀 THE TECH STACK
• AI Engineering: LangChain, LlamaIndex, ChromaDB, FAISS, Pinecone, Qdrant, nomic-embed-text.
• LLM Ecosystem: Claude (Opus/Sonnet/Haiku), GPT-4o, Ollama, Groq, LLaMA 3, Mistral.
• Backend & Infra: Python FastAPI, Redis, PostgreSQL, SQLite, Docker, Linux, Git/GitHub, Vercel Serverless.
• Frontend & Tools: React, Tailwind CSS, Playwright, Scikit-Learn, NumPy, Pandas.
• Specialized: Bilingual AR/EN Systems (Full RTL rendering, native Gulf-market tone, programmatic image/PDF composition).
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🌟 WHY WORK WITH ME?
I don't just write code; I design systems. I optimize for cost, performance, and scalability. When you hire me, you get a clean, well-documented, and fully containerized product that is ready to scale from day one.
Ready to build something custom and powerful? Drop me a message with your project scope, and let's jump on a call to map out the architecture.
Steps for completing your project
After purchasing the project, send requirements so Mohammad can start the project.
Delivery time starts when Mohammad receives requirements from you.
Mohammad works on your project following the steps below.
Revisions may occur after the delivery date.
Multi-User Session Isolation & Security
Integrating Upstash Redis to ensure strict user session isolation, securing data privacy, setting up smart model routing, and testing against prompt injections.
Containerization & Final Handover
Fully packaging the application stack using Docker and delivering the clean, production-ready source code via a secure GitHub repository. (If you prefer a specific way of delivery feel free to ask)