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I will build a rag chatbot with your documents and data
Vj W
About this gig
Need accurate answers from your documents without manually searching every file?
I will build a focused RAG chatbot or knowledge assistant that retrieves relevant evidence from your approved documents and generates answers with source citations.
Use cases include internal knowledge assistants, policy search, document analysis, technical documentation, customer-support knowledge bases, and reference libraries.
Your delivery can include document ingestion, chunking, embeddings, vector search, retrieval logic, citations, evaluation, API integration, a simple interface, source code, and documentation.
I bring 10 years across data engineering, data science, machine learning, and enterprise AI. I design RAG around evidence, evaluation, access boundaries, and documented limitationsnot unsupported model confidence.
Packages cover defined document counts, source types, and integrations. Paid APIs, hosting, complex OCR, security certification, and unrelated frontend work are excluded unless added through a custom offer.
Please message me before ordering to confirm file types, volume, access rules, integrations, and success criteria.
Get to know Vj W
Vj W
FullStack Agentic AI Agentic Systems Design and Automation, MLOps
- FromUnited States
- Member sinceJan 2025
- Avg. response time2 hours
Languages
English, Hindi
Full-Stack AI/ML Engineer and Applied Statistician with 10 years across data, ML, and enterprise AI. I build agentic workflows, RAG systems, predictive models, data pipelines, APIs, and internal tools.
My work spans banking & finance, retail, and infrastructure, transportation, and logistics.
I turn complex problems into production-ready systems with clear scope, trade-offs, and measurable outcomes.
My Portfolio
Other AI Development Services I Offer
FAQ
What document formats can you use?
I can work with text-based PDFs, DOCX, TXT, Markdown, CSV, HTML, and structured data when legally provided by the buyer. Scanned PDFs, complex tables, handwriting, images, and unusual formats may require OCR or custom preprocessing.
Will the chatbot provide source citations?
Yes. Every package includes source references appropriate to the available document structure. Citation granularity can include document, page, section, or chunk identifiers depending on extraction quality and source metadata.
Can you guarantee that every answer is correct?
No responsible developer can guarantee perfect LLM outputs. I reduce risk through retrieval grounding, test questions, citation checks, refusal behavior, access controls, and documented limitations.
Which models and vector databases do you support?
Depending on requirements, I can use OpenAI-compatible models, LangChain, FAISS, Chroma, PostgreSQL/pgvector, Pinecone, or another approved platform. Final selection depends on data volume, privacy, cost, and deployment needs.
Are API and hosting charges included?
No. Development is included; model usage, embeddings, OCR, databases, cloud hosting, and third-party subscriptions are paid directly by the buyer.
Can you connect the assistant to my application?
Yes. Standard and Premium can include defined API or application integrations. Authentication, proprietary platforms, undocumented APIs, and complex frontend work may require a custom offer.
Is my data kept confidential?
I use supplied data only for the agreed project and do not publish client content. Buyers must have permission to share it. Do not send passwords, API keys, or production secrets through order requirements.
What counts as a revision?
A revision corrects the agreed system when it does not meet documented requirements. New document collections, integrations, workflows, interface features, or changed objectives are additional scope.
