Visual AI modules
Object detection, tracking and OCR, connected to a practical workflow rather than a standalone model.
Visual AI modules, edge deployment and software integration. A focused development partner for small teams with a real project to deliver.
Cameras · streams · files
Detect · track · read
Structured data · events · video
You bring the product and the project.
We build the AI part.
For hardware developers, inspection teams and software integrators who need a defined AI module without building an entire in-house AI team.
Object detection, tracking and OCR, connected to a practical workflow rather than a standalone model.
Bring visual AI into an RK3588 device, connect video sources and make results available to your existing system.
Focused business tools, applications and websites that turn an AI capability into something your users can use.
Jetson and other platforms can be assessed for a specific project. Platform compatibility and migration effort are confirmed before a delivery commitment.
Existing Linux / RK3588 development brings video input, inference, post-processing and operations into one service. A new task still needs sample-based validation.
Starting points for a discussion — these are application directions, not customer case studies.
Connect inspection imagery to object detection, tracking or a task-specific review workflow.
Explore visual inspection, text recognition and event output around the data your cameras capture.
Build a local video and inference service into a compact device with practical operating controls.
Add a defined AI step to an application, internal tool or customer-facing website.
Begin with a specific task and a small paid validation. Agree on the scope before committing to full development.
Project-based development with agreed milestones and deliverables. English and Chinese written communication are welcome.
Share the device, target behavior, representative samples, budget and timeline. We establish what a useful result looks like.
Use a scoped paid validation to check the approach, constraints and integration path. Agree on the next step from the evidence.
Implement the agreed AI component and interfaces. Review progress against the defined milestone and test samples.
Deliver the agreed code or package, deployment instructions and acceptance results. Ownership, licensing and support are agreed in the project scope.
Yes. A defined AI module, deployment task or integration package is a good starting point. We agree on inputs, outputs and acceptance criteria so it can fit into your broader project.
Only after examining representative samples, the target device and the task. New tasks begin with validation, and acceptance criteria are agreed before full development.
No. The existing edge software foundation is on RK3588. Jetson and other platforms need a project-specific assessment. Camera systems, compact edge boxes and AI applications are also possible directions.
The device, the task, sample data, budget range and timeline. For sensitive samples, first send a short description; agree on a suitable sharing method and confidentiality terms before transferring data.
A short project description is enough to begin. We can then assess the fit, schedule and scope together.
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Board, OS, camera or video source
What the AI should recognize or do
Available images, videos or examples
Expected range or a validation budget
Target date and current project stage
Hello SmartWebPark AI, I would like to discuss an AI project. 1. Device / platform: 2. AI task and expected result: 3. Available samples: 4. Budget range: 5. Timeline / project stage: Company / name: