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AI21 and Invisible Technologies Announce Strategic Partnership to Drive AI Adoption for Enterprise

New partnership with Invisible Technologies will enable AI21 to assist enterprises with custom, data-driven AI models

Today, AI21, a leader in generative AI for enterprise, and Invisible Technologies, an industry leader in AI training and support, have announced a strategic partnership to serve the enterprise with improved AI solutions.

“We partnered with Invisible for their ability to provide high quality data at scale, essential for developing our Foundation and Task-Specific Models that deliver reliable outcomes,” said Ori Goshen, co-founder and co-CEO of AI21. “This partnership is yet another strategic step to help our enterprise clients customize AI models on more reliable data.”

The partnership will leverage Invisible’s process orchestration platform and a global workforce of experts in Supervised Fine-Tuning (SFT) – a process that refines AI models for specific tasks using tailored datasets for enhanced model performance – and Reinforced Learning from Human Feedback (RLHF) – a method that employs human feedback to further improve the quality and efficacy of AI21 models. This approach ensures the creation of more custom-built and flexible models for clients worldwide.

Invisible’s unique approach to AI training, which encompasses deep partnership with researchers, efficient management of complex processes, and a holistic focus on agent engagement and development, distinguishes them in the AI landscape. “Our strong belief in the synergistic power of technology and human expertise is at the core of our vision for the future of AI,” said Ben Plummer, CEO of Invisible. “Our collaboration with AI21 highlights this synergy and stands as a testament to our shared values of delivering the highest quality in AI.”

This partnership underscores AI21 and Invisible Technologies’ joint mission to make machines a thought partner to humans. The collaboration between AI21’s advanced models and Invisible’s best in class training methods promises a productive future for AI-driven organizations worldwide.