Randomred provides advanced data‑processing and machine‑learning tools that analyze full‑waveform measurements to deliver automated, uncertainty‑aware results for metrology, telecom, power‑grid and sensor‑network applications. Their platform includes standard‑compliant uncertainty propagation, SI‑traceable sensor‑network frameworks, and a blockchain‑compatible oracle for secure verification of calibration data, while also offering predictive credit‑risk models for financial institutions.
Funding
Funding not disclosed
Founders
Product
Problem
Many industries that rely on precise measurements—such as telecommunications, power grids, and metrology institutions—still use parameter‑based standards that do not capture the full information contained in electrical waveforms. This limits the ability to assess measurement uncertainty, propagate it reliably, and ensure traceability, especially in complex or distributed sensor networks. Additionally, the lack of trustworthy, tamper‑proof data from IoT devices hampers the adoption of blockchain‑based verification in legal metrology.
Solution
Randomred develops advanced data‑processing and machine‑learning solutions that operate on full‑waveform measurements, enabling automated, adaptive, and uncertainty‑aware analysis for a wide range of dynamic processes. Their platform provides standardized methods for uncertainty estimation and propagation, supporting compliance with metrology standards and SI traceability. For sensor networks, Randomred delivers software frameworks that assess data quality, propagate uncertainties, and perform risk analysis across distributed measurements. The company also integrates blockchain oracle technology that securely links IoT sensor data to immutable ledgers while adhering to metrology specifications, facilitating cross‑border verification of calibration and testing credentials. In the financial sector, Randomred offers predictive models that estimate the probability of late payments and segment accounts by risk, applying the same rigorous data‑science approach to improve decision‑making.
Target Audience
Primary customers include metrology laboratories, telecom and power‑grid equipment manufacturers, organizations deploying large‑scale sensor networks, and financial institutions seeking advanced credit‑risk analytics.
Features
- Full‑waveform analysis engine with machine‑learning models for adaptive measurement and uncertainty quantification
- Standard‑compliant uncertainty propagation tools that integrate with existing metrology workflows
- Sensor‑network metrology framework providing data‑quality metrics, SI‑traceability, and automated risk assessment
- Blockchain‑compatible oracle layer that authenticates IoT measurements against metrology standards for legal verification
- Financial risk prediction model that calculates late‑payment probabilities and categorises accounts into risk tiers
- API and SDKs for seamless integration with industry equipment, data platforms, and enterprise analytics environments