Enterprise Search
Hybrid Search Architectures & Dense Vector Retrieval
Overview
Locating information in legacy systems often requires exact keywords. Enterprise Search merges BM25 keyword matching with dense vector retrieval. This hybrid search system understands synonym mappings, intent contexts, and user profiles, ensuring accurate, fast access to the documents you need.
Operational Bottlenecks Addressed
Employees unable to find records due to spelling mistakes or missing exact keywords.
Siloed document servers forcing users to repeat searches across multiple folders.
Slow database query speeds affecting customer support and application performance.
The Altimet AI Solution
We implement Elasticsearch or Qdrant cluster indexing setups, mapping raw documents to vectors. The search engine dynamically weights query metrics, delivering fast, relevant results.
System Pipeline Flow
Ingestion Queue
Parses files, cleans formatting, and generates text segments.
Hybrid Encoder
Creates sparse search matrices and dense vector representations.
Query Matcher
Combines matching scores across lexical and semantic layers.
Analytics Tracker
Analyzes searches that return zero results to guide future model optimization.
Targeted Operational Metrics
95%
Search Click-through
<85ms
Query Speed Response
-75%
Irrelevant Results
Deployment Phasing
Architecture & Integration FAQs
Operational details and technical requirements.
Not sure where AI fits into your business?
Let's identify the opportunities together.
Schedule a complimentary 30-minute AI Opportunity Assessment. We will review your key operational workflows and pinpoint where AI can generate immediate, measurable returns.