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We build AI you are allowed to deploy

Blue Mesh is governed AI infrastructure. Autonomous agents, voice agents, and retrieval run inside the environment you already control, authenticated on the way in and logged on the way out, which is what makes them approvable in a bank, a hospital, or a network operations center. This page covers where the company came from, what it builds, and what it does not claim.

governed AI infrastructureruns in your environmentbecoming a separate company
01
Where this came from

Built inside Netstratum. Becoming its own company

Blue Mesh was built inside Netstratum Inc., which needed governed AI infrastructure before there was any it could buy, and it is now being established as a separate company. Netstratum has become a customer rather than a parent: it runs the platform the way any other customer runs it, and it appears on the customer list for that reason and no other. While the separation is in progress the Terms of Service still name Netstratum Inc. as the provider of the Service, and that document governs, not this paragraph. No date, no funding announcement and no headcount are published here, because none of them is settled, and a company page is a poor place to guess.

  • Built inside Netstratum Inc., and now being established as a separate company
  • Netstratum runs the platform as a customer, not as a parent
  • The platform, not the paperwork, is the part with a record behind it
02
What we build

Four modules, and you operate all four

Blue Mesh is not an endpoint you call. It is infrastructure you stand up: somewhere to design agents, a way to have them written for you, a way to train models that stay yours, and a box that can sit in a room with no internet in it.

BM Studio

Design it visually. Build and orchestrate agents on a drag-and-drop canvas, wired to the 300+ systems and tools your team already runs, so the people who understand the process are the ones assembling it.

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BM Architect

Turn ideas into code. Describe a workflow in plain language and Blue Mesh designs, tests, and deploys it, which takes the first draft off the queue that only your engineers can clear.

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BM Oasis

Train private models. Fine-tune on your own data and keep the weights inside the boundary they were trained in. That is the clause that decides whether an AI programme becomes an asset you hold or a rental you renew.

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BM in a Box

A ready-to-run appliance. The platform arrives pre-configured on NVIDIA DGX hardware, fully air-gapped, so for data that genuinely cannot leave, the deployment is a delivery rather than a connection.

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03
What it does

Three capabilities, one governed runtime

The modules are what you operate. These are what runs inside them, and each one is the same bargain in a different medium: the work happens on your side of the boundary and leaves a record behind it.

Agentic AI

Reason, plan, act. A Leader Agent decomposes each task and directs specialist sub-agents end to end, with no manual handoff between steps.

Voice agents

Listen, speak, act. Low-latency real-time voice over SIP, running on your own models rather than a public endpoint, so audio and transcript stay where your call data sits.

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Enterprise RAG

Retrieve, ground, cite. Answers are sourced from your indexed data with the citation attached, so a reviewer can check where a sentence came from.

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04
How we work

Four decisions that settle the architecture

These are not values on a wall. Each one closes off a design option that would have been easier, and together they are why the product looks the way it does.

Your environment, not ours

Private cloud, on-premises, or fully air-gapped. Building for the strictest of the three first means the looser two are subsets rather than rewrites, and it means we never have to ask you to move data to make the demo work.

A record, not a recollection

Every decision and result is logged for compliance audit: what ran, what it read, what it did, who approved it. When someone asks what the system did and why, the answer is retrieved rather than reconstructed from memory.

A person on the consequential steps

Actions that carry consequence pause for a person before they execute, at thresholds you configure. Most serious platforms have an approval gate now, so the honest comparison is how finely it can be scoped, and here that is per action and per workflow.

Controls with names

Role-based access, encryption in transit and at rest, and an audit trail on every decision. Named controls survive a security questionnaire; adjectives about how secure something is do not, and we would rather be checkable than reassuring.

05
One boundary

What this is not

Blue Mesh is not a hosted service with a sign-up form. There is no self-serve tier, and there is no version of this that does anything useful without an environment to deploy into and someone on your side who owns it. If what you want is AI running in a browser tab this afternoon, several good products do that and this is not one of them. The trade is deliberate and it runs both ways: the reason it takes a conversation to begin is the same reason it can run somewhere the internet cannot reach.

Where to look next
  • Trust and security The governance story in full: three deployment modes, the controls by name, and a plain list of what we do not claim.
  • Customers The organizations named publicly, and the one deployment described end to end: AI phone companionship running on a Blue Mesh voice agent.
  • How we compare Fifty platforms read from published sources, with the questions worth putting to every vendor on a shortlist, including us.
// about

Two questions settle most of this

Where is your data allowed to sit, and what has to be on the record when an agent acts on it? Bring those two answers and we can tell you which deployment mode you actually need, including the case where the answer is that you do not need us yet.

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