Insights

Notes from the wrong side of the data-residency wall.

Practical writing on sovereign AI, retrieval that holds up under audit, marketplace procurement and what actually stops enterprise AI reaching production. No thought leadership for its own sake.

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AI costResearch note

What an answer costs: how K-Lake reduces the tokens an assistant spends

Four retrieval approaches, the same files and the same questions. How many tokens each one put into the conversation, what that means for an AI budget, and the limits of the test.

Read the research note

"The assistant searched widely and read narrowly. 99.3% of what K-Lake found stayed on disk."
From the research note
Procurement

What a CISO actually asks in an AI security review

The questions that stall AI pilots at the security review, from how many copies of your documents will exist to whether you can switch it off, and how K-Lake answers each one.

Retrieval

Citations are the audit trail

Why grounded retrieval with source links is what makes an AI answer defensible to a regulator, and what to ask any vendor about it.

What we write about

Four themes, and nothing else

We write where we have something specific to say. If a topic does not sit under one of these, it does not belong here.

01

Sovereign and regulated AI

Data residency, air-gapped deployment, and building AI into environments that cannot send data out.

02

Retrieval that holds up

Grounding, permission-aware access, citations, and why keyword search alone keeps failing enterprise users.

03

Procurement and security review

What stalls enterprise AI deals, how to prepare for the questionnaire, and marketplace and MACC mechanics.

04

Regulation in practice

DORA, the EU AI Act, NHS data governance and what they mean operationally rather than theoretically.

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