I will build a multi source ai rag chatbot


Informazioni su questo servizio
Build a RAG system that searches documents, databases, and multiple websites with traceable citations.
I build multi source retrieval for internal knowledge, research, and AI search using private files, databases, and approved websites.
Basic: keyword RAG for one agreed data source.
Standard: hybrid vector and keyword retrieval with weighted RRF, database integration, and a UI or API.
Premium: deployed multi source hybrid RAG across files, databases, and approved websites, with deduplication, updates, evaluation, documentation, and handoff.
My live 37000 line backend discovers, reads, caches, and searches multiple web sources. Canonical source IDs, content hashes, and near duplicate detection prevent repeated storage. Lexical and vector results are deduplicated and fused with weighted RRF.
I also built md for AI, an open source pipeline for cleaning, structuring, chunking, and preserving attribution in book scale content.
OCR, scan cleanup, advanced corpus preparation, complex layouts, live crawling, and scheduled updates are quoted after inspection.
Message me before ordering Standard or Premium with your sources, preferred interface, and five real questions.
Scopri di più su Amin bm
Programming and Tech
- DaRegno Unito
- Membro daago 2026
Lingue
Inglese
Il mio portfolio
FAQ
What kinds of projects fit this gig?
Anything Python-centric: AI features and RAG chatbots, search over your own data, desktop tools, bots, data or document pipelines, research automation, and numerical computing. If you are not sure your idea fits, message me - feasibility answers are free.
Do you build with AI APIs or from scratch?
Both. Depending on your budget and privacy needs I use LLM APIs, open-source models, or classic algorithms - and I will explain the trade-offs in plain language before we start.
Will I own the code and be able to run it without you?
Yes. You receive the full source, a usage guide, and reusable configuration. Nothing is locked to my accounts.
My requirements are not fully clear yet. Is that a problem?
No - that is normal. We do a short discovery first: I ask precise questions, write down the scope, and only then quote. Changes later are negotiated openly instead of silently breaking the timeline.
What happens after delivery?
Each package includes a bug-fix window, and revisions as listed. For systems that need ongoing care

