Pricing and quotation guide
AI document search development cost
AI document search costs depend on how many documents there are and in what condition, how many stores they live in, how many need converting from scans, how permissions are handled, whether summaries or answers are added and how the index is kept current. Running costs include hosting the index, AI processing for indexing and searching, and possibly a search platform subscription. Re-indexing when files change has a cost too. The volume and state of your files usually matter more than the search technology chosen.
This guide covers cost drivers, typical scopes, pricing approaches, running costs and comparing quotes. It gives no prices, because they depend on your files, users and suppliers; LetGetGrow sets out the cost for your project in a custom quotation.
Illustrative diagram
What drives document search cost
- Document volume
- More files mean more indexing and storage.
- Scans and complex files
- Text recognition and checking add work.
- Number of stores
- Each connection needs setup and permission reading.
- Permissions
- Applying access at search time adds design and testing.
- Summaries
- Generated answers add AI usage and testing.
Costs paid to third parties (separate from our fees)
- Index hosting or search service
- AI processing fees for indexing and queries
- Text recognition tools
- Storage
Ask for indexing costs to be estimated for your current volume and annual growth.
Projects compared
| Scope | Typical inclusions | Relative cost |
|---|---|---|
| One store | Digital documents, simple permissions, passage results | Lower |
| Several stores | Mixed file types, permissions from each source | Moderate |
| Large archive | Many scans, complex permissions, summaries | Higher |
How document search is priced
Discovery and sample first
Suits you when
- File condition unknown
Watch out for
- Conversion report you keep
Fixed build plus running
Suits you when
- Scope known
Watch out for
- Running fee estimates
Phased by store
Suits you when
- Many stores
Watch out for
- Shared setup reused
Conversion
Digital documents index easily. Scanned files need text recognition, and poor scans need checking or rescanning. Ask for a sample conversion to estimate the cost for the whole archive.
Running costs
Hosting the index and processing searches incur ongoing fees, and re-indexing changed files uses AI processing too. Large, frequently changing archives cost more to keep current. Ask for estimates at your volume and change rate.
Example: phasing by file store
Illustrative example — not a client case study
Situation: An architecture practice has project files across several drives and an old scanned archive.
- Phase one indexes current project drives, which are digital.
- A sample of the scanned archive is converted to estimate quality and cost.
- Only the most-requested archive years are converted in phase two.
What this shows: The practice paid for conversion where it was most useful. This example is illustrative.
Permissions
Reading permissions from each store and applying them at search time is essential for internal search and takes careful work. Simpler permission structures make it cheaper.
Comparing quotes
Check stores covered, file types, conversion, permissions, interface, summaries, relevance and permission testing, running cost estimates, refresh routine and support.
Keeping the cost down
Start with the most-used store, exclude archives nobody searches, convert scans selectively, skip summaries at first and tidy permissions before connecting.
Summaries and answers
Returning passages is cheaper than generating summaries or answers, which add AI usage and testing for accuracy. Consider adding summaries once the search itself proves useful.
Judging the value
Estimate time spent searching today and ask pilot users how much faster they find what they need. Count reused work, such as past reports or clauses found instead of rewritten.
Number of stores
Each document store, such as a shared drive, a cloud folder or a document management system, needs a connection, a way to read permissions and a refresh process. Connecting one store is much simpler than five. Start with the store people search most and add others once the search proves useful.
Testing
Relevance testing with real searches and permission testing with accounts in different roles take time from the provider and your staff. They show whether results are useful and safe, so keep them in the budget.
Search interface
A simple search page costs less than embedding search into an intranet, a document management system or a messaging tool. Price the option that matches where people already work.
Data protection work
Reviewing which folders contain personal data, preparing a data protection impact assessment, which ICO guidance says AI use usually requires, and checking supplier terms add time and possibly adviser fees.
Filters and metadata
Capturing details such as client, project and date during indexing makes filters possible. Where those details already exist in folder structures or a document system, this is cheap; where they must be extracted from document text, it adds work.
Support
Indexing jobs can fail and permissions change. A support arrangement or agreed hourly rate keeps the search reliable after launch.
Questions about AI document search development cost
What affects AI document search cost?
File volume and condition, stores, permissions, summaries and refresh.
Do scans cost more?
Yes, they need text recognition and checking.
What are the ongoing fees for document search?
Index hosting, search processing and re-indexing.
Can it be phased?
Yes, by store or archive period.
Are summaries extra?
They add AI usage and testing.
How do we measure the benefit of document search?
Time saved searching and work reused.
Request a Custom Quote
Ask about AI document search development cost
Thank you — your enquiry has been sent.
We have received your message and will reply by email. If you need to add anything, email info@letgetgrow.com.