AI assistants
AI document search development services
AI document search services connect your file stores to a search that understands meaning. The quality of a provider shows in how it handles the practical problems: deciding what to index, converting scans and complex files, applying permissions so people only see what they may open, testing relevance with real searches, keeping the index current and supporting your data protection work. Ask how a provider approaches each of these, and for evidence such as conversion samples and permission tests, before judging on a demonstration with tidy sample files.
This page covers stages, responsibilities, evidence to ask for, warning signs and support. LetGetGrow builds customer-facing chatbots and internal AI assistants, with the scope, data sources, cost and timeline set out in a custom quotation.
Illustrative diagram
- Discovery
- Conversion
- Build
- Testing
- Maintain
How the engagement runs
Discovery
Stores, file types, users, searches.
Output: Index plan
Sample conversion
Scans and complex files tested.
Output: Conversion report
Build
Index, permissions, interface.
Output: Test search
Testing
Real searches, permission checks.
Output: Test results
Launch and maintain
Refresh routine and reporting.
Output: Live search
The index plan
The plan should list which stores and folders are included, which are excluded and why, which file types are handled, how permissions are read and how often the index refreshes. Review it with your IT and data protection leads before work starts.
Who does what
| Task | Usually |
|---|---|
| Access to file stores | Client IT provides |
| Deciding what to exclude | Client, with provider advice |
| Conversion and indexing | Provider |
| Supplying real search examples | Client |
| Permission testing | Provider, client confirms |
Warning signs
Demo only on sample files
Your scans and formats may behave differently.
Indexes everything by default
Sensitive folders may be included.
No permission testing
Results could reveal restricted files.
No refresh plan
Search returns outdated or deleted content.
Relevance testing
Give the provider a list of real searches staff make, with the documents they expect to find. Testing against this shows whether the right results appear near the top. Ask for the results and how the provider improved weak searches.
Example: evaluating a provider with real files
Illustrative example — not a client case study
Situation: A law firm considers AI search across its precedent bank.
- The provider converts a sample including old scanned precedents and reports accuracy.
- Fifty real searches from fee earners are used to test relevance.
- Permission tests confirm that restricted matter folders never appear in results.
What this shows: The firm decided based on evidence from its own files. This example is illustrative.
What you should receive
Planning
- Index plan with exclusions
- Conversion report
Evidence
- Relevance test results
- Permission test results
Operation
- Refresh routine
- Usage and failed-search report
Conversion samples
Ask for a sample of your scanned and complex files to be converted first, with a report on quality. Poor scans may need rescanning or excluding. This early step avoids surprises after everything is indexed.
Data protection support
Ask where the index and search queries are stored, who can access them and what suppliers do with them. ICO guidance says AI use usually requires a data protection impact assessment.
Support after launch
Ask how new stores are added, how permission changes are reflected and what happens if indexing fails.
Discovery
Expect the provider to ask where documents live, which file types are common, how many there are, who searches and for what, and how permissions are managed today. It should ask for real examples of searches that currently fail. These answers shape the index plan and the testing, and a provider that skips them is guessing.
Where people search
Search might sit in an intranet page, inside your document management system, in a staff messaging tool or in a standalone app. Ask which the provider recommends and how each affects permissions, adoption and cost. Putting search where people already work usually helps adoption.
Summaries and answers
If the provider proposes generated summaries or answers on top of search, ask how it keeps them faithful to the source passages, how sources are shown and how this was tested. Summaries should be optional and clearly labelled.
What the contract should cover
Scope of stores and file types, testing and acceptance, data processing terms, refresh routine, support response times and how you can export your index configuration if you change provider.
Filters people understand
Ask how results can be narrowed by date, client, project, document type or author. Good filters make meaning-based search far more practical, and they depend on capturing those details during indexing. Agree which details matter most before the index is built.
Reporting
Ask for regular reports on searches made, searches with no useful result and any indexing failures. They show where coverage or relevance needs work.
Questions about AI document search development services
What does a document search service include?
Index plan, conversion, build, testing and maintenance.
What proof should a document search provider show?
Conversion samples, relevance tests and permission tests.
Who decides what is excluded?
You, with the provider's advice.
How is relevance tested?
With real searches and the documents staff expect to find.
What about scanned files?
Test a sample first; poor scans may need rescanning.
How often will the provider refresh the index?
A refresh routine agreed in the plan.
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