Loading organizations...
Founded in 2025 by former RapidAPI chief executive Iddo Gino, Datawizz is a San Francisco enterprise with operations in Tel Aviv that develops Specialized Language Models as efficient alternatives to large general language models. The startup provides an intermediate software layer that automatically generates small, task-specific models from relevant data, routes queries to the optimal model, and corrects errors. This approach minimizes reliance on external providers like OpenAI while enabling localized deployment on personal computers and mobile devices to reduce energy use and costs. Operating with a team of four employees, the company targets early enterprise customers across the fintech, electronic commerce, and SaaS sectors. To support its platform, Datawizz secured twelve and a half million dollars in September 2025 through a seed venture capital financing round led by Human Capital alongside BGV and 91VC.
Datawizz.ai has raised $13.0M across 1 funding round.
Datawizz.ai has raised $13.0M in total across 1 funding round.
Datawizz.ai has raised $13.0M in total across 1 funding round.
Datawizz.ai's investors include Brian Blond, Angular Ventures, 91Ventures, Benhamou Global Ventures.
Datawizz.ai has raised $13.0M across 1 funding round. Most recently, it raised $13.0M Seed in September 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Sep 1, 2025 | $13M Seed | Brian Blond | Angular Ventures, 91 Ventures, Benhamou Global Ventures | Announced |
Datawizz.ai is a technology company founded in 2025 that specializes in generating realistic synthetic data and building specialized language models (SLMs) to optimize AI usage for enterprises. Their platform helps businesses reduce the high costs and inefficiencies associated with large general-purpose AI models by automatically training smaller, more efficient expert models tailored to specific enterprise data and AI request patterns. Datawizz serves organizations that rely heavily on AI and machine learning, offering solutions for machine learning, software testing, data enrichment, and augmentation, all while ensuring data privacy and compliance. Their technology achieves significant cost reductions (up to 85%), speed improvements (5 to 15 times faster), and higher accuracy compared to traditional large language models (LLMs)[1][2][3].
Datawizz was founded in 2025 by Iddo Gino, who recognized the rapidly growing costs and inconsistent results enterprises faced when using large, general-purpose AI models. The company emerged to address this challenge by offering specialized, cost-effective AI models that enterprises can fully own and deploy on-premises, on devices, or in the cloud, eliminating expensive API calls and external data sharing. Early traction included raising $12.5 million in seed funding led by Human Capital, with participation from BGV and 91VC, enabling Datawizz to accelerate product development and expand operations across the US and Europe[2].
Datawizz rides the trend of AI specialization and cost optimization amid the explosive growth in AI adoption, where enterprises spent $8.4 billion on LLM API calls in the first half of 2025 alone. The timing is critical as the AI market faces challenges of high operational costs and inconsistent model performance. By enabling organizations to own and customize their AI models, Datawizz addresses growing concerns around data privacy, vendor lock-in, and scalability. Their approach influences the broader ecosystem by pushing the industry toward more efficient, specialized AI deployments that balance cost, performance, and control[2].
Looking ahead, Datawizz is positioned to expand its footprint in the AI infrastructure space by continuing to develop its platform capabilities and grow its customer base across the US and Europe. Trends such as increased demand for AI cost efficiency, data privacy, and on-device AI will shape their journey. As enterprises seek more control over AI models and data, Datawizz’s specialized model training and routing technology could become a standard for managing AI workloads. Their influence may evolve from a niche cost-saving tool to a foundational AI management platform that empowers businesses to innovate securely and efficiently.
This trajectory ties back to their core mission: enabling enterprises to *own their AI* by providing smarter, faster, and more affordable AI solutions tailored to their unique needs[2][3].
