aisol/solutions/archive search (RAG)
solution 2 / 8

AI search across corporate documents and internal archives

Semantic search across millions of pages of corporate documents — including scanned ones. The system understands the meaning of a query rather than matching keywords. An answer in 30 seconds instead of hours of manual searching.

For whom: the quasi-government sector, oil and gas, law firms, banks, insurers — any organization with an archive of 50,000 pages or more. Built on AWS Bedrock + a vector database; data stays in Kazakhtelecom Cloud or on-premise.

archive search30 sec
“permit for a hazardous facility”semantic query
Regulation No. 47-VNpp. 12–14 · 3 requirementssource
Letter from the Ministry of Ecology08.02.2024 · Legal Dept. archivescan · OCR
an answer with a link to the source · across 1.2M pages
problems

What happens without a system

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Finding the right document or standard takes anywhere from 30 minutes to several hours — an employee browses through folders by hand.

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Employees duplicate work: they don't know that a similar project has already been done and the solution is in the archive.

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Scanned documents are not indexed by Windows/SharePoint search — searching through them is physically impossible.

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When an employee leaves, the knowledge leaves with them — there is no structured access to their materials.

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Legal and technical standards are “buried” in volumes of documentation — finding a specific clause by hand is unrealistic.

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Different employees answer the same client question differently — interpreting documents from memory.

pilot benchmarks

We set target metrics before the start

We agree on the metrics with you before work begins. If we don't reach them, we keep working until we do or refund the money proportionally.

up to 80%reduction in search time — a benchmark from comparable RAG deployments
all formatstext-based PDF, DOCX, Excel and scanned materials
from 30 secaverage response time per query
AWS Bedrockinfrastructure with no limits on archive size
system components

How corporate AI search works

Semantic search

Understands the meaning of a query, not keywords. “How do I obtain a permit for a hazardous facility?” — finds all relevant standards across different documents.

Filters and categorization

Search by document type, date, department, project, author. Narrow the results in seconds.

OCR for scans

Recognizes text from scanned PDFs and photos. Honestly reports the OCR accuracy for each material.

Integration with storage

SharePoint, Google Drive, 1C, Confluence, file servers. No data migration required.

Multilingual support

Kazakh, Russian, English. A search in one language finds documents in another.

Version comparison

Shows what changed between two versions of a document. Critical for regulations and contracts.

Source with page reference

Every answer comes with a link to the document and the page number. The employee sees the original source.

Role-based access

Everyone sees only what they have rights to. The archive stays secure even with broad access.

example scenario

Examples of queries to the system

QuestionWhat are the documentation requirements for a nature-use permit according to our internal regulations?
SystemUnder Regulation No. 47-VN of 2023 (pp. 12–14), the following are required: a site survey report, an environmental assessment, and approval from the local executive authority. A related requirement is the letter from the Ministry of Ecology dated 08.02.2024 (found in the Legal Dept. archive). Show both documents?
QuestionDid we have a contract with KazStroyMontazh, and on what terms?
SystemFound 3 contracts: from 2019, 2021 and 2023. The latest is a contract for equipment installation, 48 million tenge, an 8-month term, closed with a signed acceptance act. Open the document?
frequently asked questions

What you should know

There are no technical limits on size — we use AWS Bedrock. We select the specific configuration for your volume during the technical assessment stage.
The system inherits access rights from your corporate storage. If an employee does not have access to a file, they will not see it through search.
OCR works even with low quality. For each document we show a recognition-quality score; when accuracy is low, we flag it and recommend rescanning.
It depends on the volume. A typical archive of 100,000 documents takes 3–5 business days for initial indexing. New documents are added automatically.
Yes. On-premise deployment on the client's servers with a local model is available. Data does not leave the company's perimeter.

Ready to enable search across your archive?

We'll run a test on 1,000 of your documents — within 2 business days we'll show the search quality on your data. The pilot runs 4–6 weeks, and we'll measure the result together.