You will get Ai Agent Recruiter WhatsApp Bot
Project details
ai-agent-recruiter
Building an AI Agent which can talk to candidate on whatsapp, process his resume for a job and conduct a basic interview!
This agent is live, try it out by sending "Hi".
If you want to test diffrent flows, send whatsapp message "CLEAR" this will delete all memory of user and start afresh!
Stack
Using LLM's (DeepSeekV2, Claude (in-progress))
Langfuse for observability
Plivo for whatsapp
MongoDB for database
AssemlyAI/Deepgram for Voice to Text
It will reach out the candidate on whatsapp based on this resume and phone no. Do END-END shortlisting and conduct a basic whatsapp audio based interview
Whatsapp Agent
Check if candidate is available by sending a curated message on whatsapp
Based on his reply
Ask few basic screening round questions like salary, location, etc
Based on predefined rules, if all OK
Ask basic technical questions to the candidate on whatsapps and ask candidate to reply via message
This allows candidate to quickly respond to question and we are able to analyze his communication skills as
Shortlist candidate for technical round
Keep sending status to recrutiers on slack
Building an AI Agent which can talk to candidate on whatsapp, process his resume for a job and conduct a basic interview!
This agent is live, try it out by sending "Hi".
If you want to test diffrent flows, send whatsapp message "CLEAR" this will delete all memory of user and start afresh!
Stack
Using LLM's (DeepSeekV2, Claude (in-progress))
Langfuse for observability
Plivo for whatsapp
MongoDB for database
AssemlyAI/Deepgram for Voice to Text
It will reach out the candidate on whatsapp based on this resume and phone no. Do END-END shortlisting and conduct a basic whatsapp audio based interview
Whatsapp Agent
Check if candidate is available by sending a curated message on whatsapp
Based on his reply
Ask few basic screening round questions like salary, location, etc
Based on predefined rules, if all OK
Ask basic technical questions to the candidate on whatsapps and ask candidate to reply via message
This allows candidate to quickly respond to question and we are able to analyze his communication skills as
Shortlist candidate for technical round
Keep sending status to recrutiers on slack
What's included
| Service Tiers |
Starter
$100
|
Standard
$200
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 7 days | 7 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 4 |
Number of Scenarios | 3 | 4 | 6 |
Number of Graphs/Charts | 2 | 3 | 4 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
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About Manish
AI Engineer | Claude API | AI Agents | OpenClaw | RAG | n8n | Voice AI
83%
Job Success
Noida, India - 4:01 pm local time
I build AI systems that save businesses time, reduce manual work, and generate measurable results — autonomous agents, RAG pipelines, voice bots, and AI-powered SaaS. 8+ years in software engineering, 3+ years focused entirely on AI/LLM systems. OpenClaw expert with production autonomous agents running without human review.
WHO I WORK WITH
Startups building their first AI product
Agencies adding AI to client workflows
Enterprises automating internal operations
Founders who need a senior AI engineer, not a prompt wrapper
WHAT I HAVE BUILT
AI Agents & Multi-Agent Systems
Built a production CRM with AI-powered sales pipeline, reorder prediction, and automated analytics — Claude API driving intelligent decision-making across the platform. Deployed multi-agent systems using OpenClaw with orchestration layers, scheduled automation, tool calling, and governance controls — including an autonomous agent that reviews GitHub PRs end to end without manual intervention. Built Google Document AI automation with n8n workflow pipelines processing thousands of documents with OCR extraction and LLM-powered classification.
RAG Pipelines & Knowledge Systems
Shipped a production RAG pipeline with multi-tenant architecture, document ingestion, smart chunking, semantic search, and voice-based retrieval via Retell AI. Built enterprise knowledge base systems with LangChain, Pinecone, and Chroma — handling bulk processing queues and structured Q&A across large document sets.
Voice AI & Conversational Agents
End-to-end voice agent systems with Deepgram, Amazon Polly, ElevenLabs, Retell AI, and VAPI — full stack voice pipelines from telephony to LLM reasoning to TTS delivery. Real-time speech-to-text, LLM reasoning, and natural text-to-speech delivery. Built voice-enabled AI assistants for customer service and sales automation.
AI Automation & Workflow Engineering
Production n8n workflows with multi-step LLM chaining — Gmail triggers, Google Calendar sync, conditional branching, document extraction, and database operations. Integrated Claude API, OpenAI, and open-source LLMs into automated business workflows, including OpenClaw-based agents for repo and document automation.
LLM Fine-Tuning & Optimization
Domain-specific model training using LoRA, QLoRA, PEFT with Unsloth and Axolotl. Fine-tuned LLaMA 3, Mistral 7B, and Mixtral for medical, legal, and customer service applications. Deployed with vLLM and TensorRT-LLM on AWS SageMaker and RunPod.
AI SaaS & Full Stack Development
Complete product development — Next.js, React, TypeScript, Python, FastAPI, Node.js, PostgreSQL, Supabase, MongoDB, Tailwind CSS. From architecture to deployment on AWS, Vercel, and Docker/Kubernetes infrastructure.
STACK
AI: Claude API, OpenAI, LangChain, LlamaIndex, CrewAI, AutoGen, OpenClaw, n8n
LLMs: GPT-4, Claude Opus/Sonnet, LLaMA 3, Mistral, Mixtral, Gemma
Vector DBs: Pinecone, Chroma, Qdrant, FAISS, Weaviate, Milvus
Voice: Deepgram, Amazon Polly, ElevenLabs, Retell AI, VAPI
Backend: Python, FastAPI, Node.js, NestJS, Django
Frontend: Next.js, React, TypeScript, Tailwind CSS
Database: PostgreSQL, Supabase, MongoDB, Redis, Firebase
DevOps: Docker, Kubernetes, AWS (EC2, S3, Lambda, SageMaker), CI/CD
If you need AI that works in production — not just demos — let's talk. Available 40-50 hrs/week for long-term engagements and can start immediately.
Steps for completing your project
After purchasing the project, send requirements so Manish can start the project.
Delivery time starts when Manish receives requirements from you.
Manish works on your project following the steps below.
Revisions may occur after the delivery date.
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