You will get AI customer support agent with RAG knowledge base and escalation
Project details
Generic AI chatbots answer from training data and hallucinate when they don't know. That destroys customer trust fast. I build AI
Customer Support Agents grounded in your actual documentation FAQs, product manuals, help articles, internal wikis so every answer is accurate, traceable, and on-brand.
It is a production support system with RAG retrieval, confidence scoring, escalation logic, CRM sync, and full audit trails.
WHAT I DELIVER:
✅ RAG knowledge base ingests your docs, PDFs, URLs, Notion, Confluence, or internal database
✅ Semantic search retrieval answers grounded in your actual content, with source citations
✅ Confidence scoring agent knows when it does not know and escalates instead of hallucinating
✅ Smart escalation creates structured tickets with conversation summary, issue tag and priority score
✅ CRM / helpdesk sync Zendesk, Intercom, HubSpot, Freshdesk
✅ Sentiment detection flags frustrated or high-value customers for immediate human routing
✅ Multi-channel website chat, WhatsApp, Slack, email
✅ Analytics dashboard resolution rate, escalation rate, top unanswered questions, CSAT trends
✅ Works with OpenAI, Anthropic, Azure OpenAI, and self-hosted LLMs
Customer Support Agents grounded in your actual documentation FAQs, product manuals, help articles, internal wikis so every answer is accurate, traceable, and on-brand.
It is a production support system with RAG retrieval, confidence scoring, escalation logic, CRM sync, and full audit trails.
WHAT I DELIVER:
✅ RAG knowledge base ingests your docs, PDFs, URLs, Notion, Confluence, or internal database
✅ Semantic search retrieval answers grounded in your actual content, with source citations
✅ Confidence scoring agent knows when it does not know and escalates instead of hallucinating
✅ Smart escalation creates structured tickets with conversation summary, issue tag and priority score
✅ CRM / helpdesk sync Zendesk, Intercom, HubSpot, Freshdesk
✅ Sentiment detection flags frustrated or high-value customers for immediate human routing
✅ Multi-channel website chat, WhatsApp, Slack, email
✅ Analytics dashboard resolution rate, escalation rate, top unanswered questions, CSAT trends
✅ Works with OpenAI, Anthropic, Azure OpenAI, and self-hosted LLMs
AI Algorithms
CycleGAN, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AIOps, Anomaly Detection, Conversational AI, Natural Language Generation, Natural Language Understanding, Sequence Modeling, Text Recognition, Time Series ForecastingAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, Jasper AI, PyTorch, StreamlitAI Models
BERT, ChatGPT, GPT-4, LLaMA, Naive Bayes Classifier, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$700
|
Standard
$2,000
|
Advanced
$4,000
|
|---|---|---|---|
| Delivery Time | 6 days | 15 days | 25 days |
Number of Revisions | 1 | 3 | 6 |
AI Model Integration | |||
Batch Normalization | - | - | |
Database Integration | |||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | |||
Model Monitoring | - | ||
Model Testing & Optimization | - | - | |
Model Tuning | - | - | |
Natural Language Processing | |||
NLP Tokenization | - | - | |
Pre-Training | - | - | |
Prompt Engineering | |||
Setup File | |||
Source Code |
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CR
Carmen R.
May 11, 2026
Senior Distributed Systems Architect for MCP Security Gateway
It was a great pleasure working with Talha.
SC
Shariann C.
Apr 11, 2026
Software Developer for Advanced AI Projects (Agentic LLM Platform)
He seemed to know what he was doing but he was very delayed in deliverables so we could no longer work together.
JL
Jesse L.
Aug 30, 2023
Formatter for Phonetics/Translation book (Using type setter)
Work wasn't bad, Talha completed the task and patiently revised multiple requests in details and formatting. Was polite and responded fairly quickly to messages.
PA
Pavel A.
Mar 12, 2023
Stable Diffusion Trainer is needed
Talha did a good job of training a custom stable diffusion model
About Talha
Agentic AI Engineer | RAG, LangChain, LangGraph | LLM Chatbot & Python
75%
Job Success
Dina Mor, Pakistan - 11:39 pm local time
Most engineers bolt AI onto an existing product. I architect it in from day one, with AI security controls, compliance layers, and full observability built before deployment, not patched in afterward.
WHAT I BUILD
AI Agents & Multi-Agent Systems - autonomous agents that reason, plan, and execute across complex workflows with LangChain, LangGraph, CrewAI, and Model Context Protocol (MCP). Orchestrator-executor architectures with human-in-the-loop checkpoints built in from the start.
RAG & LLM Pipelines - Retrieval Augmented Generation with hybrid semantic search, embeddings, and vector database optimization across Pinecone, Qdrant, Weaviate, ChromaDB, and pgvector, with sub-100ms query latency. LLM fine-tuning with LoRA, DSPy, and RAFT for legal, medical, and financial data.
AI Chatbots & Voice AI - customer support agents and voice agents using Vapi, Retell AI, ElevenLabs, Twilio, and Whisper, with escalation, memory, and multi-turn context handling.
AI Automation & Integration - n8n, Make, Zapier, and GoHighLevel workflows wired into your existing tools, CRMs, and legacy systems. Function calling and strict structured outputs for reliable, repeatable runs.
AI Security - prompt injection defense, PII detection, knowledge-graph audit trails, and guardrail layers for regulated healthcare and fintech, on top of OpenAI and Anthropic Claude deployments.
SaaS Development - Python, FastAPI, Node.js, React, Next.js, PostgreSQL, Redis, Docker, and AWS. Multi-tenant architecture with RBAC, Stripe billing, and white-label support, scalable to 50,000+ concurrent users.
LLMOps & Observability - LangSmith, Langfuse, Helicone, LiteLLM, and Guardrails AI for tracing, evaluation, cost monitoring, and reliability engineering in production.
RESULTS
73% hallucination reduction on a fintech platform at 1M+ transactions/day
65% lower LLM response latency in production
60% reduction in manual ops cost for healthcare and real estate
100+ systems shipped across 35+ businesses worldwide
SELECTED WORK
MCP Security Gateway - senior distributed-systems architecture for a secure, observable gateway controlling agent tool access.
AI Voice Agent SaaS - full-stack platform that catches missed calls and pushes leads straight into a CRM flow.
LeadIntel AI - lead-generation SaaS with AI automation and personalized LLM outreach.
StudyFlow OS - enterprise AI learning platform with retrieval-grounded answers.
INDUSTRIES
Healthcare, Fintech, Legal, Real Estate, B2B SaaS, Logistics, Insurance, E-Commerce, MedSpa, Staffing & Recruiting, Education & EdTech, Cybersecurity, Proptech, and Wellness & Health Tech.
STACK
LLMs: OpenAI (GPT-4o, GPT-4.1), Anthropic Claude, Google Gemini 2.5 Pro, LLaMA 4, DeepSeek R1, Mistral, Ollama (local/private).
Agentic: LangChain, LangGraph, CrewAI, LlamaIndex, MCP.
Voice: Vapi, Retell AI, ElevenLabs, Whisper, Twilio.
Automation: n8n, Make, Zapier, GoHighLevel.
Vector DBs: Pinecone, Qdrant, Weaviate, ChromaDB, pgvector.
LLMOps: LangSmith, Langfuse, Helicone, LiteLLM, Guardrails AI.
Backend: Python, FastAPI, Node.js, REST, GraphQL.
Frontend: React, Next.js.
Infra: AWS, Docker, Kubernetes, CI/CD, Redis, PostgreSQL.
SPECIALIZED CAPABILITIES
Domain document parsing with RAFT for dense medical charts, legal deeds, and financial filings, training models to skip boilerplate and extract only the data your workflow needs. DSPy-compiled pipelines that self-optimize against success metrics instead of fragile hand-tuned prompts. Large-context analysis of entire legacy codebases for accurate architectural breakdowns before a rebuild.
HOW I WORK
I start by scoping the actual problem and the success metric, not the tooling. You get clear milestones, working demos early, and clean, documented code you or your team can maintain. I communicate proactively, respond within hours, and flag risks before they become blockers.
WHO I WORK WITH
Founders and teams who need AI that survives real traffic: production reliability, security, and observability over flashy prototypes. Whether you are adding your first AI agent, fixing a RAG system that hallucinates, or scaling a multi-agent platform, I can take it from architecture to deployment.
WHAT YOU GET
Production-ready code, architecture diagrams, evaluation and test coverage, deployment scripts, and a short handover doc so nothing lives only in my head. Built to scale, secure by default, and easy for your team to extend, with clear inline comments throughout the codebase.
Open to hourly, fixed-price, and ongoing retainer engagements. If you need AI that runs reliably in production with security and observability built in from day one, send me a message and let's scope your project. I reply quickly.
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.
Step:
Client purchases the project and sends requirements.
Step:
Review of your knowledge sources, support channels, escalation logic and helpdesk integration requirements.