Use cases

Same index. Very different questions.

K-Lake crawls, extracts and enriches your files once. What people then ask of it depends on who they are. These are the seven starting points we see most often, with the outcome each one delivers, all on data that never leaves your environment.

+62%

Demonstrable patterns, not promises

The same building blocks, grounded retrieval, permission trimming and citation, drop into any regulated customer. Each is demonstrable on representative data, or on your own, behind your firewall. Not on the list? It probably still fits: tell us what you hold and what you want to ask of it.

USE CASE 01

Your policies and procedures, answered with sources

For compliance, operations and IT teams

Staff ask Copilot, Claude, ChatGPT or Gemini and get an answer drawn from your own policies, procedures and reports, with a link to the page it came from. Nothing is exported to build it. The assistant signs in as the person asking and sees only the files that person could already open.

Outcome that mattersTime back for the people who search for documents, and an AI rollout that passes access review because the controls are the ones you already run.

USE CASE 02

KYC, AML and investigations

For financial services and investigations teams

Identity documents, contracts, prior records, related accounts, transaction narratives and connected parties pulled from siloed shares into one grounded, cited pack, trimmed to what each investigator may already see.

Outcome that mattersReview packs in minutes rather than hours. Investigators spend their time deciding, not hunting, and every fact is traceable for the audit trail.

USE CASE 03

Every obligation in your contract estate, found before it bites

For legal, procurement and finance

Renewal dates, notice periods and obligations surface from the agreements you already hold, across shares and SharePoint. Ask which contracts involve a counterparty, who signed them and what they commit you to. The knowledge graph keeps relationships an agreement actually states separate from names that simply appear together.

Outcome that mattersNo renewal missed for want of reading, and diligence questions answered with the documents that prove the answer.

USE CASE 04

A defensible baseline before you classify, migrate or clean up

For data governance, security and storage teams

Before a records programme or a migration, Discover measures what you actually hold from the index K-Lake has already built. It shows what is stale, duplicated, unowned or open to everyone, where it sits and who owns it, and every number links to the files behind it.

Outcome that mattersExposure fixed before an assistant is ever connected, which is the order a regulator would expect to see.

USE CASE 05

AI for the data that is never allowed to leave

For defence, public sector, financial services and healthcare

Retrieval, indexing and permission checks run entirely inside your boundary, with extraction, OCR and transcription on engines you host. Licensing is validated offline. Pair K-Lake with a local model and nothing crosses at all, including on sites with no internet connection.

Outcome that mattersA security posture your reviewers can test for themselves, with the same experience on a disconnected site as on a connected one.

USE CASE 06

Recordings you can search by what was said

For training, research, media and investigations teams

Calls, interviews, hearings and training video are transcribed on self-hosted models and indexed alongside your documents. Text shown on screen is searchable too, and every result opens at the moment the words were spoken.

Outcome that mattersAn assistant that can cite the minute a statement was made, instead of someone replaying hours of recordings to find it.

USE CASE 07

One deployment, many customers, each kept apart

For managed service providers and platform partners

Offer each of your customers governed AI over their own data without building separate infrastructure for each. Every source, user and file belongs to exactly one tenant, isolated in the database. Each tenant gets its own MCP endpoint and identity provider, and licensing supports your own branding.

Outcome that mattersIsolation simple enough to explain to a customer’s security team in one sentence, with licensing ready for marketplace sale.

USE CASE 08

Know what is sensitive before an AI sees it

For CISOs, data protection officers and information governance teams

K-Lake classifies every file it indexes as public, internal, confidential or restricted, and shows the evidence behind each label. Rules then decide what search and AI may return, enforced in the data layer rather than in the assistant.

Outcome that mattersA DPO who can show exactly which restricted content an assistant is able to reach, and prove that the answer is none.

How the security story actually works

K-Lake keeps the document estate, index and permission enforcement inside the customer's environment. Pointed at a cloud model such as Copilot, only the specific retrieved, permission-checked snippet is sent, under the customer's own agreement with that vendor. For fully sovereign cases, K-Lake runs air-gapped against a local model, demonstrated with the internet physically switched off.

By industry

Where the residency wall is highest

Five sectors combine the strongest regulatory pressure, the largest document estates and the most urgent pressure to show AI results.

Tier 1 · highest priority

Financial services and banking

DORA, MiFID II and FCA rules constrain sending client data to external AI services.
Analysts spend hours searching annual reports, fund prospectuses and credit files.
The largest vertical by AI knowledge-management spend.

"We cannot send client files to ChatGPT, but our analysts are three times slower than peers who use AI."

Tier 1 · highest priority

Legal and professional services

Client confidentiality and legal professional privilege make cloud AI a non-starter for matter data.
Dense estates of contracts, case files and precedents benefit most from semantic retrieval.
High time-cost of manual review makes the return visible in billable hours saved.

"We know AI could halve document review time, but privilege means nothing leaves our servers."

Tier 1 · high priority

Healthcare and life sciences

HIPAA, NHS data governance and GDPR require patient data to remain on controlled infrastructure.
Clinicians and researchers need fast access to protocols, guidelines and trial data.
Self-hosted deployment removes the vendor data-processing exposure entirely.

"Our researchers spend a fifth of their time hunting for internal trial data that already exists."

Tier 2 · strong opportunity

Government and public sector

Public bodies are constrained from externalising classified or sensitive citizen data.
Ageing legacy file-share estates make retrieval slow and unreliable.
Self-hosted is the lower-risk path under EU AI Act high-risk classification.

"We have decades of policy documents but our people cannot find what they need."

Tier 2 · specialist, high value

Defence, aerospace and critical infrastructure

ITAR, CMMC and NATO STANAG requirements make air-gapped operation mandatory, not optional.
K-Lake has been demonstrated operating with the internet physically disconnected.
Large technical documentation estates (manuals, specifications, maintenance logs) benefit enormously from semantic search.

"Our maintenance engineers spend hours searching technical manuals that can never touch the internet."

On the numbers. The FinanceBench figure is an independent benchmark on public SEC 10-K and 10-Q filings. The retrieval-quality figure is internal benchmarking; methodology available on request. Workflow outcomes on this page are illustrative of the value pattern and are not guaranteed results. Any accuracy claim for your organisation should come from a proof-of-concept on your own documents.

Start here

Pick a use case. We will prove it on your data.

A working proof-of-concept on your infrastructure, using your documents, behind your firewall. Most are answering real questions within the first week.

Try it on your data Or email [email protected] See the platform