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Fiverr Pro
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I will build a custom ai system fastapi, faiss docker transormer rag
Muhammad Omaid
About this gig
Need a custom AI system, not a wrapper around an API? I plan it, build it from zero, hand you the code.
Muhammad Omaid, Head of AI at Magnus Mage (est. 2019): 8+ years in production, 10+ engineers, 4 AI systems live.
First 5 to 10 days are planning: architecture, library selection, a written plan you approve before code.
What we build from zero:
RAG: custom embeddings, tuned encoding and decoding, FAISS or pgvector, retrieval clustered in 3D to tune chunking and recall.
Post-training: SFT, DPO, QLoRA on Llama, Qwen or Mistral, with eval reports; private inference on your GPUs.
Multi-LLM: routing across open and hosted models by cost, latency and data sensitivity.
FastAPI services with Pydantic schemas, async workers and OpenAPI contracts.
Enterprise Docker containers for large traffic: load-tested, monitored, on AWS, Kubernetes or on-prem.
Security: auth, rate limits, audit log.
Packages: MVP in 30 days, Advanced in 45; Enterprise is a dedicated team at $10,000 per month.
You get source code, architecture doc, load-test and eval reports, CI/CD, walkthrough video, bug-fix window.
Message us before ordering with your use case, data and traffic for a custom quote.
Get to know Muhammad Omaid
Muhammad Omaid
Head of AI at Magnus Mage, LLM RAG and fine tuned models
- FromPakistan
- Member sinceJun 2024
- Avg. response time1 hour
Languages
Urdu, English
Head of AI at Magnus Mage (est. 2019). 8+ years in production software, BS Computer Science (FAST-NUCES), 10+ engineers behind me. I build private, secure AI: fine-tuned open models on your GPUs, RAG over your data (Transformers, embeddings, FAISS, pgvector), FastAPI and Docker services built for large traffic, agents with human-approval guardrails, AI security mapped to OWASP, SOC 2 and ISO 27001. On Web3 my team runs a live layer-1 (two chains, bridge, explorers, wallets); I architected its on-chain KYT. Every delivery includes source, tests and a handover. Message me for a custom quote.
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FAQ
What happens in the planning phase?
Days 1-5 (MVP) or 1-10 (Advanced): we map your use case, data and traffic, choose the architecture and libraries (FastAPI, FAISS or pgvector, Transformers, Docker, Kubernetes) and write a plan with milestones. You approve it before any code is written.
What does RAG built from zero mean?
No framework templates. We train or tune custom embeddings, tune encoding and decoding for your documents, index in FAISS or pgvector, and cluster the retrieval space in 3D to tune chunk size and recall. You get retrieval metrics, not just a chatbot.
What is post-training and when do I need it?
Post-training adapts an open model (Llama, Qwen, Mistral) to your data with SFT, DPO or QLoRA. You need it when prompts and RAG are not enough: domain language, strict output formats, tool calling. Included in Advanced and Enterprise, with an eval report before and after.
What is multi-LLM routing?
One API, several models. Requests are routed by cost, latency and data sensitivity: sensitive data stays on your private model, general tasks go to a hosted model, with fallbacks and per-call cost tracking. Included in Advanced and Enterprise.
Why FastAPI and Pydantic?
FastAPI gives async, high-throughput services with OpenAPI contracts built in; Pydantic schemas validate every request and response so the LLM layer never receives or returns malformed data. Both are written from zero for your system, no boilerplate generators.
How do you handle large traffic?
Enterprise Docker containers with async workers and queues, horizontal scaling on Kubernetes or AWS, caching, rate limits and a load test at your target traffic before handover. Monitoring and alerts are included in Advanced and Enterprise.
Can it run on my own infrastructure?
Yes. Everything ships as Docker containers and runs on your cloud (AWS, GCP, Azure), Kubernetes or on-prem GPUs. For private inference we serve open models with vLLM or Ollama, so your data never leaves your network.
MVP, Advanced or Enterprise: which one?
MVP (30 days): one AI service with RAG, FastAPI and Docker. Advanced (45 days): MVP plus a post-trained model, multi-LLM routing, 3D retrieval clustering and monitoring. Enterprise: a dedicated team at $10,000 per month, two months minimum, renewed as long as you need.
What do I receive at the end?
Source code in your repository, architecture document, load-test and eval reports, CI/CD pipeline, Docker images, a walkthrough video and a bug-fix window. You own the code, the model weights and the data.
How do we work together?
Message before ordering with your use case, data and traffic; we reply with a plan and a custom quote. During the build: daily updates on Fiverr, milestones, a demo at the end of each phase. NDA on request.
