Enterprise Search Services
Your teams know the answer exists somewhere — finding it fast is the problem. We build AI powered enterprise search systems that surface what people need, from the systems they already use.
Trusted by Enterprises in 30+ Countries
OUR SERVICES
Enterprise Search Services We Deliver
RAG
Implementation
We build retrieval augmented generation pipelines so your AI returns answers sourced from your actual enterprise data.
Knowledge Base Development
We structure and index your unstructured content into a reliable enterprise search platform your teams can query in seconds.
Enterprise Search Integration
We connect your enterprise search engine to the tools your teams already use — so the right answer is always one query away.
OUR SOLUTIONS
Our Enterprise Search Solutions
Policy & Coverage Knowledge Search
Clinical Guideline & Protocol Search
Technical Manual & Procedure Search
Unified Cross-System Knowledge Search
Semantic Search Implementation
Role-Based Knowledge Access Control
OUR PROCESS
How We Implement Enterprise Search
Our Approach
We map every content source your organization relies on — structured and unstructured — to understand what exists, where it lives, and how it needs to be connected before we design anything.
Key Activities:
- Content source inventory and classification
- Data quality and accessibility assessment
- Query pattern analysis and user research
- Search scope and integration requirements definition
Our Approach
We design the retrieval and generation architecture around your specific data environment — selecting the right embedding models, vector stores, and retrieval strategies so search returns results that are accurate and contextually relevant.
Key Activities:
- Vector database selection and configuration
- Embedding model evaluation and selection
- Retrieval augmented generation pipeline design
- Integration architecture for enterprise systems
Our Approach
We ingest, chunk, and index your content in a way that preserves meaning — so the search layer understands context, not just keywords. Every document type is handled with the right processing strategy.
Key Activities:
- Document ingestion and preprocessing pipelines
- Chunking and embedding strategy implementation
- Enterprise document search index construction
- Metadata tagging and retrieval optimisation
Our Approach
We connect the enterprise search software layer to your existing tools and deploy it in your environment — whether cloud, on-premise, or hybrid — with access controls and permissions aligned to your org structure.
Key Activities:
- Enterprise system and SaaS connector integration
- Role-based access and permission mapping
- Search interface deployment and configuration
- End-to-end retrieval accuracy testing
Our Approach
Go-live is not the finish line. We provide ongoing support to monitor search performance, resolve issues as they surface, and continuously refine retrieval quality — so the system keeps improving as your data and usage evolve.
Key Activities:
- Query performance monitoring and issue resolution
- Search index updates as new content sources are added
- Feedback loop configuration for continuous improvement
- Periodic retrieval quality reviews and tuning
Our Approach
We map every content source your organization relies on — structured and unstructured — to understand what exists, where it lives, and how it needs to be connected before we design anything.
Key Activities:
- Content source inventory and classification
- Data quality and accessibility assessment
- Query pattern analysis and user research
- Search scope and integration requirements definition
Our Approach
We design the retrieval and generation architecture around your specific data environment — selecting the right embedding models, vector stores, and retrieval strategies so search returns results that are accurate and contextually relevant.
Key Activities:
- Vector database selection and configuration
- Embedding model evaluation and selection
- Retrieval augmented generation pipeline design
- Integration architecture for enterprise systems
Our Approach
We ingest, chunk, and index your content in a way that preserves meaning — so the search layer understands context, not just keywords. Every document type is handled with the right processing strategy.
Key Activities:
- Document ingestion and preprocessing pipelines
- Chunking and embedding strategy implementation
- Enterprise document search index construction
- Metadata tagging and retrieval optimisation
Our Approach
We connect the enterprise search software layer to your existing tools and deploy it in your environment — whether cloud, on-premise, or hybrid — with access controls and permissions aligned to your org structure.
Key Activities:
- Enterprise system and SaaS connector integration
- Role-based access and permission mapping
- Search interface deployment and configuration
- End-to-end retrieval accuracy testing
Our Approach
Go-live is not the finish line. We provide ongoing support to monitor search performance, resolve issues as they surface, and continuously refine retrieval quality — so the system keeps improving as your data and usage evolve.
Key Activities:
- Query performance monitoring and issue resolution
- Search index updates as new content sources are added
- Feedback loop configuration for continuous improvement
- Periodic retrieval quality reviews and tuning
WHY IT MATTERS
Benefits of AI Powered Enterprise Search
Accurate Answers, Faster
AI Grounded in Reality
Less Time, More Output
One Query, All Systems
Decisions Backed by Data
Scales With Your Data
Latest Case Studies
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Rebuilt and unified parcel operations for an Australian logistics network across 1,700+ locations
Unified 1,700+ partner locations and five carrier integrations into a single parcel management platform, processing 10,000+ daily transactions.
Read Full Case Study → -
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Replaced manual loan workflows with a custom platform for a Danish lender
Automated loan origination, credit checks, and document generation for a Danish property credit platform.
Read Full Case Study → -
Delivered a wear analysis and lifecycle management platform for a global mining manufacturer
A third-party tool replaced with a purpose-built inspection and wear platform tracking 900+ mining assets at global mine sites.
Read Full Case Study → -
Delivered three generations of analytics infrastructure for a 250-clinic dental group
Three generations of analytics infrastructure built over 20 years, delivering daily operational dashboards across 250 dental clinics and 1,000+ providers.
Read Full Case Study → -
Designed and built every internal clinical system for Australia's leading cancer centre
Clinical systems, MDT workflows, staff compliance, and an Azure analytics platform built from scratch for a specialist cancer centre across 9 departments.
Read Full Case Study →
TESTIMONIALS
Businesses Worldwide Trust Classic Informatics
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PARTNER WITH US
Why Classic Informatics?
Value Beyond Code
Real-time data and modern systems give your teams the visibility to act.
Deep Tech Expertise
20+ years across legacy, data, and AI — the hard problems aren't new to us.
Built for Growth
We align every solution to your business goals, not just your tech stack.
Reliable Delivery
Expert teams who move fast, communicate clearly, and deliver on time.
AI-First Approach
Every solution we build is designed with AI in mind, from architecture to delivery.
Complete Transparency
You know what we're building, why, and what it costs — at every stage.
FAQS
Frequently Asked Questions
Your Teams Shouldn't Have to Hunt for Answers.
We build enterprise search that works in your environment.
