Enhance in-car infotainment with speech

Our quality-focused approach to speech collection focuses on proper distribution to defeat algorithmic bias so that every user is heard.



Customers are willing to spend up to 15% more on a car for a state-of-the-art infotainment system.


of millennials

Nearly ¾ of millennials consider enhanced infotainment features as ‘must-haves’ when purchasing new vehicles.

Spontaneous speech collection

Train in-car virtual assistants to understand real human speech.

Audio transcription

Build the foundation of speech recognition models with highly-accurate transcriptions.

Listening tests

Collect valuable insight on the naturalness of a virtual assistant’s utterances.

Develop predictive maintenance

We teach models to process a wide array of input types so they can monitor critical assets and flag small issues before they snowball into critical failures.


less downtime

Automakers with predictive maintenance programs in place experience 160 fewer hours of equipment downtime per year.


billion saved

Market analysts expect predictive maintenance will save manufacturers between $240-$630 billion per year in the next decade.

Audio collection & validation

Train models to listen for mechanical anomalies.

Multimodal data collection

Enable models to process a large range of datatypes to understand overall asset health.

Image collection & validation

Teach models to watch for small signs of minor malfunctions.

Build autonomous vehicles

Our computer vision and multimodal workflows build the foundations for automated driver assistance.



Experts project a market value of $1 trillion for autonomous vehicles in supply-chain logistics.


cost reduction

Autonomous vehicles stand to lower freight-shipping costs by as much as 40% per kilometer.

Object tracking

Train models to recognize and follow moving objects.

Image tagging

Enable models to identify certain objects present in images.

Image classification

Teach models to sift through large swaths of images/videos.

Success stories

Mastercard’s R&D Labs needed unique, multi-lingual text data that covered 20 designated payment scenarios in English and Spanish, and they needed it fast.

Keeping a nation’s lights on means constantly inspecting electricity poles for damage. EDP partnered with DefinedCrowd to improve Asset Performance Management processes.

A global electronics maker came to DefinedCrowd with the goal of building more inclusive facial recognition models, requiring accurately annotated images with highly specific criteria.

A Fortune 500 Tech company needed comprehensive speech training data in French that accounted for a wide range of dialects, requiring diverse data in terms of age, gender and regional dialects.

A visionary Fortune 500 Tech company leveraged sentiment analysis models to dig beyond surface-level understandings to extract granular-level insights.

Smart companies see the pile of unstructured text floating through the digital realm as a strategic goldmine of consumer insights.