Question 1

What is private inference?

Accepted Answer

Private inference runs AI models inside a dedicated environment you control — never a shared, public model API — so regulated or confidential data is never sent to a third-party model provider. A fail-closed gateway refuses any request that can't be served inside your boundary.

Question 2

How does Miko keep our data isolated?

Accepted Answer

Your workload runs in a single-tenant dedicated environment with customer-held encryption keys, and we run open-weight models ourselves — so your data never reaches a third-party model provider like OpenAI or Anthropic. Every request is attested before inference, producing an auditable record of data class and route.

Question 3

How do we adopt AI without sending data to the cloud?

Accepted Answer

Adoption doesn't require sending anything to a public model API. Models are self-hosted on single-tenant dedicated infrastructure (open-weight, no public model API), a pre-inference gateway classifies and routes every request, and anything that can't be served inside your boundary is refused rather than forwarded — zero egress by architecture.

Question 4

Why managed delivery instead of building it in-house?

Accepted Answer

An in-house build means hiring an ML team, standing up infrastructure, and maintaining models indefinitely. Miko Labs runs the system as a managed service: finished work arrives in your existing workflow, there's no tool to operate, and the system gets sharper as it learns your organization.

Question 5

Do you only work with regulated industries?

Accepted Answer

No. We started where the stakes were highest — legal, title, escrow, veterans benefits — because if AI can be trusted with privileged files, it can be trusted with your operation. The same managed-delivery model works for any business with document-heavy, repeatable work that drains a team's day.

Question 6

Is this consulting, or do you actually run it?

Accepted Answer

We run it. There's no deck and no demo theatre — Miko builds the system, operates it, and delivers finished work into the tools your team already uses. You review and sign off; you don't operate software or manage a model.

Question 7

How is this different from AI governance platforms?

Accepted Answer

Governance platforms add policy and monitoring on top of cloud model APIs — your data still leaves your perimeter and you trust a policy to protect it. Miko Labs makes egress structurally impossible: inference is private by architecture — self-hosted open-weight models with no third-party model provider in the chain, and the system fails closed when it can't serve a request privately.

Question 8

Are you SOC 2 or HIPAA certified?

Accepted Answer

Formal certification is in progress. The architecture is built to meet SOC 2, ISO 27001, HIPAA / HITECH, and in-region residency from the start, and we will walk your security team through the controls, our current status, and a DPA or BAA under NDA.

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