The situation
A support team searches across a growing knowledge base.
Enterprise Search Implementation
Enterprise search connects business content to a usable retrieval experience. The work spans source ingestion, document structure, permissions, query behavior and the way relevance is evaluated.
- Understand search tasks
- Design indexing and retrieval
- Measure and operate
Is this right for you?
When this is the right work.
People cannot find the right content, search results ignore business context or an existing index has become difficult to scale and maintain.
The first conversation establishes the environment, the constraint and who will accept the result. We agree a bounded starting point before expanding the engagement.
Scope
What DotConn delivers.
- 01
Understand search tasks
Identify user queries, important content, permissions and the consequences of poor results.
- 02
Design indexing and retrieval
Choose schemas, ingestion paths, refresh behavior and keyword or hybrid retrieval suited to the task.
- 03
Measure and operate
Create a representative query set, review relevance and establish index, failure and recovery routines.
Deliverables
What you receive.
Acceptance criteria identify the checks, records and handover needed for the agreed scope.
- Source, schema and retrieval architecture
- Ingestion pipeline and query configuration
- Relevance evaluation set and operations runbook
In practice
A practical example.
Our approach
We define useful queries, normalize the source content and compare results against an agreed relevance set.
The useful result
Search changes become reviewable through evidence rather than subjective demos alone.
Responsibility
Agree the responsibility.
DotConn
Assesses and delivers the technical work in the agreed scope, with reviewable changes and handover. Continuing operation requires a separately defined managed-service scope.
Your team
Provides authorized access, business priorities and accountable decision-makers; approves policy choices and accepts the agreed result.
Set this boundary early
Search cannot correct every source-quality or access-governance problem. Elasticsearch and OpenSearch choices are evaluated separately from the need for a dedicated search specialist.
FAQ
Questions worth resolving.
Is enterprise search the same as RAG?
No. Search retrieves information. RAG uses retrieved information as context for generation and adds answer-quality and model-behavior evaluation.
Pricing, timing and how to prepare are covered in working with DotConn.
Connected work
Services that work alongside this.
Elasticsearch Implementation
Elasticsearch is a search and analytics engine used to index and retrieve structured and text content. An implementation must connect its data model and query behavior to actual user tasks.
ExploreOpenSearch Implementation
OpenSearch provides search and analytics capabilities, including vector retrieval. A useful implementation is designed around the source data, query workload and operating environment.
ExploreDedicated Search Engineering Specialists
Dedicated search expertise adds architecture, indexing and query capability to your team’s work. The staffing engagement differs from commissioning a defined search-implementation project.
Explore