100%
Local AI execution on your device
Private -> Local -> Always Yours
Private AI that understands you. Without sending it to the cloud.
A private AI layer for your browser that remembers, understands, and helps — private by design, local by default.
Private AI that stays on your machine
No cloud processing of your browsing context
Offline-ready help inside the browser
0:00 / 0:00
0 uploads
Browsing context never has to leave your machine
Offline-ready
Core workflows keep working without cloud dependency
$0
No recurring AI subscription for on-device help
Join Early Access
Get priority onboarding, founder-circle perks, and direct influence on what we build next.
ARCHITECTURE
Everything stays
on your machine.
No data leaves your device. Ever. Here's exactly what talks to what.
Public articles are delivered in bulk
Each day, the OCNO server crawls public news sources and delivers the full article bundle to your device in bulk. Because everything arrives upfront, the server does not know what you actually read or like.
Your local model does the ranking
A local ranker compares that bundle against your own browsing context, memory, and reading profile - entirely on-device.
Personalisation stays local
The server provides the inputs, but it does not see the local signals or ranking logic that shape your feed. The relevance layer lives on your side of the boundary.
PRIVATE AI
Built around private defaults.
Useful AI for browsing only works here when ownership, visibility, and control are built in from the start.
01Local
Execution stays close
- Run assistance where the context already exists
- Keep private reading habits off remote systems
- Avoid shipping every tab into an external workspace
- Use AI without handing over your browsing life
02Boundary
Your data stays yours
- No cloud processing for core browsing intelligence
- No telemetry-first product tradeoff
- No hidden profiling of what you explore
- A clear line between public inputs and private signals
03Autonomy
Reliable without lock-in
- Offline-capable local-first workflows
- No recurring cost for every useful interaction
- Control over when and how AI participates
- A browser assistant you can actually trust with sensitive work
What enabled this?
5-10x Faster
Thanks to its compiler-optimized engine and full GPU utilization, Ocno delivers up to 5–10× higher performance compared to traditional CPU-based in-browser model execution.
Smaller models are catching up 🔥
Smaller models like Qwen3 4B (GPU and 4GB RAM needed) can achieve quality comparable to large earlier models such as GPT-4o in many tasks proven by various benchmarks.
Model Compression & Quantization
Advances in quantization and model compression drastically reduced memory requirements, making powerful models practical on everyday devices. You can now run model comparable to GPT-4o on just 3–4 GB of RAM — enabling capabilities once limited to large cloud systems.
What hardware do you need?
MacBook M1 (Apple Silicon)
- Designed, developed, and extensively tested on Apple Silicon devices, including MacBook Pro M1 and MacBook Air M1.
- Apple Silicon unified memory architecture and high-efficiency GPU acceleration provide excellent local AI inference performance.
- Newer Apple Silicon chips (M2, M3, and beyond) deliver smoother performance.
- Newer chips also enable larger and more capable models.
Minimum: 8GB
Good: 16GB
Best: 32GB+
Minimum: M1
Good: M1 Pro
Best: M3 Max+
Recommended Baseline
M1 Pro or newer16GB RAMApple Silicon
MAKER
Meet the Builder
I replaced my social life with shipping.
