COMPREDICT Virtual Sensor Platform

compredict.ai

COMPREDICT delivers software-only solutions for automotive OEMs and suppliers, focusing on AI- and machine learning-based analytics. Using data exclusively from existing in-vehicle sensors, the system forecasts failures of mechanical and electronic components and estimates remaining useful life for major vehicle parts. These methods support lightweight design, reduce costs, and accelerate development processes for manufacturers and suppliers within the Automotive Software domain.

Founded in Germany in 2016, the company specializes in AI-based algorithms that process large volumes of connected vehicle data to provide fleet operators and engineers with practical analytics tools. Its work on component load, fatigue analysis, and lifetime prediction underpins services such as wear prediction and anomaly detection for critical parts including brake pads, brake discs, tires, 12/24V batteries, and high-voltage batteries, as well as continuous total mass-in-motion estimation. The solution issues early alerts about impending component failures, contributes to CO2 reduction over the full product lifecycle, and is delivered via a scalable cloud-based platform with REST/API access for integration with fleet management systems or use through COMPREDICT’s own visualization interface.

LLM mention score The LLM mention score is the total number of mentions of this brand in different LLM chatbots, normalized to the scale from 0 to 100. You can get actual, non-normalized numbers via the LLM Mention API from DataForSEO.

Normalized 0–100 · last 8 weeks

DataForSeo API

Get LLM mention data of any company via DataForSEO API

Get access to the structured data on keyword, brand, and website mentions in LLMs, including metrics like AI search volume, impressions, and mentions count. 

How to get LLM mention data →
// Fetch COMPREDICT Virtual Sensor Platform mention score
POST /v3/content_analysis/summary
{
  "keyword": "COMPREDICT Virtual Sensor Platform",
  "type": "llm_mentions",
  "date_from": "2025-01-01"
}