You will get RAG and LangChain Integration, OpenAI, Vector Search, Embeddings, Python
Top Rated
Top Rated
Project details
Production-ready RAG builds with LangChain, OpenAI embeddings, and your choice of vector DB (Pinecone, Weaviate, Supabase pgvector). End-to-end from ingestion to evaluated answers.
You get:
• LangChain pipeline with custom chunking for your content
• Vector DB integration (Pinecone, Weaviate, or pgvector)
• Eval harness to measure answer quality before shipping
• Citation tracking so users verify sources
• Admin UI: ingest docs, monitor queries, tune retrieval
• Production deployment on your hosting
Tech: LangChain, OpenAI text-embedding-3, GPT-4o or Claude Sonnet, Pinecone or Weaviate or Supabase pgvector, FastAPI or Nest.js backend, Next.js admin UI.
Use cases I have built:
• Document Q&A for SaaS knowledge bases (legal, healthcare, finance)
• Internal copilot over Confluence, Notion, Google Drive
• Research assistant with citation tracking
• Multi-tenant RAG for customer-facing AI products
Keywords: rag, langchain, vector search, embeddings, openai, pinecone, weaviate, pgvector, ai document q&a, knowledge base ai, retrieval augmented generation, ai copilot, semantic search.
You get:
• LangChain pipeline with custom chunking for your content
• Vector DB integration (Pinecone, Weaviate, or pgvector)
• Eval harness to measure answer quality before shipping
• Citation tracking so users verify sources
• Admin UI: ingest docs, monitor queries, tune retrieval
• Production deployment on your hosting
Tech: LangChain, OpenAI text-embedding-3, GPT-4o or Claude Sonnet, Pinecone or Weaviate or Supabase pgvector, FastAPI or Nest.js backend, Next.js admin UI.
Use cases I have built:
• Document Q&A for SaaS knowledge bases (legal, healthcare, finance)
• Internal copilot over Confluence, Notion, Google Drive
• Research assistant with citation tracking
• Multi-tenant RAG for customer-facing AI products
Keywords: rag, langchain, vector search, embeddings, openai, pinecone, weaviate, pgvector, ai document q&a, knowledge base ai, retrieval augmented generation, ai copilot, semantic search.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Generated Code, Conversational AIAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$750
|
Standard
$1,800
|
Advanced
$3,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 28 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | |||
Detailed Code Comments | - | ||
Image Upscaling | |||
MLOps | - | ||
Model Deployment | |||
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | |||
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | ||
Source Code |
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EW
Edgard W.
Dec 29, 2025
Faktastisch Development
AJ
Alan J.
Mar 21, 2024
Developer for edu site
AM
Andrea M.
May 5, 2022
Advice for Creation of NFT to be associated with physical art
Punctual and precise in the explanations
AM
Andrea M.
Apr 13, 2022
Advice for Creation of NFT to be associated with physical art
I recommend him, very knowledgeable and helpful
AM
Andrea M.
Feb 22, 2022
Creation of NFT to be associated with physical art
Dmitriy was very helpful to resolve some problems and answer some questions about blockchain technology
About Dmitriy
Senior AI Engineer LangChain OpenAI LLM RAG Agentic AI Developer
100%
Job Success
Zaporizhzhya, Ukraine - 9:51 pm local time
Recent work: Faktastisch (1700+ hrs, $86K, 5-star) full-stack React/Node SaaS rebuild, Proctoring MVP (active), educational platform ($29K React/Next.js), CTO-as-advisor engagements. Past production builds: MediBrain, MyAnswer, VoiceDesk, Cosmo marketplace, Stepler (N1 Swedish Appstore fitness).
What I deliver:
- Senior full-stack architecture: React + Next.js frontend, Node.js + NestJS backend, PostgreSQL/MongoDB
- Code review and architecture consulting for engineering teams
- Production-ready SaaS from MVP to scale
- TypeScript end-to-end, GraphQL APIs, Supabase, AWS infrastructure
- AI integration when projects call for it: OpenAI, RAG, LangChain
Tech stack: React, Next.js, Node.js, NestJS, TypeScript, PostgreSQL, MongoDB, GraphQL, Supabase. Strong Angular and Python background. Lead engineer for product teams.
Senior Full Stack Developer, Full Stack Developer, React Developer, Next.js Developer, Node.js Developer, NestJS Developer, TypeScript Developer, Architecture Consultant, Code Review Specialist, AI Integration Developer.
Steps for completing your project
After purchasing the project, send requirements so Dmitriy can start the project.
Delivery time starts when Dmitriy receives requirements from you.
Dmitriy works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery and content audit
Review your document sources, chunking constraints, accuracy target, and integration points. Choose vector DB and embedding model. Written scope before code.
Build phase (pipeline plus eval)
LangChain pipeline build, vector DB integration, eval harness with your test queries, admin UI for ingestion and monitoring. Iterative demos every two to three days.