/ Services / Local AI

Local AI for teams that can't ship data out.

For healthcare, legal, and finance clients who cannot send records to a third-party API. Open-weight models on infrastructure you control, grounded in your own documents, with the audit and access logs your compliance people will ask for.

Talk through your case → All services
/ What's included

Your data stays put.

The model, the document index, and every query run inside your boundary. Nothing is sent to a hosted API.

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Open-weight models, your hardware

We deploy Llama, Mistral, or Qwen on infrastructure you control: your own servers, or a private cloud tenancy you own. The model weights and the inference run inside your network boundary. No prompts, no documents, and no embeddings leave to a third-party API.

Llama / Mistral / Qwen
On-prem or private cloud
Inside your network boundary
No third-party API calls
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RAG over your documents

Retrieval-augmented generation grounded in your own files: policies, records, contracts, knowledge base. Answers are pulled from your documents and cite where they came from, so staff can check the source instead of trusting a black box.

Private vector index
Answers cite their source
Scoped to your corpus
No public training data leakage
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Wired into systems you run

The deployment connects to the tools you already use rather than living in a separate tab. Internal search, a support inbox, an intake form, a line-of-business app. We build the integration against your existing stack so it fits the workflow your team already has.

Connects to existing tools
Internal search or intake
API for your own apps
No rip-and-replace
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Audit and access logs

Every query, document retrieval, and response is logged with the user, the timestamp, and the sources used. Access is role-based. When your compliance officer or auditor asks who saw what and when, you have a record instead of a shrug.

Per-user query logs
Role-based access
Retrieval and source trail
Exportable for audit
/ Who it's for

Regulated operators, not everyone.

If a vendor data breach or an off-network prompt is a regulatory problem for you, this is built for you.

Healthcare

Ontario clinics

Clinics, practices, and health teams handling patient records under PHIPA who cannot route data through OpenAI or Anthropic. Drafting, summarizing, and search over charts stays on infrastructure you control.

  • PHIPA-aligned controls
  • Records never leave your boundary
  • Per-user access and logs
Legal

Firms and in-house

Practices bound by privilege and confidentiality that need search and drafting over matter files without those files touching a third-party model or its training data.

  • Privilege stays intact
  • Grounded in your matter files
  • Answers cite their source
Finance

Regulated finance

Teams handling client financial data under contractual or regulatory data-residency rules that forbid sending it to a hosted API. The model and the data sit on infrastructure you own.

  • Data residency respected
  • On-prem or private cloud
  • Exportable audit trail
/ Straight talk

When you do and don't need this.

Most businesses: skip it

Let's be clear up front. Most businesses do not need local AI. If your data is not regulated and you are comfortable with a vendor's data-processing terms, a hosted API like OpenAI or Anthropic is cheaper, faster to set up, and usually a stronger model than anything you would self-host. We will say so on the call rather than sell you hardware you do not need.

Local AI earns its cost in a narrow set of cases: a compliance regime or contract that forbids sending data to a third party, strict data-residency rules, or a genuine reason this data must never leave your network. That is healthcare, legal, and finance more often than not. If that is you, the trade-offs are worth it. If it is not, we would rather point you at the simpler option.

Get an honest read →
/ Related reading

The thinking behind it.

We have written up the trade-offs in detail. Worth a read before you decide.

/ Blog

Why local AI matters

What local AI deployment actually means for a regulated business, and the problems it solves that a hosted API cannot.
/ Blog

When local LLMs win

The specific cases where a self-hosted open-weight model beats a cloud API, and the larger set of cases where it does not.
/ Blog

Self-hosted LLM TCO

The real total cost of running your own model in 2026: GPUs, power, and maintenance versus a per-token API bill.
/ Blog

PHIPA-compliant AI

How Ontario clinics can use AI over patient data while staying inside PHIPA, and where the technical line sits.
/ Common questions

FAQ.

Does our data ever leave our infrastructure?
No. The whole point of this build is that the model, the document index, and the inference all run on hardware you control, either on-prem or in a private cloud tenancy you own. Prompts, retrieved documents, and embeddings stay inside your network boundary. There are no calls to OpenAI, Anthropic, or any other hosted API at inference time.
Which models do you deploy, and are they any good?
Open-weight models: Llama, Mistral, and Qwen, sized to your hardware and your task. For grounded question-answering over your own documents, a mid-size open model with good RAG usually does the job. For open-ended reasoning at the frontier, a hosted API is still ahead, and we will tell you plainly if your use case is one of those rather than sell you a local box that underperforms.
What does this cost to run?
Honest answer: it depends on hardware, model size, and how many people hit it. Self-hosting trades a per-token API bill for fixed costs in GPUs, power, and maintenance, so it makes sense at steady volume or when compliance rules out the cloud, and it makes less sense for light or spiky usage. We write up the trade-off for your specific case before you commit. We do not publish a flat price because a number with no context would be misleading.
Is this PHIPA or compliance friendly?
Keeping patient or client data on infrastructure you control, with access controls and audit logs, lines up with how regulated operators are expected to handle sensitive records under PHIPA and similar regimes. We build the technical controls: data stays in your boundary, access is role-based, and queries are logged. We are developers, not your lawyers or your privacy officer, so the final compliance sign-off is theirs to give.
Can you maintain it after it goes live?
Yes, on a monthly retainer. Model updates, security patches on the host, index refreshes as your documents change, and tuning as usage grows. You can also take the whole thing in-house: you own the deployment, the configuration, and the runbooks, and nothing is locked behind our infrastructure.
● connect@aurabyt.com

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