I build production AI workflows that retrieve the right context, take action across business tools, and complete operational work with monitoring and human review.
Recent systems include a healthcare voice-to-CRM workflow with 150+ call records, a source-grounded RAG platform managing 1,682+ documents, and an AI sales CRM tracking $99.5K+ in revenue.
I handle the complete production path around the AI: agents, tool execution, MCP, APIs, data, permissions, dashboards, evaluation, monitoring, and deployment.
𝗪𝗛𝗔𝗧 𝗜 𝗕𝗨𝗜𝗟𝗗
𝗦𝗘𝗟𝗘𝗖𝗧𝗘𝗗 𝗪𝗢𝗥𝗞
𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗮𝗱𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝘃𝗼𝗶𝗰𝗲 𝘀𝘆𝘀𝘁𝗲𝗺: Connected voice intake to lead qualification, appointments, transcripts, summaries, CRM history, and staff handoff.
𝗔𝗜 𝘀𝗮𝗹𝗲𝘀 𝗖𝗥𝗠: Built call transcription, lead scoring, follow-up actions, pipeline automation, payment workflows, reporting, and $99,500+ in tracked revenue.
𝗥𝗔𝗚 𝗮𝗻𝗱 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲: Built a source-grounded platform managing 1,682+ documents with cited answers, organization access, permissions, audit history, and human review.
𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗔𝗜 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲: Built a pipeline that produced 486 videos in one month across multiple brand workspaces, with asset history and cost tracking.
𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞
I start with the workflow and the action the system must complete. Then I identify the required data, tools, decisions, failure paths, and human controls.
I keep the first milestone focused and independently useful, with clear acceptance criteria, working checkpoints, and testing against the agreed workflow.
Mujtaba S. earns an estimated $7.1k/mo. That's 4.9× the typical freelancer and more than 99.73% of everyone we track.
𝗬𝗢𝗨 𝗖𝗔𝗡 𝗘𝗫𝗣𝗘𝗖𝗧
• Early identification of integration, data, and API risks
• Clear separation between agreed scope and new requirements
• Testing of important workflows and edge cases before handoff
• Documentation covering setup, operation, and known limitations
• Production software your team can operate and extend
𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗦𝗧𝗔𝗖𝗞
◆ 𝗔𝗜: OpenAI, Claude, Gemini, MCP, LangChain, LangGraph, RAG, tool calling
◆ 𝗩𝗼𝗶𝗰𝗲: Twilio, Vapi, Retell, ElevenLabs, Deepgram, OpenAI Realtime
◆ 𝗕𝗮𝗰𝗸𝗲𝗻𝗱: Python, FastAPI, Node.js, REST APIs, GraphQL, WebSockets
◆ 𝗗𝗮𝘁𝗮: PostgreSQL, Supabase, Redis, MongoDB, Pinecone, Qdrant
◆ 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: Next.js, React, TypeScript, React Native
◆ 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: AWS, Docker, Vercel, CI/CD, logging, and monitoring
If you need an AI workflow that can retrieve the right information, act across your systems, and reliably complete real work, send me the current process and the result it needs to produce.