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$
USD
I will build a rag ai knowledge base for technical teams
Amine E.
About this gig
Technical teams don't always search documentation using perfect keywords.
A technician might describe a machine symptom in natural language, while another query might contain an exact alarm code, parameter, part number or model identifier.
I build internal RAG knowledge assistants designed to handle both.
Your team can search manuals, procedures and technical documents conversationally while still retrieving exact technical identifiers when precision matters.
Answers can include document and page citations, and the assistant can explicitly report when the available documentation does not support an answer.
Depending on the package, I can implement:
- structured, section-aware document ingestion;
- semantic and PostgreSQL full-text hybrid retrieval;
- exact alarm, parameter, model, part, or policy identifier search;
- answers with document and page citations;
- explicit insufficient-evidence behavior;
- conversation history and multi-turn support;
- authentication, roles, administration, usage controls, and pilot monitoring;
- an evaluation set with retrieval, grounding, citation, and behavior analysis.
Get to know Amine E.
Amine E.
RAG and Full Stack AI Developer
- FromMorocco
- Member sinceAug 2026
Languages
Arabic, English, French
I build grounded AI assistants and RAG chatbots that turn PDFs, manuals, SOPs, policies, and internal knowledge into reliable answers with source citations.
I focus on retrieval quality, document ingestion, exact identifiers, insufficient-evidence handling, and clean web chat experiences.
I’ve built SourceChat, a working multi-format document RAG app, plus a technical knowledge assistant using hybrid vector + full-text retrieval.
My stack includes Node.js/NestJS, React, OpenAI, Gemini, PostgreSQL/pgvector, Pinecone, and LangChain.
My Portfolio
FAQ
How is this different from your simple RAG chatbot Gig?
The simple Gig uses ordinary chunking and vector similarity search for a focused document set. This Gig supports structured ingestion, hybrid retrieval, exact identifiers, operational controls, multi-turn workflows, and evaluation.
Can you guarantee an accuracy percentage?
Not before the corpus, questions, and acceptance criteria are reviewed. I will report measured results and limitations rather than promise an unsupported percentage.
Is the Premium package enterprise production-ready?
It is a pilot-ready foundation for the agreed scope. Enterprise readiness may require additional security review, penetration testing, compliance work, disaster recovery, scaling, support, and customer-specific integration.
Can you work with technical identifiers and conflicting document versions?
Yes. Exact-identifier search and version-aware metadata can be included. When sources conflict, the assistant should distinguish applicability or request clarification instead of inventing one universal answer.
Does the assistant replace a qualified engineer or professional?
No. It helps qualified users retrieve and verify approved information. It should not control equipment, authorize safety decisions, or replace professional judgment.
Are provider and hosting fees included?
No. Model, database, storage, authentication, and hosting fees are paid through the buyer's accounts.
What is included in post-delivery support?
The included revision period covers agreed defects. Ongoing maintenance, new documents, prompt tuning, evaluation runs, or new features require an extra or separate order.
