AI That Works on Your Devices, Not Just in the Cloud
Skerry Labs helps hardware and product teams move AI analysis onto the device itself — keeping data local, reducing latency, and making deployments you can actually maintain.
Three Ways We Can Help
Each service is scoped to a specific stage of your journey toward on-device AI — from first exploration to a fleet-wide rollout.
Edge Feasibility Review
A starting point for teams exploring whether their analysis workload can realistically run on hardware rather than a cloud endpoint. We look at your use case, device constraints, and data flow — then put together a clear written summary of what a sensible path would look like.
- Use case and hardware review
- Device constraint assessment
- Written approach summary
On-Device Setup
For engineering leads ready to move beyond planning, this service takes a small build onto the target device — with a working update routine so the deployment stays maintainable after we leave. Includes a hands-on training session for your team.
- Device configuration and setup
- Structured update routine
- Team training session
Edge Deployment Programme
A broader engagement for teams managing a fleet of devices. We handle multi-device setup, establish a regular review cycle, and produce a maintenance handbook so your own engineers can take ownership of the deployment long-term.
- Multi-device configuration
- Ongoing review cycle
- Maintenance handbook
Why Teams Choose On-Device AI
Moving analysis onto the device changes how your product performs, what data leaves the hardware, and how much your team depends on connectivity.
Lower Latency
When the model runs on the device, results come back in milliseconds — no round trip to a remote server required.
Data Stays Local
Sensitive readings and user data never leave the device, which simplifies data handling and reduces exposure.
Works Offline
Processing continues whether the device is connected or not — useful in manufacturing floors, field sites, and remote locations.
Reduced Cloud Spend
Shifting inference to the device cuts the volume of API calls and cloud compute your product relies on.
Team Ownership
We document update routines and review cycles so your engineers maintain the deployment without depending on us long-term.
Right-Sized Approach
We scope each engagement to your actual stage — feasibility, single-device, or fleet — rather than pushing a larger project than you need.
Have a Use Case in Mind?
Drop us a note with a brief description of your device and what you're trying to do with it. We'll take a look and come back with an honest assessment of what's worth pursuing.
Frequently Asked Questions
What does "on-device AI" actually mean?
It means the model or analysis logic runs directly on the hardware — a microcontroller, embedded board, or edge device — rather than sending data to a cloud server for processing. The device handles everything locally.
How do I know if my hardware can support this?
That's what the Edge Feasibility Review is designed to answer. We look at memory, processing power, storage, and your specific analysis task, then give you a written view of what's realistic and what might need adjustment.
Do we need AI or ML expertise in-house before starting?
No. Our services are designed for hardware and product engineering teams, not data science teams. You bring knowledge of your device and use case; we bring the edge AI setup and documentation.
What happens after the engagement ends?
We document everything — update routines, configurations, review processes — so your team can maintain the deployment independently. The goal is for you to own it, not to keep coming back to us.
How long does each service take?
The Feasibility Review typically takes one to two weeks. On-Device Setup runs two to three weeks depending on device complexity. The Edge Deployment Programme is a longer engagement, usually four to eight weeks, based on fleet size and review scope.
Are the prices fixed or negotiable?
The listed prices are starting points for the standard scope of each service. If your situation requires a different scope — more devices, additional review cycles, or a narrower focus — we're happy to discuss what fits your project.
Our Location
Suite 12-2, UOA Business Park, Shah Alam, Selangor
Send Us a Message
Whether you have a specific project or just want to talk through whether edge AI makes sense for your product, we're happy to hear from you.
Contact Details
Phone
+60 3-5022 7461Address
Suite 12-2, UOA Business Park,
Jalan Pengaturcara U1/51A,
40150 Shah Alam, Selangor
Office Hours
Monday – Friday: 9:00 AM – 6:00 PM
Closed weekends and Malaysian public holidays