device assessment
We define the solution, acceptance criteria and connection to the business result.
service
Edge AI and local processing close to the data source
We design local image, video and event processing for devices where the cloud is unavailable, expensive or undesirable.
data loop production-ready
01 Task
02 Architecture
03 Development
04 Launch
05 Evolution
API integrations and statuses
Reports PDF, XLS, BI
AI validated on data
use case
When it makes sense
Useful for cameras, industrial environments and tasks such as license plate recognition on RK3568, where latency, privacy, autonomy or cloud-free operation matters.
local video processingcamera eventsmodel optimizationdevice integrationevent logsresult transfer
Solution scope
01 device assessment
02 model selection
03 inference optimization
04 event service
05 local storage
work
What the project includes
model selection
We define the solution, acceptance criteria and connection to the business result.
inference optimization
We define the solution, acceptance criteria and connection to the business result.
event service
We define the solution, acceptance criteria and connection to the business result.
local storage
We define the solution, acceptance criteria and connection to the business result.
launch instructions
We define the solution, acceptance criteria and connection to the business result.
examples
Typical outcomes
camera-side detection
The result can be used in an interface, API, report, integration or operating procedure.
license plate recognition on RK3568
The result can be used in an interface, API, report, integration or operating procedure.
event log
The result can be used in an interface, API, report, integration or operating procedure.
local service
The result can be used in an interface, API, report, integration or operating procedure.
status transfer
The result can be used in an interface, API, report, integration or operating procedure.
control panel
The result can be used in an interface, API, report, integration or operating procedure.
process
How the project runs
Stages adapt to the task, but the logic remains the same: less uncertainty, more verifiable output.
- 01
Understand the task
We clarify the business goal, constraints, data, users, integrations, risks and success criteria.
- 02
Design the solution
We define the architecture, roles, interfaces, API, data model and first production-ready scope.
- 03
Build the working version
We launch the key workflow early enough to test value and collect feedback from real users.
- 04
Prepare for operation
We add access control, logs, monitoring, reports, documentation and clear error handling.
- 05
Integrate and launch
We connect the system to external tools, client infrastructure and day-to-day business workflows.
- 06
Support and improve
We fix, optimize and extend the system as the product and business process evolve.
start
What to send for an estimate
- device type
- data stream
- expected latency
- network conditions
- privacy constraints
technology
What may be used
ONNXTensorRTOpenCVRK3568Dockercameras
FAQ
Questions about this direction
Can we start with an audit or short discovery phase?
Yes. For complex tasks it is often safer to start with a short discovery phase to clarify risks, data, integrations and first-version scope.
How quickly can we get the first working version?
The timeline depends on the task and available inputs. We isolate the main workflow so the first useful version appears before the full system.
Do you hand over source code and documentation?
Yes. Repository access, delivery format, credentials and documentation are agreed before development starts.
next step
Have a product idea, automation task or AI project?
Describe the task and add a link to sample data or the current workflow. We will assess the approach, risks, stages and first working version format.