for automotive applications

Teraki's unique edge processing technology solves the performance issues and the cost challenges for connected cars and autonomous driving. Our software operates in constrained and embedded hardware and gets more, better and AI-optimised car data to our customers. Done 10X more efficiently, quicker and with the highest possible accuracy rates. In doing so, Teraki enables to truly scale applications such as Crash Detection, Predictive Accident Alerts, Predictive Maintenance, Fleet Management and Autonomous Driving.

What we do

About Us.

What. How. Why.

What we do.

Teraki’s software is a key driver for scaling of Insurance, Predictive Maintenance and Autonomous Driving Applications by enabling access to more qualitative data.

Teraki begins doing so, by identifying the most relevant data already at the embedded side and transmits this data in the proven most compact form possible. This is done while maintaining the customers key KPIs based on the latest state of the art AI data processing schemes. As such, Teraki’s software enables to fulfil low-latency SLAs required by the end-user and ultimately to adapt key KPIs such as cost-per-mile at the highest precision and lowest latency.

Therefore, Teraki enables to bridge the gap towards true vehicle autonomy, by overcoming the time-gap of future 5G networks and by optimising automotive hardware cost efficiency.

How it works?

The data reduction is achieved by pure software. In the car (sensor, microcontroller, gateway, etc.), a client software with lowest requirements is deployed and identifies the data streams required by the AI based processing scheme. Only a fraction of the data is effectively acquired and encoded.

The data is recomposed and fed into the customers AI processing schemes, relying either on the fully reconstructed or reduced data. No relevant information is lost, while maintaining between x4 to x15 more data rates than accessible with compression products.

With a proper analysis of the data in a telematics device, higher reduction rates are achieved. Teraki’s products are compatible with existing compression and AI chip based processing solutions.

Key features.

Compared with alternatives:
Your CPU processes 5x more data.
Your application runs with 15x less end-to-end latency.
Your mobile data consumption is up to 50x lower.
Key insights are gained already at the device level while maintaining lower hardware requirements than NN based solutions.

100% software (client - server architecture). No additional hardware required.
It fits in constrained environments, the client component is just a few KB small.
Works with any private or public cloud infrastructure.
Suited for real-time applications.
Compatible with all protocols, networks, encryption and hardware technologies.
Compatibility with latest hardware platforms including AI based processing chipsets.

Use Cases.

Examples of mobility applications that Teraki makes happen.
Automotive Insurance

Automotive Insurance

Use Case: Crash detection

Crashes form the largest category of costs to insurers.

Better and more complete crash detection significantly improves the main KPIs for insurance companies as with more available data algorithms can achieve higher accuracies and draw more relevant conclusions.

Within existing architectures and hardware Teraki technology delivers 30% higher accuracy rates on crash detection algorithms. In addition, Teraki gets you this data 10 times quicker, thereby improving of the key KPIs for crash detection: accuracy and latency

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Predictive Maintenance

More data leads to less down time & costs and to higher customer satisfaction.

Getting more data our of a car with existing hardware (e.g. microcontroller, gateway, telematics unit) enables to do good analysis to determine when maintenance is due.

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Predictive Maintenance
Autonomous Driving

Autonomous Driving

Autonomous Driving is highly dependent from new sensors such as lidar, radar, video, etc. These sensors have in common to exponentially produce more data than the existing telematic sensors. This increases the data processing even more.

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Core benefits our solution provides.


AI schemes and algorithms work better with Teraki technology

Teraki data processing software provides customer’s algorithms to work with more accurate and higher frequency data streams. This means that Teraki is able to get more relevant information from the car to feed the algorithms you work with. The result is higher accuracy rates (more “true positives”) in detecting or predicting events and behaviour.


Small CPU footprint on sensor devices

Teraki reduces the CPU footprint of connected devices, thus also reduce the energy consumption and processing latency. This is particularly relevant for connected car applications with restricted hardware resources and for which a potential upgrade is only expected within next car series. Teraki plays a key role in lowering the CPU requirements for edge analytics applications, key for example for autonomous car applications.


Improved end-to-end latency

Teraki reduces the encoding/decoding latency introduced with respect to other compression solutions by up to a factor 30. Teraki helps at improving the processing latency of data. This is crucial especially in connected car applications where often immediate actions need to be derived from the data.


More data at same costs

Teraki allows you to significantly reduce the traffic generated by sensor networks and consequently to reduce your 3G/4G or satellite communication costs.


Reduce storage space of your time series and video data

Teraki helps to reduce the storage requirements for sensor data by an average of 90% and up to 99%. The reduced storage capacity requirements directly allow to increase the storage time in end devices and reduce loss of data due to communication bottlenecks. Within 2018, image, video as well as 3D data will be supported.


We are a team of experienced researchers with a broad expertise in transferring disruptive innovations into the market.
Daniel Richart

Daniel Richart

Markus Kopf

Markus Kopf

Geert-Jan Van Nunen

Geert-Jan Van Nunen



Working at TERAKI

View our job page to see what position we have currently open.

We are a diverse team of various backgrounds and are always looking for exceptional people. See open positions


Check out our latest Press Releases and News

CB Insights lists Teraki as one of the world’s 70 AI companies revolutionizing Automotive

Teraki was identified as one of the key players in the Automotive AI stack and “Edge Processing” recognised as an important, separate category

Teraki secures $2.3M in additional funding and launches DevCenter for quicker data and AI model training.

Automotive AI startup Teraki today announced it has raised $2.3 million in additional funding for its mission to provide breakthrough AI and edge data processing software. The company also announced today the launch of the Teraki DevCenter—a cloud-based data training and prototyping environment, allowing customers to train Teraki’s algorithms on their data.

Teraki launches AI and edge processing technology to meet exploding data analytics demands of the automotive industry

Teraki's breakthrough AI technology enters market using Infineon's AURIX™ line of automotive microcontrollers. Teraki’s 10X plus increase in automotive chip, communications and learning performance makes highly accurate AI applications possible in existing embedded environments.

Teraki completes $3M in financing to deliver AI and edge processing to meet exploding data analytics demands of automotive industry

Breakthrough AI technology increases automotive chip, communications and learning performance more than 10X making highly accurate AI applications possible in embedded environments. Paladin Capital Group and GPS Ventures funding will support customer implementations and accelerate roadmap development.

Partner & Awards.

We received awards and are supported by:


Latest Blog

Why Edge Computing is key for the automotive industry

Edge computing is not a new technology, but It is now starting to realise its true potential in the real-time data transfer from device to cloud and in real-time data processing at the device.

Reduce video processing with an additional 75% and retain high detection rates.

In this blog we share with you how we achieve significant data reductions in the video stream without compromising the predictive power of the car’s perception stack.

Autonomous Car’s Big Problem

The energy consumption of edge processing reduces a car’s mileage with up to 30%.


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