AI workers Deployment Security Trust Questions Book a briefing

Own your intelligence. Stop renting it.

OwnIQ deploys open-weight AI models on your own infrastructure, fine-tuned on your decision history. The model carries your institutional judgment, gets better every month, and your confidential material never leaves your control.

Book a briefing See AI at work
  • On-prem, your colo, or your cloud account
  • Air-gap ready
  • Pinned, versioned releases you approve
2 similar past batches found
Secret recipe never left the building
A new way to use AI

Stop using AI as an assistant. Put it to work.

Cloud assistants only ever see what's safe to share, so they help with the easy stuff. OwnIQ runs on your own hardware, so you can finally hand AI your most sensitive work: the secret recipes, client files and big decisions that actually matter.

AI as an assistant
  • Only sees what's safe to share
  • Gives generic suggestions
  • You still do the real work
AI as a worker
  • Sees everything, safely, on your hardware
  • Does the job using your own past decisions
  • You review and sign off
The problem

Your most valuable work is too sensitive for OpenAI, Anthropic or Gemini.

Secret recipes, formulas, ten years of hard-won decisions and your clients' IP can't be pasted into a cloud chatbot. So your team either does the important work without AI, or quietly pastes it in and hopes for the best.

What a cloud model gets

Leaves your network
Prompt, after redaction Here's our secret cola recipe: 4.2 g vanilla from Supplier B, 1.8 g lime oil and 0.6 g cinnamon per litre. Customers say the latest batch tastes different. What changed?

Changes in taste can have many causes, such as ingredient quality, supplier changes, storage conditions or measuring errors. Try comparing the new batch with an older one and reviewing any recent changes to your process.

GenericHedgedNo precedentCan't see your history

What your OwnIQ model gets

Stays on your hardware
Prompt, whole Here's our secret cola recipe: 4.2 g vanilla from Supplier B, 1.8 g lime oil and 0.6 g cinnamon per litre. Customers say the latest batch tastes different. What changed?

The vanilla changed. Supplier B's vanilla is about 15% stronger, so the same 4.2 g now tastes like more. Your batch notes show this exact complaint in 2023 and 2025. Cut vanilla to 3.6 g per litre and run a blind taste test before the next batch ships.

SpecificCitedCommits to a callYour house rules

Redaction removes exactly the figures the answer depends on. The hard work has to run where the data lives.

Why own it

A model that knows how your firm decides.

Generic models summarize your files. Yours reaches your house call: it ranks your sources, commits to a recommendation and applies the unwritten rules your senior people follow.

01 / Control

Confidential material goes in whole.

Your data, weights and logs stay on hardware you control. No inbound internet, an allow-listed outbound proxy, and every byte that does leave is logged. If you want, nothing leaves at all.

Documents indexed2.4M
Questions answered today18,240
Bytes sent to any AI vendor0
Weights, datasets and audit log held on-site
02 / Better

Measured on your work, not a leaderboard.

Every release faces your own eval suite: real tasks scored against your experts' answers, and "does it reach the decision your team actually made" on cases it has never seen.

Deviation drafting66% win
CAPA proposals63% win
SOP and spec search58% win
Your model winsTiePrevious model wins
03 / Cost

Cheaper at scale.

Frontier-tier tokens carry big margins. Get comparable quality on hardware you own, with house rules baked into the weights so every prompt is shorter.

Frontier API
$224K
Flash-tier API
$173K
OwnIQ on-site
$49K
Monthly, 5,000-person enterprise with agents. Infra only, illustrative.
04 / Compounds

Better every month.

Every edit becomes a preference pair, an eval case and training data. Improvements ship as tested, versioned releases you approve.

v9v14 76% accuracy
05 / Portable

Keep everything when models improve.

The real asset is your eval suite and mined dataset. When better open weights ship, we re-base onto them and switch only if they win.

Base A2026
→
Base B2027
→
Carried over every timeDataset + eval suite
Deployment

Your cloud, your building, or both.

Start in your own cloud account in week one, then move onto dedicated hardware when it arrives. The same platform runs everywhere.

OwnIQ Platform

Runs in your AWS, Azure or GCP account.

  • Permission-aware search with citations
  • Decision mining, fine-tuning and evals
  • Monthly releases through your release gate
  • Web, Teams, Word and an OpenAI-compatible API

Best for pilots, and teams under about 1,000 people.

OwnIQ Appliance

Runs on hardware in your building or colo.

  • From one server to a full rack
  • No inbound internet, air-gap ready
  • Idle night-time GPU hours used for training
  • OEM on-site parts, remote support you approve

Best for confidential and high-volume workloads.

Most value

OwnIQ Complete

Platform and Appliance, fully managed.

  • Pilot in your cloud from week one
  • Move onto your hardware when it lands
  • Monitoring, patching, retraining and SLAs
  • Everything in Platform and Appliance

Best for regulated enterprises who want it handled end to end.

The platform is a subscription. Hardware can be bought, leased over 36 months, or provided as a service. Every quote includes three numbers: all-in monthly cost, cost per active user, and your break-even against your current API spend.

Get your three numbers
Security

Your data stays put. Every answer is accounted for.

Built for security teams who assume everything will be probed, and for auditors who want to see why the model said what it said.

Data stays under your control.Customer content never leaves your environment.
No standing access.You approve every support session.
You own the weights.And the dataset and evals that made them.
Nothing changes silently.Pinned versions, released with your sign-off.

Want the architecture, data flows and controls in detail? Our trust page covers deployment, the threat model and what your security team will ask.

Visit the trust page
Live briefing, 30 minutes

See your own judgment in a model.

We take on a handful of design partners at a time, and build each deployment by hand. Tell us where the pain is and we'll show you what OwnIQ would do with it.

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Questions

What buyers ask us first.

Something else? Ask us directly.

Does any of our data leave the building?

Not by default. The system has no inbound internet access, and outbound traffic goes through an allow-listed proxy where every request is logged. If your data lives in SaaS tools like Microsoft 365, our connectors reach your own tenant, which we explain to your security team up front. Fully air-gapped is available.

Why not just use a cloud AI service inside our own tenant?

You'd still be renting the model. You can't train it on your judgment the way we do, you can't take it with you, the vendor retires versions on its own schedule, and you pay per token forever. And your most confidential material often still can't go in whole.

How do we know it's actually better?

Your own eval suite: real tasks scored against your experts' answers, plus "does it reach the decision your team made" on past cases it has never seen. Every release has to beat the current one, with enough cases to be statistically meaningful, before it ships.

Can people see information they shouldn't through the AI?

Search enforces the permissions from each source system at the moment someone asks. Models are only trained on data every one of their users is allowed to see, and highly sensitive facts are never trained in at all. We prove it by planting unique canary strings in restricted data and testing every release.

Is it cheaper than what we pay for AI today?

At volume, usually by a lot, especially against frontier-tier pricing and agent-heavy workloads. For light use, the cheapest APIs can beat any hardware, and we'll tell you so. If confidentiality rules out external APIs entirely, the real comparison is OwnIQ versus not using AI on your best data.

How long until it's live?

A pilot runs in your own cloud account within weeks. Dedicated hardware is typically live two to three months after order, depending on lead times, and the first fine-tuned release follows four to six weeks later.