360 Labs builds AI that runs on your own computers. Your files, records and questions stay inside your company and never go to an outside AI firm.

We do 3 things. We take public AI models that anyone can download and train them to be very good at one job. We build small AI models from scratch when a client needs one that's fully theirs. And we build the apps your staff use every day to work with those models. We're a team of 20+ AI engineers, and we've set up 30+ of these systems in India, the UK, the Gulf (GCC) and the US.

We're a research lab, so the people who build your system also build and study AI models. We've published 10+ research papers. Large IT firms mostly supply people to work on your project, and they often spend months on planning before anything gets built.

This matters because private AI is hard to get right. Fitting a model onto one Mac Studio in a fund's office, or onto a small computer next to a factory camera, takes people who know how models work inside. We usually show you a working first version within days, and full systems go live in weeks.

Private AI is AI that runs on computers you control. Your files, records and questions never leave your company.

Most AI works another way. When you use a tool like ChatGPT, your data travels over the internet to the company that runs it. Their computers work out the answer and send it back. With private AI, the model sits in your own server room, your own private cloud account, your office or a device in your hand.

It's like owning a printer instead of sending your files to a print shop. You get the same pages, and your files never leave the building.

No. In a private setup, the models run on your own computers and no outside AI company is involved. No file, record or question leaves your network. If you ever want a cloud model for one task, we connect it with your own account and keys, and only for that task.

Those plans work well for everyday tasks, and many companies should use them. But your data still goes to the provider's computers to be processed. A bank, hospital, law firm or government team often can't allow that for its most useful data, such as customer records, patient notes and legal files. Private AI lets you use AI on exactly that data. You also own what you build, and no other company can raise the price on you.

For one specific job, often yes. A big model like GPT knows a little about everything. We take an open model, which is one anyone can download and run, and train it hard on one task, like reading your leases or answering questions about your sales data. A model trained this way can match or beat a big one at that task.

One public test shows this. Spider 2.0-Lite is a contest for turning plain-English questions into database searches. Our model, Omni 1.0, came 5th, and it scored higher than every entry built on Claude, GPT or Gemini.

The biggest cloud models are still better at broad work, like writing about any topic. So we pick the model that fits the job.

Often less than you'd expect, and it depends on the job. A Mac Mini can run a full data system for one factory. A Mac Studio runs the AI for a $150M venture fund. Camera systems use small computers like the NVIDIA Jetson Orin, or a server with an RTX 4090 graphics card. Big systems used across a whole company run on GPU servers or NVIDIA DGX machines.

We work out the right hardware with you before we start. If you'd rather not buy anything, you can rent machines from us that only you use.

You do. The models we train on your data belong to you, and so do the code and everything around them. We never use your data to train models for anyone else.

We build checks into every system, so it's hard for the AI to make something up without anyone noticing.

• Every answer shows where it came from.
• If a source can't be found in a real document, the system removes it and tells you.
• Numbers like forecasts, totals and quantities come from fixed maths, and the AI only explains them.
• When the AI wants to change a record, a person must approve it first, and the system logs who approved what.

In one legal tool, every answer in a review table links to the passage it came from. The one source that couldn't be traced was removed and flagged.

Yes, and most projects start this way. We look at how your teams work and find the tasks where AI would save the most time or money. Then we check where your data is kept, what must stay inside your company, and what model and hardware each task needs.

You get a plan. It says what to build first, how much it will cost to run, and whether to buy computers or rent them from us. It also tells you where a ready-made tool would do the job, so you don't pay us to build something you could buy. We can also help you set rules for how your company uses AI, such as who signs off on what it does.

Our projects start at $20,000, and large systems go above $100,000. The price depends on what you need built, and you'll know it before work starts.

Hardware is extra. Some systems run on one Mac Mini, and others need GPU servers. You can buy the hardware or rent machines from us. Once the system is running, you pay for the machines, and there's no fee per question that someone else can raise.

Yes, and we suggest it. A pilot means we pick one task, run it on your real data and show you the results. If it works, we move to the next task. Your team gets to judge the system on your own documents before you commit to anything bigger.

To get started, book a 30-minute call with one of our engineers on the contact page, or email us at ceo@360labs.ai. You'll get a proposal within 48 hours.