Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights on big data startups. This time, you get to discover 5 hand-picked startups developing ethical data collection solutions.
Global Startup Heat Map: 5 Top Ethical Data Collection Solutions
The 5 ethical data collection solutions you will explore below are chosen based on our data-driven startup scouting approach, taking into account factors such as location, founding year, and relevance of technology, among others. This analysis is based on the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 1.3 million startups & scaleups globally.
The Global Startup Heat Map below highlights the 5 ethical data collection startups & scaleups our Innovation Researchers curated for this report. Moreover, you get insights into regions that observe a high startup activity and the global geographic distribution of the 117 companies we analyzed for this specific topic.
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Airbloc develops a Compliant Data Exchange Platform
Data exchange platforms allow organizations to commercialize, distribute, share and obtain data. These platforms need to be compliant with international and local privacy laws which regulate data collection. To this avail, startups employ technologies such as a distributed ledger to ensure and verify consent to data collection.
South Korean startup Airbloc offers a data exchange platform that follows ethical data collection principles. The startup uses blockchain and REST APIs to ensure that all participating companies utilize consensual data only. Airbloc also embeds ethical data collection principles to its other products such as Data Lab, a customer intelligence platform, to ensure data issuers’ privacy and participants’ compliance with regulations.
co:census works on Survey Data Collection
Contrary to extracting data insights from website viewership or app activity, the purpose of a survey is to collect straight answers to the questions of interest. Be it a budgeting consideration for a local government or feedback for a new product, the right questions help ethically collect useful data. To help with this, startups develop platforms for survey design, collection, and data analysis.
US-based startup co:census develops a survey data collection platform for private and public sectors. The startup uses Short Message Service (SMS) as a survey administration channel and processes inbound messages in its analytics platform. It provides data-driven insights that facilitate decision-making without infringing on the privacy of consumers.
Raylytic develops Medical Data Collection Solution
In modern medicine, data powers various processes from clinical studies to health insurance. However, regulatory requirements such as HIPAA require patients’ consent for data collection, and the cost of clinical studies often limits MedTech companies’ collection capacities. Therefore, startups develop data collection and processing solutions that provide digital medical documentation and study data.
German startup Raylytic provides medical data collection and analysis solutions for pharma companies, research centers, and hospitals. The startup’s platform, UNITY, handles electronic data capture, clinical trial management, and medical image analysis. The platform allows clinicians to design individual, adjustable questionnaires for collecting medical and background information, securing data collection regulation compliance.
Loyall specializes in GDPR-Compliant Data Collection
Implementation of the General Data Protection Regulation (GDPR) leads to a loss of non-compliant customer data. As a result, startups are rethinking conventional data collection practices. Nowadays, companies need to disclose the purpose of data collection and have customers’ consent to use their data. That is why startups offer data collection platforms that take into account compliance regulations such as the GDPR.
Norwegian startup Loyall develops a GDPR-compliant data collection solution for retail, telecom, and marketing companies. The startup collects information on physical and digital customers either using an API or through WiFI software. The platform converts collected information into GDPR-compliant profiles to develop more targeted marketing campaigns.
Deeping Source offers Data Anonymization
Training a good machine learning (ML) model requires significant amounts of data. But the compliance with privacy regulations renders a lot of collected data unusable for ML training. Consequently, startups develop data anonymization solutions that remove personal information from collected data, making it usable for AI applications.
South Korean startup Deeping Source offers data anonymization for ML development. The startup offers an anonymizer, obfuscator, jammer, and watermarking to remove personally identifiable information (PII) from the text, video, audio, and images. By removing PII, the solution Deeping Source ensures that the collected data is compliant with regulations and allows companies to safely use key attributes for building ML models.
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