DSG.AI is a Tel Aviv-based company specializing in AI governance, risk management, and compliance solutions. Founded in 2015, the company has developed over 100 large-scale custom AI models and products for leading enterprises across multiple industries.
Company Overview
- Headquarters: 30 Haarba'a St, Tel Aviv, Israel
- Founded: 2015
- Employees: Approximately 44 as of 2024
- Revenue: Estimated at $3.8 million as of July 2024
- Funding: Raised $6 million in a Series A round in June 2022
Leadership Team
- Dr. Elan Sasson: Co-Founder and CEO
- Dr. Gideon Rosenthal: Co-Founder and VP of R&D
- Shaul Abergil: Co-Founder and VP of Projects
- Dr. Amjad Abu-Rmileh: Chief Data Scientist
- Or Tsur: CFO
- Elior Cohen: CTO
- Guy Schneider: Director of Sales & Business Development
Products and Services
DSG.AI offers a modular Governance, Risk, and Compliance (GRC) platform for AI, designed to operate within clients' cloud infrastructures and integrate seamlessly with organizational AI assets. Their solutions empower organizations to navigate the complexities of the evolving AI landscape while ensuring compliance with regulations such as the EU AI Act.
Market Position and Competitors
Operating within the software development industry, DSG.AI focuses on AI business management oversight, distinguishing itself from competitors like DataRobot and Palantir Technologies. This unique positioning emphasizes the company's commitment to safe and responsible AI deployment.
Industry Outlook
The global data science services market was valued at approximately $52.7 billion in 2023 and is projected to reach around $150.8 billion by 2032, growing at a CAGR of 12.8%. This growth is driven by the increasing reliance on data-driven decision-making and advancements in AI and machine learning technologies.
Opportunities and Challenges
DSG.AI is well-positioned to capitalize on the growing demand for AI governance and risk management solutions, especially as organizations seek to comply with emerging regulations like the EU AI Act. However, challenges such as the shortage of skilled data science professionals and the need for continuous innovation in a rapidly evolving market remain pertinent.
