You will get an AI MVP built from idea or no-code to production with Python + AI stack
Rising Talent
Rising Talent
Project details
You will get your AI product built from idea to production — whether you need a fast no-code MVP, a Python backend behind your Lovable or Replit build, or a full system architected from scratch.
Most AI products stall at the same three points: the no-code builder hits its ceiling, the backend can't handle real load, or the MVP works in demo but breaks in production. I cover all three. With 5+ years shipping production AI systems across Healthcare, Finance, Government, and Construction, I build what you can charge for, scale, and hand to a team; NOT just what looks good in a Loom recording
Most AI products stall at the same three points: the no-code builder hits its ceiling, the backend can't handle real load, or the MVP works in demo but breaks in production. I cover all three. With 5+ years shipping production AI systems across Healthcare, Finance, Government, and Construction, I build what you can charge for, scale, and hand to a team; NOT just what looks good in a Loom recording
Programming Languages
HTML & CSS, Python, Ruby/Ruby on RailsCoding Expertise
Cross Browser & Device Compatibility, PSD to HTML, Performance OptimizationWhat's included
| Service Tiers |
Starter
$500
|
Standard
$2,000
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 24 days |
Number of Revisions | 5 | 3 | Unlimited |
Number of Pages | 10 | 10 | 100 |
Design Customization | |||
Content Upload | - | ||
Responsive Design | - | - | |
Source Code |
About Muhammad
Senior AI Engineer | AI Agent Integration, Automation, LLM, RAG Expert
Lahore, Pakistan - 7:31 am local time
𝟕+ 𝐘𝐞𝐚𝐫𝐬, 𝟏𝟓+ Python Production Systems · 𝟕𝟎%+ cost reduction on AI infrastructure · AI Integration · Backend · Automation
A voice agent needs a backend that handles concurrency, a RAG system needs an ingestion pipeline and a multi vendor marketplace needs AI translations wired into a payment and fulfilment system.
𝐈 𝐛𝐮𝐢𝐥𝐝 𝐀𝐈-𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬 𝐚𝐧𝐝 𝐏𝐲𝐭𝐡𝐨𝐧 𝐛𝐚𝐜𝐤𝐞𝐧𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐫𝐮𝐧 𝐢𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧. 𝐌𝐲 𝐰𝐨𝐫𝐤 𝐬𝐩𝐚𝐧𝐬 𝟑 𝐥𝐚𝐲𝐞𝐫𝐬:
- The AI integration layer (agents, voice, chatbots, no code wiring)
- The generative AI layer (LLMs, RAG, fine tuning, evaluation)
- The backend layer that makes both of those reliable
𝐈 𝐛𝐮𝐢𝐥𝐝 𝐚𝐜𝐫𝐨𝐬𝐬 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐬𝐭𝐚𝐜𝐤: 𝐛𝐮𝐭 𝐈 𝐨𝐰𝐧 𝐭𝐡𝐞 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞!
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𝐖𝐇𝐎 𝐈 𝐖𝐎𝐑𝐊 𝐖𝐈𝐓𝐇:
- Founders shipping their first AI product: you need prior production experience on your side, not someone learning on your budget
- SaaS teams adding AI features: LLM integration that handles real usage without cost surprises or reliability risk
- Businesses automating manual workflows: hours of human work converted into scheduled pipelines
- Clients burned by half-finished work full ownership from architecture through deployment and handoff
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𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃:
𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐕𝐨𝐢𝐜𝐞
RetellAI voice agents, WhatsApp/Telegram/Discord bots, MCP servers, CRM automation via N8N · Make · Zapier
𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐒𝐲𝐬𝐭𝐞𝐦𝐬
RAG pipelines, multi-model LLM routing, fine-tuning with automated retraining, multi-agent orchestration (LangGraph), evaluation (LangSmith · PromptLayer · LiteralAI)
𝐁𝐚𝐜𝐤𝐞𝐧𝐝 & 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞
Celery/Redis concurrent task systems, ingestion and scraping pipelines, scheduled workflows, webhook integrations
𝐒𝐚𝐚𝐒 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬
FastAPI/Django APIs, multi-tenant platforms, Stripe billing, RBAC dashboards
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𝐒𝐄𝐋𝐄𝐂𝐓𝐄𝐃 𝐒𝐘𝐒𝐓𝐄𝐌𝐒:
𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐈 𝐒𝐞𝐚𝐫𝐜𝐡
Multi-model routing across OpenAI, Claude, Gemini, and DeepSeek by query type and cost profile
𝐃𝐮𝐚𝐥-𝐀𝐠𝐞𝐧𝐭 𝐌𝐚𝐫𝐤𝐞𝐭 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 · 𝐀𝐮𝐫𝐨𝐫𝐚
Parallel agents running TAM/SAM calculations and competitor analysis simultaneously, synthesizing across Perplexity, EXA, and live web. Research cycles: days → under 30 minutes
𝐕𝐨𝐢𝐜𝐞 & 𝐂𝐡𝐚𝐭 𝐁𝐨𝐨𝐤𝐢𝐧𝐠 𝐀𝐠𝐞𝐧𝐭 · 𝐂𝐨𝐜𝐨𝐜𝐮𝐫𝐞, 𝐋𝐨𝐧𝐝𝐨𝐧
RetellAI phone agent and WATI WhatsApp bot unified via MCP servers for fully automated nightclub reservations. Zero staff intervention across both channels
𝐂𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 · 𝐒𝐪𝐮𝐢𝐝 𝐄𝐑𝐏
GPT-4o-mini fine-tuned on construction datasets with automated weekly retraining. Structured extraction from unstructured estimate PDFs. Processing time: hours → minutes
𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐀𝐈 · 𝐍𝐮𝐫𝐢𝐐
Audio → SOAP notes and patient summaries. AssemblyAI selected after benchmarking four STT providers. Specialty-specific prompt architecture per department
𝐌𝐞𝐝𝐢𝐜𝐚𝐥 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭 · 𝐂𝐡𝐮𝐠𝐡𝐭𝐚𝐢 𝐋𝐚𝐛
Differential diagnosis, report analysis, and test suggestions via MCP tooling. Logfire observability. Live on Play Store
𝐏𝐚𝐫𝐥𝐢𝐚𝐦𝐞𝐧𝐭𝐚𝐫𝐲 𝐓𝐫𝐚𝐧𝐬𝐜𝐫𝐢𝐩𝐭 𝐀𝐈 · 𝐇𝐢𝐥𝐥 𝐌𝐨𝐧𝐢𝐭𝐨𝐫, 𝐂𝐚𝐧𝐚𝐝𝐚
Speaker attribution for parliamentary transcripts. Claude/OpenAI dual-model fallback in production. Manual processing: hours → minutes
𝐌𝐮𝐥𝐭𝐢-𝐕𝐞𝐧𝐝𝐨𝐫 𝐌𝐚𝐫𝐤𝐞𝐭𝐩𝐥𝐚𝐜𝐞 · 𝐀𝐟𝐫𝐨𝐜𝐚𝐫𝐭 · 𝐎𝐣𝐢𝐲𝐨
Lead backend engineer. AI translations, three payment gateways (Stripe · Safepay · Paratika), commission engine, rider app, live streaming. iOS + Android + Web
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𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤:
LangChain · LangGraph · OpenAI · Anthropic · RAG · MCP Servers · Python · Django · Pydantic AI · LangSmith · FastAPI · Redis · Celery · AWS · RetellAI · ElevenLabs · Assembly AI · N8N · Make · Zapier · Supabase · Lovable · Replit · Cursor · Copilot · PromptLayer · NodeJS
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𝐇𝐎𝐖 𝐈 𝐖𝐎𝐑𝐊?
Evaluation is built in from the start: output quality measured before it reaches users. I own architecture through handoff, with documentation your team can actually maintain.
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𝑵𝒆𝒙𝒕 𝑺𝒕𝒆𝒑𝒔
Leave me a message or an offer with what you need integrated. I’ll respond within 24 hours with a straight answer on fit, what the main risks are, and a rough scope.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Assess & Scope
Review your current state: idea, existing build, or broken backend. Define exactly what gets built, what stack fits, and what success looks like before work starts
Architecture Decision
Choose the right path: no-code builder with Python backend, full Python stack from scratch, or fixing and extending what exists. Shared with you before a line of code is written