Solutions
Edge AI, IoT, electronics design and embedded systems
Edge AI
Intelligence on the device, next to the sensor.
An edge product runs its model on the device, so the processor, the memory, the power budget and the heat decide what is possible before any software is written. Those choices are made early, from requirements that are often still incomplete.
What MithraTiny does for it today
- Choose the main processor and the other main active parts of an edge board from its requirements, with worst-case rating and derating checks and the design risks listed.
- Turn the requirements of an edge product into test cases, with a traceability matrix and a coverage report.
- Run on a model of your own on your own network (Ollama), so a design never has to leave it.
Next
In future developmentAI engineering agents for the edge: checking a model and its workload against the memory, power and latency budget of a device before the hardware is chosen.
IoT
Connected devices that hold up in the field.
An IoT product is a small device with a long life: it runs on limited power, sits on a network and has to keep working for years. Whatever is decided about its parts, its cost and its requirements is multiplied by the number of devices that ship.
What MithraTiny does for it today
- Choose the main processor and the other main active parts of an IoT device or gateway from its requirements, with worst-case rating and derating checks and the design risks listed.
- Find savings in the bill of materials of a gateway or a sensor node, shown per unit and per year at your annual volume.
- Turn the requirements of a connected product into test cases, with a traceability matrix and a coverage report.
Next
In future developmentAI engineering agents for connected products: from device requirements to a checked design for power, connectivity and a long life in the field.
Electronics design
From requirements to a board you can defend.
A board is a chain of decisions: which part, at which rating, from which supplier, at what cost. Each one has to hold in the worst case and be explained to the next person who reads the design.
What MithraTiny does for it today
- Go from board requirements to functional blocks, a power tree and checked main active components, with the missing requirements listed instead of guessed.
- Find savings in a bill of materials: duplicates, alternates, obsolete parts and supplier consolidation, each saving counted once and each change with its risk.
- Check parts against live DigiKey and Mouser stock, price, lead time and lifecycle, once the distributors are connected: the figures come from the distributors, never from a model.
- Ground the results in your own datasheets, design rules and approved parts lists.
Next
In future developmentAI engineering agents for more of the design flow: design review support and supporting calculations beyond the main components and the bill of materials.
Embedded systems
Requirements that turn into verified behaviour.
An embedded product is judged against its requirements and the standards of its field, and every requirement needs a test. Writing and tracing those tests by hand takes time that engineers would rather spend on the design.
What MithraTiny does for it today
- Turn requirements into functional, system and non-functional test cases, with positive, negative and boundary cases, for Embedded Systems and for domains such as automotive and industrial automation.
- Trace every requirement to its tests, see what is not covered yet, and export to Excel, PDF and JSON.
- Ground the test cases in the standards and guidelines you add, such as ISO 26262, ASPICE or DO-178C.
Next
In future developmentAI engineering agents for the firmware side: from requirements to the verification of the software and of the hardware and software interface.
See everything that is in future development
The MithraTiny LLM, more AI engineering agents and the work for each area above.
Put an AI Engineer on your next board
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