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

Assistants that answer from company files

For knowledge, operations and IT teams

Copilot, Claude, ChatGPT or an agent of your own answers from policies, contracts, reports and correspondence without a data export. The assistant connects as the individual user, sees only what that user could already open, and every fact carries a citation back to the original.

Outcome that mattersHours a week returned to the people who search for documents, answers that carry their own evidence, and an AI rollout that passes the access-control review.

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

Contract and counterparty intelligence

For legal, procurement and finance

The knowledge graph reads every extracted agreement and records the people, organisations and agreements it names and the relationships between them. Which agreements renew this quarter, who signed them, which counterparties share an adviser, which files put the same three people in the same room.

Outcome that mattersRenewal and obligation dates surfaced before they lapse, counterparty exposure visible across every agreement, and diligence answered with a list of files rather than a week of reading.

USE CASE 04

Know the estate before you classify, migrate or clean it

For data governance, security and storage teams

Discover turns what K-Lake has already crawled into a live estate overview: totals, how much is searchable, composition by type, language, size, age, owner and source, and exposure signals for world-readable, stale, unowned and duplicated files, with the actual files listed behind every number.

Outcome that mattersA defensible, repeatable baseline for governance programmes, redundant and obsolete data identified with its owners, and exposure reduced before an assistant is ever connected.

USE CASE 05

Grounded AI where the data cannot leave

For defence, public sector, financial services and healthcare

Classified material, patient records, regulated financial data, or a network with no route to the internet. K-Lake runs entirely inside your cluster. Extraction, OCR and transcription run on engines you host, licensing is validated offline, and in air-gapped mode a self-hosted model answers over MCP with the same per-file trimming and the same audit trail.

Outcome that mattersAI retrieval inside the boundary with zero egress, a security posture reviewers can verify rather than read, and no diminished experience for disconnected sites.

USE CASE 06

Searchable audio and video archives

For media, training, research and investigations teams

Recorded meetings, training sessions, interviews and hearings are transcribed on self-hosted models, with on-screen text read for video. Every segment is timecoded, so a search hit opens the player at the exact moment.

Outcome that mattersHours of recordings searched in seconds, hits that open at the exact timecode, and an assistant that can cite the minute something was said.

USE CASE 07

Governed AI for many customers on one deployment

For managed service providers and platform vendors

Every source, user, token and file belongs to exactly one tenant, isolated by row-level security below the application. Each tenant gets its own MCP endpoint and can federate to its own identity provider, and licences can carry a product name for white-label deployments.

Outcome that mattersPer-customer AI without per-customer infrastructure, isolation you can explain to a customer’s security team in a sentence, and marketplace-ready licensing.

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