Private
Your data stays within your environment.
On-device intelligence · noiot.ai
AI That
Never Leaves.
Private. On-Device. Intelligent.
The next generation of AI doesn't need to live in the cloud.
No IOT builds intelligent systems that run directly on your devices and private infrastructure, keeping your conversations, knowledge, workflows and data where they belong.
With you.
Be among the first to experience private, on-device AI.
$0M
Global average cost of a single data breach.
IBM · 2025 [1]
$0M
Healthcare average, the costliest sector of any industry.
IBM · 2025 [1]
0%
Of employees paste company data into generative AI prompts.
LayerX · 2025 [3]
0
Packets that leave the device when the model runs on it.
No IOT · by design
Evidence · 01
The leak isn't hypothetical. It's measured.
Cloud AI works. The cost is that your material has to travel to reach it. Once it has travelled, its safety is somebody else's policy. Independent research now puts numbers on what that costs.
What employees actually send to AI tools
Each square = 1 in 100Pasting into prompts
Share of employees who paste corporate data into generative AI prompts.
0%Outside company control
Share of those pastes made from personal accounts, not corporate ones.
0%Sensitive material
Share of corporate data entering AI tools classed as sensitive, up from 10.7% two years earlier.
0%Sources: LayerX, Enterprise AI and SaaS Data Security Report 2025 [3]; Cyberhaven, 2025 [4]. Roughly 14 pastes per employee per day go to non-corporate accounts, at least three of which carry sensitive content.
Ungoverned AI, by the numbers
IBM Cost of a Data Breach 2025
0%
Shadow AI breaches
One in five breaches involved unsanctioned AI tools running without oversight.
0%
No access controls
Of organisations breached through an AI system, almost all lacked AI access controls.
0%
No governance policy
Most organisations still have no policy governing AI use or shadow AI risk.
Source: IBM Security / Ponemon Institute, Cost of a Data Breach Report 2025 (600 organisations, 17 industries, 16 countries) [1]. Organisations with heavy shadow AI use paid roughly $670,000 more per breach.
Data that never leaves can't be leaked in transit. That's the whole idea.
Evidence · 02
What one breach costs.
Averages across 600 breached organisations. Healthcare has been the most expensive sector to breach for more than a decade running, and it is exactly where the most sensitive AI prompts are being written.
Average cost per breach, 2025
USD, millions
Elevated exposure
Baseline
Source: IBM Security, Cost of a Data Breach Report 2025 [1]. Breaches took an average of 241 days to identify and contain globally; healthcare averaged 279 days [1][5].
How many parties touch one request
Attack surface, per queryCloud AI
0Points where the data exists outside your control.
- Local network egress
- Transit provider
- Provider infrastructure
- Sub-processors
- Server-side logs
- Retention & training pipelines
No IOT
0The request is answered where it was written.
- Local memory
- Local storage
- Local model weights
Illustrative architecture comparison. Every additional party is a point at which access control, retention policy and jurisdiction stop being yours. That is the failure mode IBM identifies in 97% of AI-related breaches [1].
Evidence · 03
Dependable means it works when the internet doesn't.
On 20 October 2025, a DNS fault inside a single AWS region cascaded through the services that most of the internet is built on. Thousands of platforms went dark for hours. Nothing was attacked. A routine update was enough.
20 October 2025 — us-east-1
Availability, 24-hour windowCloud-dependent AI15+ hours degraded
On-device AIUnaffected
00:0006:0012:0018:0024:00 UTC
0AWS services caught in the cascade
0Platforms disrupted worldwide
0Outage reports logged globally
0Attackers involved. It was a config error
Sources: Cisco ThousandEyes outage analysis, 20 Oct 2025 [6]; AWS post-event summary; Downdetector aggregate reports [7]. A race condition in DynamoDB's DNS management cascaded to dependent services across the region.
Time to first response
Same task, same model classCloud round trip100–500 ms
On-device inferenceUnder 10 ms
Sources: comparative edge-versus-cloud inference literature; network latency to centralised model services measured from ~48 ms to several hundred ms depending on provider and user location [8][9]. Figures vary by model size, hardware and task. The gap is structural, not incidental: distance costs time.
No network dependency. No shared blast radius.
The principle
Bring the intelligence to the data.
Not the other way around. It's a one-line change in architecture that removes most of the exposure above.
Cloud AIData leaves you
Your data
Internet
Cloud
AI
Internet
You
Six hops. External servers. Retention you don't set.
No IOTData stays with you
Your data
Your device
Your AI
Nothing crosses the perimeter. Private by architecture, not by promise.
On-device
AI runs locally on compatible devices and infrastructure.
Always yours
Your intelligence layer isn't dependent on sending everything to someone else's cloud.
Less cloud. More control.
Applications
One technology.
Many worlds.
AI that respects privacy.
Private AI assistants for hospitals, clinics, doctors and patients.
$7.42M · 279 days
Average healthcare breach cost, and the average time to identify and contain one. IBM, 2025 [1][5]
- Medical knowledge assistance
- Patient interaction
- Clinical workflows
- Medical documentation
- Healthcare administration
- Private medical AI
Your private AI study partner.
An AI that can live on your computer and understand your personal study material without sending sensitive academic content to the cloud.
233 incidents
AI-related security incidents recorded in a single year, a 56% rise. Stanford AI Index, 2025 [10]
- Exam preparation
- Research assistance
- Personal knowledge systems
- Academic document analysis
- Private tutoring
- Offline learning
A home that thinks locally.
Bring AI into the home without turning every interaction into a cloud transaction.
15+ hours dark
How long cloud-dependent home devices were degraded in one 2025 regional outage. ThousandEyes [6]
- Private AI assistant
- Home automation
- Local voice control
- Smart routines
- Security
- Personal knowledge
Your AI office, inside your office.
Deploy private AI across teams and workflows without exposing sensitive business information to external AI infrastructure.
+$670,000
Added cost per breach at organisations with high shadow-AI use. IBM, 2025 [1]
- Internal knowledge
- Document intelligence
- Meeting intelligence
- Workflow automation
- Private copilots
- Department-specific AI
Pick the world you'd start with. We'll tell you when it's ready.
The future of AI isn't necessarily in the cloud.It may be sitting on your desk.
No IOT is exploring what happens when intelligence moves closer to the people, devices and environments that use it.
How it works
AI. Where you need it.
Install
Deploy No IOT on a compatible device or private infrastructure.
Connect
Connect your knowledge, workflows, devices and applications.
Think
Let AI reason, assist and automate, all locally.
No unnecessary data journeys.
No dependency on a remote AI brain.
Future vision
We're building an AI world that works offline.
Imagine:
01
A hospital where sensitive AI interactions remain inside the hospital.
02
A researcher whose AI understands years of private work without uploading it.
03
A student whose personal AI works without an internet connection.
04
A home where the AI assistant actually lives inside the home.
05
An office where company intelligence stays inside the company.
That's the world No IOT is building toward.
Early access starts with a small group. Yours could be in it.
Wishlist
Be early.
No IOT is building the next generation of private, on-device intelligence. We're starting with a small group of early users, innovators, researchers, healthcare professionals and organizations.
Join the wishlist and be among the first to know when No IOT is ready.
Early access · rolling invitations
References
- IBM Security & Ponemon Institute — Cost of a Data Breach Report 2025. 600 organisations, 17 industries, 16 countries.
- IBM Think — Navigating the AI rush without sidelining security, 2025.
- LayerX — Enterprise AI and SaaS Data Security Report, 2025.
- Cyberhaven — AI adoption and corporate data exposure research, 2025.
- HIPAA Journal — Average cost of a healthcare data breach, 2025.
- Cisco ThousandEyes — AWS outage analysis, 20 October 2025.
- Downdetector / AWS post-event summary, October 2025.
- Comparative edge-versus-cloud inference performance literature, 2024–2025.
- Edge-first language model inference: models, metrics and tradeoffs — arXiv:2505.16508.
- Stanford HAI — AI Index Report 2025, AI-related security incident tracking.
Figures are drawn from published third-party research and describe the wider industry, not No IOT products. No IOT is pre-release; nothing here is a performance claim about a shipping product.