AI-Powered Search & Knowledge Systems
Semantic search, RAG-based retrieval, and citation-backed answers across your enterprise data.
Traditional search fails with unstructured data
Keyword search doesn't understand intent. Your team needs semantic search that finds meaning, not just matching strings — across documents, databases, and knowledge bases.
- Semantic vector search across all document types
- RAG (Retrieval Augmented Generation) for cited, contextual answers
- Multi-source search — docs, databases, APIs, websites
- Real-time indexing as new content is added
- Enterprise-grade with access controls and audit trails
What We Build
Semantic Search
Vector-based search that understands meaning, not just keywords. Find relevant results even with different terminology.
Multi-Source Indexing
Index content from databases, document stores, APIs, and web sources into a unified search layer.
Document Intelligence
Extract, chunk, and embed documents — PDFs, DOCX, spreadsheets, presentations — for intelligent retrieval.
Knowledge Graphs
Build relationships between entities, concepts, and documents for context-aware search results.
Access-Controlled Search
Search results respect user permissions — no unauthorized data exposure.
Real-Time Updates
New documents and data are indexed in real-time, keeping search results always current.
Use Cases
Enterprise Knowledge Search
Replace siloed search tools with a unified semantic search across all company knowledge — wikis, docs, Confluence, SharePoint, and databases.
Research & Discovery Platform
Help researchers find relevant papers, patents, and datasets across millions of documents with AI-powered relevance ranking.
Product Documentation Search
Let customers and support agents search product docs semantically, getting direct answers with source citations.
Legal Document Retrieval
Search across contracts, case files, and regulations with semantic understanding of legal concepts and terminology.
How We Work
Data Inventory
Catalog all data sources and define search requirements.
Index & Embed
Process, chunk, and embed all content into vector stores.
Build & Tune
Develop search interface, tune relevance, and add RAG capabilities.
Deploy & Scale
Production deployment with monitoring, scaling, and continuous indexing.
Why DataTamer
Built by People Who Ship AI Systems
We don't just advise on AI — we build, deploy, and operate AI products every day
We Ship AI Products
We build and operate our own AI platform. This isn't theory — it's daily practice.
Product DNA, Not Consultancy
Engineering-first team that ships code, not slide decks.
Data-Connected AI Expertise
Deep experience with data ingestion, retrieval, vector search, and multi-source intelligence.
Strong UX & Platform Craft
Premium interfaces and product experiences, not generic dashboards.
Concept to Production
From initial architecture to deployed, monitored production systems.
Modern Stack Execution
Next.js, React, Python, Kafka, vector DBs, multi-LLM orchestration — battle-tested.
Start Your AI Project
Tell us what you're building. We'll review and get back within 24 hours.
Book a Strategy Call
30-minute call to discuss your project, requirements, and how we can help.