Tasq AI and BLEND have agreed to merge, forming a unified company under the Tasq AI brand aimed at closing what the companies describe as the enterprise AI “trust gap” by improving the accuracy and reliability of production-grade AI systems.
Based in Tel Aviv, the combined company said it is generating tens of millions of dollars in revenue and will employ roughly 120 people. The merged entity will offer an end-to-end “Data Refinery” platform that combines proprietary data technology with a global human network, including millions of contributors and more than 25,000 vetted domain experts spanning over 120 languages.
Tasq AI said its expanded client roster includes about 200 enterprise customers, naming Meta, PayPal, Reddit, iHerb, Puma and Payoneer among them. Financial terms of the merger were not disclosed.
Yoav Ziv, a former executive at Amdocs and Checkmarx, will serve as CEO of the merged company. Ziv said the company’s approach is designed to increase the speed and quality of data work used in model training and evaluation, including enabling models to be trained “up to 10x faster than existing approaches.”
The company positioned the merger against broader enterprise challenges around data readiness and AI adoption. Citing Salesforce research, Tasq AI said 76% of business leaders feel pressure to deliver value from data, while a separate “Your Data, Your AI” survey found 54% of AI users do not trust the data used to train their models—an issue the company argues slows adoption. Tasq AI also referenced MIT research indicating a high failure rate for generative AI projects, attributing many breakdowns to poor data quality and fragmented data processes.
Tasq AI said the merged platform is built around a multi-layer model that deploys human intelligence “just in time,” pairing large-scale crowd work for volume and diversity with domain experts for specialized, higher-precision tasks. The company said the approach is intended to support workflows such as LLM evaluation, fraud detection, video annotation, and other data-intensive AI use cases where accuracy and cultural nuance are critical.
Founded in 2019, Tasq AI said it pioneered the “Data Refinery” approach to AI training and delivers “99% trust-grade data” for accuracy-sensitive industries. The company said it is backed by private investors led by Professor Shai Dekel.
KEY QUOTES:
“If we compare the AI revolution to the automotive revolution, NVIDIA builds the highways, AI model companies build the engines, and data is the fuel. Yet data-related challenges prevent many AI systems from reaching their destination, despite massive investments in infrastructure and models. Tasq AI’s mission is to ensure AI models deliver real, production-grade value and that the adoption of AI models and GPUs continues to scale. We build the modern refinery that organizes data and human expertise to power the AI revolution.”
Erez Moscovich, Founder and President, Tasq AI
“Data has become the critical defensive layer in the $1.5 trillion AI market, that safeguards the quality and reliability of AI models. We are establishing a single entity that combines technology and people to tackle the greatest challenge in AI implementation: trust, at speed and quality levels no one thought possible. Tasq AI’s technology enables AI models to be trained up to 10X faster than existing approaches.”
Yoav Ziv, CEO, Tasq AI
