You will get custom Build RAG Application
Rising Talent
Project details
Build a custom Retrieval-Augmented Generation (RAG) application that transforms your documents into an intelligent AI assistant.
I develop scalable, production-ready RAG solutions that enable users to chat with PDFs, knowledge bases, websites, and business data using the latest LLMs such as OpenAI, Claude, Gemini, and open-source models. My solutions focus on accuracy, source citations, fast retrieval, and seamless user experience.
Whether you need an internal knowledge assistant, customer support chatbot, document search system, or enterprise AI solution, I deliver clean architecture, optimized vector search, and reliable deployment tailored to your requirements.
What sets my service apart:
Custom RAG architecture (not generic templates)
Support for PDFs, websites, databases, and APIs
Vector databases (Pinecone, Chroma, Weaviate, FAISS, Qdrant)
Source citations and hallucination reduction
Modern web UI and API integration
Production-ready deployment and documentation
Get a secure, scalable, and accurate AI-powered knowledge system built specifically for your business.
I develop scalable, production-ready RAG solutions that enable users to chat with PDFs, knowledge bases, websites, and business data using the latest LLMs such as OpenAI, Claude, Gemini, and open-source models. My solutions focus on accuracy, source citations, fast retrieval, and seamless user experience.
Whether you need an internal knowledge assistant, customer support chatbot, document search system, or enterprise AI solution, I deliver clean architecture, optimized vector search, and reliable deployment tailored to your requirements.
What sets my service apart:
Custom RAG architecture (not generic templates)
Support for PDFs, websites, databases, and APIs
Vector databases (Pinecone, Chroma, Weaviate, FAISS, Qdrant)
Source citations and hallucination reduction
Modern web UI and API integration
Production-ready deployment and documentation
Get a secure, scalable, and accurate AI-powered knowledge system built specifically for your business.
Programming Languages
JavaScript, Python, TypeScriptCoding Expertise
Cross Browser & Device Compatibility, Localization, SecurityWhat's included $5,000
These options are included with the project scope.
$5,000
- Delivery Time 5 days
- Number of Revisions 2
- Design Customization
- Content Upload
- Source Code
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JF
Johannes R F.
Apr 8, 2026
Connect Amazon Bedrock AI Agent with HUD Smart Glasses
Excellent work. We just had to make changes to the contract scope and will set up a new contract soon.
AA
Adam A.
Apr 24, 2024
Social media scraping bot
He knows what he is doing. If you want something done well, I would utilize his services.
About Talha
AI Engineer | Chatbots | RAG | Agents | Automations | Voice AI
Lahore, Pakistan - 3:51 am local time
I help startups and teams turn messy data, documents, and manual workflows into reliable AI products. I can own the full lifecycle: problem framing → architecture → model selection/fine-tuning → data pipelines → deployment → evaluation → monitoring → cost and latency optimization.
Over the last decade, I've built credit-scoring, fraud/risk, and recommendation systems for enterprise environments (Accenture, Turing/Dropbox, NETSOL), plus AI products used by millions (Musicfy, Crayo). As a Kaggle Master and AWS Certified Machine Learning - Specialty engineer, I combine ML/DL fundamentals with modern GenAI engineering.
⚙️ WHAT I BUILD
🔸 RAG & knowledge systems — PDF/db/API ingestion, OCR, chunking, metadata, embeddings, hybrid search, re-ranking, citations, RAG evaluation, and Neo4j knowledge graphs
🔸 Agentic workflows & copilots — LangGraph / LangChain / LlamaIndex orchestration with tool use, structured outputs, function calling, memory, human approval flows, guardrails, and MCP/API integrations
🔸 Voice AI — low-latency conversational agents and telephony using VAPI, Amazon Connect, Twilio, Whisper, and ElevenLabs; I cut one voice pipeline from 7s → under 2s with ~95% cost savings
🔸 Chatbots & business automation — support, internal knowledge, lead-gen, sales ops, recruiting, and document-heavy workflows using custom APIs, n8n, Make, and backend services
🔸 Custom ML & deep learning — credit scoring, fraud/risk, forecasting, recommendations, NLP, classification/ranking, feature engineering, explainability, and model evaluation
🔸 LLM fine-tuning — SFT, LoRA, QLoRA, PEFT, dataset preparation, eval sets, and deployment for LLaMA, Mistral, DeepSeek, and Hugging Face models
🔸 Computer vision & document AI — object detection/classification, OCR, forms/tables, Textract, LayoutLM, multimodal vision-language models, and legal/deposition analysis
☁️ CLOUD, DEPLOYMENT & MLOps
🔸 AWS/Azure — Bedrock, Bedrock Agents, AgentCore, SageMaker, Lambda, ECS/Fargate, Amazon Connect, Textract, Azure AI Foundry, Azure OpenAI, Azure ML, Synapse, Databricks
🔸 MLOps — MLflow, W&B, DVC, CI/CD, Docker, Kubernetes, FastAPI, vLLM, quantization, scheduled retraining, and deployment automation
🔸 LLMOps & quality — LangSmith, LangFuse, RAGAS, DeepEval, prompt/version tracking, regression tests, guardrails, monitoring, drift detection, and cost/latency dashboards
🔸 Data engineering — ETL and batch/streaming pipelines with Spark, Databricks, Kafka, Airflow, PostgreSQL, and data warehouses
🏆 PROVEN RESULTS
🔸 Musicfy — AI music-creation platform ($1.5M ARR)
🔸 Crayo — AI video-clipping tool (3.2M users)
🔸 RAG + Neo4j knowledge graph for financial risk assessment
🔸 Voice AI latency cut 7s → under 2s, with ~95% cost reduction
🔸 Credit-scoring models reaching up to 95% accuracy in production workflows
🔸 Recommendation systems improving engagement by up to 50%
🔸 Content-moderation system removing 85% of harmful content
🔸 OCR + LLM resume-screening automation reducing processing time by 85%
🔸 Document-intelligence and legal deposition-analysis platforms using RAG + OCR + LLMs
🧰 TECH STACK
Languages: Python · TypeScript / JavaScript · SQL
GenAI: OpenAI · Claude · AWS Bedrock · Azure OpenAI · LLaMA · Mistral · DeepSeek · LangChain · LangGraph · LlamaIndex · Hugging Face · fine-tuning
ML / DL / CV: PyTorch · TensorFlow · scikit-learn · XGBoost · LightGBM · OpenCV · YOLO · SHAP
Backend: FastAPI · Node.js · Express · REST APIs · WebSockets
Data & Vector: PostgreSQL / pgvector · Pinecone · Qdrant · Weaviate · Neo4j · Elasticsearch / OpenSearch · Spark · Databricks
Infra & Observability: Docker · Kubernetes · AWS · Azure · CI/CD · MLflow · W&B · LangSmith · LangFuse
🏢 INDUSTRIES
Fintech (credit, risk, fraud, underwriting) · Legal (deposition and contract analysis) · Healthcare (clinical NLP) · AI SaaS and creator tools · E-commerce and recommendations · Customer-support automation · Recruiting and document operations
🤝 HOW I WORK
I start with the business problem, success metric, data reality, and deployment environment. Then I design the simplest reliable system: model, retrieval strategy, evaluation loop, and production architecture.
You get clear milestones, fast iteration, technical documentation, and ownership across the AI, backend, and cloud layers. I build secure, maintainable, compliance-aware systems with practical handling for PII, SOC 2, HIPAA, and GDPR-sensitive workflows.
✅ A GOOD FIT IF YOU
🔸 Need a production RAG, chatbot, agent, or Voice AI system
🔸 Want to automate operations and reduce manual work
🔸 Are building an AI SaaS product or adding AI to an existing platform
🔸 Have an AI prototype that is slow, unreliable, expensive, or hard to evaluate
Share what you're building and I'll show you exactly how I'
Steps for completing your project
After purchasing the project, send requirements so Talha can start the project.
Delivery time starts when Talha receives requirements from you.
Talha works on your project following the steps below.
Revisions may occur after the delivery date.
Delivery
Delivery for 100% project