Your data. Instantlyqueryable by AI.
We build RAG systems that let your team and customers ask questions in plain English and get precise, cited answers from your documents, wikis, and databases — with zero hallucinations.
✓ Retrieved 3 relevant chunks
🤖 AI Response:
Enterprise contracts include a 30-day full refund window. After 30 days, a pro-rated refund is issued... [Source: enterprise-tos-v3.pdf, p.12]
Documents Indexed
10M+ vectors
< 2s
Query Response Time
95%+
Retrieval Accuracy
10M+
Docs Indexed
0%
Hallucination Rate*
Purpose-built for accurate, scalable retrieval.
Pinecone
Vector DB
Weaviate
Vector Search
OpenAI
Embeddings & LLM
LangChain
RAG Framework
Supabase
pgvector
LlamaIdx
Document Index
Unstructured
Doc Parsing
Redis
Semantic Cache
Every RAG use case. Zero hallucinations.
Document Q&A Systems
Let users query thousands of PDFs, manuals, and reports in plain English and get precise, cited answers.
Internal Knowledge Bases
Index your company wikis, SOPs, and Confluence/Notion pages into a searchable AI assistant for employees.
Semantic Search Engines
Replace keyword search with meaning-based retrieval — users find what they need even without exact terms.
AI Copilots
Context-aware AI assistants trained on your proprietary data that help teams draft, research, and decide faster.
Multi-Source Retrieval
Combine data from databases, APIs, documents, and web sources into a single unified retrieval pipeline.
Source Citation & Hallucination Control
Every AI response includes verifiable citations from your documents — reducing hallucinations to near zero.
From raw documents to intelligent Q&A.
Data Audit & Ingestion
Identify all source documents (PDFs, URLs, databases, wikis) and plan the ingestion pipeline.
Chunking Strategy
Design optimal chunk sizes, overlap windows, and metadata tagging for maximum retrieval accuracy.
Embedding & Indexing
Generate embeddings with OpenAI or open-source models and index into Pinecone, Weaviate, or pgvector.
Retrieval Pipeline
Build hybrid retrieval (semantic + keyword), re-ranking, and context window optimization.
LLM Response Layer
Integrate GPT-4 or Claude with your retrieval layer, system prompts, and citation enforcement.
Sync & Maintain
Set up automated re-indexing as documents change, with quality monitoring and drift detection.
"DevTaastic indexed our entire 8-year legal document archive — 40,000+ files — into an AI assistant. Our lawyers now find case precedents in seconds instead of hours."
Alex M.
Managing Partner, LexCore Legal
Frequently Asked Questions
Turn your documents into an AI knowledge engine.
Send us a sample of your documents and we'll run a free indexing test with accuracy benchmarks — so you can see results before committing.