You will get a production-ready RAG document intelligence API with FastAPI + LangChain
Project details
You'll get a production-ready, local-first RAG document intelligence system — built the right way, not a tutorial prototype.
I'm a Senior AI Engineer with 8+ years building ML and LLM systems for Fortune 500 clients. This offering is based on DocuMind, a real system I've already shipped: FastAPI backend, ChromaDB vector store (cosine HNSW), LangChain text splitting, Ollama LLM, and a Next.js 15 operator dashboard.
What you get:
• Grounded Q&A — answers backed only by your documents with structured SourceCitation objects (doc ID, section, page, chunk, distance)
• 5 query modes: general, compare, methodology, datasets, reproduce
• FLARE-inspired active retrieval for higher accuracy
• API key auth, CORS, rate limiting, gzip, security headers
• Docker Compose deployment with JSON logging and health probes
• arXiv bulk fetch endpoint for research corpora
This is a complete, auditable, self-hosted system. No data leaves your infrastructure.
Choose your tier based on scope. Enterprise includes custom embeddings, multi-tenant support, and 2 weeks of post-launch support.
I'm a Senior AI Engineer with 8+ years building ML and LLM systems for Fortune 500 clients. This offering is based on DocuMind, a real system I've already shipped: FastAPI backend, ChromaDB vector store (cosine HNSW), LangChain text splitting, Ollama LLM, and a Next.js 15 operator dashboard.
What you get:
• Grounded Q&A — answers backed only by your documents with structured SourceCitation objects (doc ID, section, page, chunk, distance)
• 5 query modes: general, compare, methodology, datasets, reproduce
• FLARE-inspired active retrieval for higher accuracy
• API key auth, CORS, rate limiting, gzip, security headers
• Docker Compose deployment with JSON logging and health probes
• arXiv bulk fetch endpoint for research corpora
This is a complete, auditable, self-hosted system. No data leaves your infrastructure.
Choose your tier based on scope. Enterprise includes custom embeddings, multi-tenant support, and 2 weeks of post-launch support.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Hugging FaceAI Models
LLaMAWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$3,000
|
Advanced
$5,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 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 |
Frequently asked questions
About Drake
Senior AI Engineer & Architect | Enterprise LLM Agents | GCP Vertex AI
Acworth, United States - 7:47 pm local time
I specialize in LangChain, LangGraph, multi-agent orchestrations, RAG pipelines, and robust FastAPI backends that translate complex AI into measurable business impact.
🤖 Agentic AI & LLM Engineering
Autonomous Workflows: Design and deploy multi-agent systems using LangChain and LangGraph for high-stakes enterprise use cases (underwriting, fraud detection, document intelligence).
Production RAG: Build advanced Retrieval-Augmented Generation systems scaling across millions of documents.
Integrations: Connect agentic workflows seamlessly into core communication stacks, including Slack, Telegram, and enterprise email environments.
☁️ End-to-End ML & MLOps on GCP
Vertex AI Mastery: Build complete enterprise pipelines—from data preparation and training to evaluation, deployment, and continuous monitoring.
Proven ROI: Led predictive modeling for fraud detection (30% accuracy improvement), student retention, and predictive maintenance (80% reduction in operational events) across 20TB+ datasets.
Cost Optimization: Architected cloud infrastructure refinements that cut client cloud spend by 50%.
⚡ FastAPI & Production API Development
Backend Architecture: Build high-performance, asynchronous RESTful APIs utilizing Pydantic validation, async job processing, and Docker containerization.
System Integration: Deliver clean API layers engineered to power real-time dashboards, integrate with legacy CRMs, and serve production ML models at scale.
📊 Data Science & Technical Stack
Core Competencies: Python, SQL, BigQuery, XGBoost, LightGBM, SHAP/LIME explainability, and advanced feature engineering.
Enterprise Delivery: Trusted to deliver mission-critical solutions for Fortune 500 clients, including Morgan Stanley, Wells Fargo, US Bank, and Verizon.
I bridge the gap between deep technical execution and executive-level strategy. I work at $80/hr and bring principal-level execution to every engagement.
Let's hop on a call and talk about what you need built.
Drake Talley
Principal AI Engineer | PrismBase.ai
Steps for completing your project
After purchasing the project, send requirements so Drake can start the project.
Delivery time starts when Drake receives requirements from you.
Drake works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Architecture Design
Review your documents, use cases, and infra. Define chunking strategy, embedding model, retrieval config, and API surface. Deliver architecture doc.
Ingestion Pipeline & Vector Store Build
Build document ingestion (PDF/DOCX/TXT), chunking, embedding, and ChromaDB vector store with cosine HNSW indexing. Wire FastAPI ingest endpoints.