You will get AI-first CRM: Autonomous sales, ops & finance cockpit for founders
Project details
Let your CRM manage your company.
We build AI-native CRMs where autonomous agents run your sales, operations, and finance end-to-end — while your team steps in only to approve high-stakes decisions.
What gets automated:
• Sales — call transcription, AI-generated proposals, follow-ups, pipeline hygiene
• Operations — project plans, task assignments, delivery tracking, bottleneck detection
• Finance — real-time analytics on revenue, margin, burn, receivables
• Founder cockpit — daily briefings on what happened, what's blocked, what needs your call
Why work with us:
PGAGI is an AI-native studio with Top Rated Plus status on Upwork and 45+ engineers shipping agentic systems in production. We also run Toingg, our voice and messaging AI platform handling 10,000+ calls daily in partnership with ElevenLabs — so we build at real scale, not demo scale.
Who this is for:
Founders and operators of 5–100 person companies tired of their team spending half their time updating tools instead of doing actual work.
Delivery: Fixed-price, milestone-based, built on your stack. Every module ships production-ready with role-based approval workflows so humans stay in control of what matters.
We build AI-native CRMs where autonomous agents run your sales, operations, and finance end-to-end — while your team steps in only to approve high-stakes decisions.
What gets automated:
• Sales — call transcription, AI-generated proposals, follow-ups, pipeline hygiene
• Operations — project plans, task assignments, delivery tracking, bottleneck detection
• Finance — real-time analytics on revenue, margin, burn, receivables
• Founder cockpit — daily briefings on what happened, what's blocked, what needs your call
Why work with us:
PGAGI is an AI-native studio with Top Rated Plus status on Upwork and 45+ engineers shipping agentic systems in production. We also run Toingg, our voice and messaging AI platform handling 10,000+ calls daily in partnership with ElevenLabs — so we build at real scale, not demo scale.
Who this is for:
Founders and operators of 5–100 person companies tired of their team spending half their time updating tools instead of doing actual work.
Delivery: Fixed-price, milestone-based, built on your stack. Every module ships production-ready with role-based approval workflows so humans stay in control of what matters.
AI Development Type
Knowledge Representation, Recommendation System, Software MaintenanceAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$3,700
|
Standard
$5,100
|
Advanced
$7,200
|
|---|---|---|---|
| Delivery Time | 20 days | 35 days | 45 days |
Number of Revisions | 2 | 2 | 3 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
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Ali D.
May 20, 2025
Machine Learning and Data Science
Very talented, smart, and dedicated ml engineer. he became part of our ML development team. We are very happing to have him in our team.
MS
Manish S.
Aug 29, 2024
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Joseph R.
Aug 27, 2024
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Alina S.
Aug 2, 2024
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Gagat B.
May 16, 2024
VA table 2
excellent result, talented, beyond what I expected, will contract him again
About Neelambar
Full Stack AI Developer | AI Automation | AI Integration | AI Engineer
100%
Job Success
Pune, India - 11:07 am local time
I have noticed that most AI projects don't fail after the MVP stage. They fail when a user hits a long-running workflow, and the system freezes, or 100 other things that are not expected. I build the infrastructure that prevents such failures when moving from an AI demo to a system that handles real users, real data, and real consequences.
Right now, asking a coding agent to build an application is a commodity any beginner can experiment with. The engineers worth hiring are the ones who keep an agent running under real load, recover it when it crashes, and know exactly what it was doing when it did. The difference is exactly that between a sailing ship and a nuclear submarine.
Over the last few years, my team and I have built 80+ AI systems across industries. And these are real systems up and running right now with real users, real revenue, and a real business impact.
We specialize in building systems that are:
- Enterprise-grade
- Reliable while maintaining harness with non-deterministic LLM
- Scalable, handling unexpected load
- Secure, with complex vulnerabilities taken care of in-house
- Integrated into real businesses solving real problems
- Built for ROI
What I Build:
- AI SaaS MVPs and Production builds: Next.js/React.js + AI Agents + CRMs/Tools + Stripe
- Multi-Agent Systems: LangGraph + LLM pipelines, 80+ products in production
- Enterprise RAG: Context-aware engines across Notion, Slack, SQL & Drive (10K+ docs)
- AI Voice Agents: Livekit + Vapi + ElevenLabs for appointment booking, sales, support
- MCP Servers: Custom servers exposing your data to your agents
- n8n + LLM Workflows: End-to-end automations with CRM, email, voice, WhatsApp
- Multi-Channel Ops: Telegram, Shopify + Square + Wholesale unified in Google Sheets / QuickBooks
Specialized in:
- Claude Ecosystem: Claude Code, Cowork, MCP, Skills, Plugins, Agent SDK, OpenClaw (self-hosted)
- Voice AI Agents: Livekit, Retell, Vapi, Bland, Synthflow, ElevenLabs, Deepgram, Whisper, Custom pipeline
- AI Systems: RAG, GraphRAG, SQL Agents, Multi-Agent Systems, Computer Use, Browser Automation
- Frameworks: LangChain, LangGraph, CrewAI, Pydantic AI, OpenAI SDK, Claude Code, Deep Agents, Livekit
Technical Stack:
- AI & LLMs: Anthropic Claude, OpenAI, Gemini, DeepSeek, Llama / Ollama (local)
- Voice & Real-Time — LiveKit, WebRTC, SIP, RTP, Deepgram, ElevenLabs, OpenAI Realtime API.
- Orchestration: LangChain, LangGraph, CrewAI, Pydantic AI, MCP, Temporal, Langfuse
- Vector & Data: Qdrant, Pinecone, ChromaDB, Supabase, PostgreSQL, pgvector
- Backend: Python, FastAPI, Node.js, TypeScript, Docker, Kubernetes, AWS, Redis, Apache Kafka.
- Frontend: Next.js, React, Tailwind, Vercel AI SDK
- Automation: n8n, Claude Code, Webhooks, REST APIs, OpenClaw
What you can expect:
Systems-first delivery. Not scripts that work once in isolation. Services with logging, error handling, and observability built in from the start, because retrofitting these into a broken production system costs three times what it would have taken to include them.
Technical honesty. If your use case doesn't need a large language model, I'll tell you. If a specific model is overkill for your budget and use case, I'll say so. I have lost projects being upfront about this. The ones I keep tend to run long.
Clean handoff. Containerized, fully documented codebases built for your team to maintain, extend, and understand without me in the room.
Steps for completing your project
After purchasing the project, send requirements so Neelambar can start the project.
Delivery time starts when Neelambar receives requirements from you.
Neelambar works on your project following the steps below.
Revisions may occur after the delivery date.
Deep-dive workshop to map your sales, ops, and finance workflows.
We audit your current tools, define agent responsibilities, and deliver a system architecture doc with approval workflows and integration blueprint