AI21 is leading the shift from LLMs and Reasoning models to planning AI systems. Maestro increases the accuracy of GPT-4o and Claude Sonnet 3.5 by up to 50% on complex, multi-requirement tasks, transforming AI from an unpredictable tool to a trustworthy system.
LAS VEGAS, March 10, 2025 /PRNewswire/ — AI21, a pioneer in frontier models and AI systems, today unveiled Maestro, the world’s first AI Planning and Orchestration System designed to deliver trustworthy AI at scale for organizations.
Introduced at the HumanX 2025 conference, Maestro marks a significant advancement in enterprise AI, boosting the instruction-following accuracy of paired Large Language Models (LLMs) by up to 50% and ensuring guaranteed quality, reliability, and observability. This technology transcends the limitations of traditional LLMs and Large Reasoning Models (LRMs), setting a new benchmark for AI capabilities.
Maestro delivers a substantial improvement in LLM performance on complex tasks. It elevates the accuracy of models like GPT-4o and Claude Sonnet 3.5 by up to 50% and empowers reasoning models, such as o3-mini, to surpass 95% accuracy. Notably, Maestro bridges the performance gap between non-reasoning and reasoning models, aligning the accuracy of Claude Sonnet 3.5 with advanced reasoning models like o3-mini.
While enterprises are eager to integrate AI into their operations, large-scale generative AI deployments often falter. According to the Amazon Web Services (AWS) CDO Agenda 2024, only 6% of organizations have a generative AI application in deployment, highlighting the fundamental limitations of current AI solutions for mission-critical tasks. The prevailing approaches—“Prompt and Pray” and hard-coded chains—present significant challenges. The “Prompt and Pray” method, which relies on LLMs and LRMs to execute open-ended tasks, lacks control and reliability due to the probabilistic nature of these models. Hard-coded chains, while more predictable, are rigid, labor-intensive, and prone to failure under changing conditions.
Reasoning models, designed to solve complex tasks through thinking tokens, have not alleviated these issues. They exhibit inconsistent performance, struggle to adhere to instructions, and fail to reliably utilize tools. Consequently, none of these approaches delivers the accuracy, reliability, and adaptability essential for widespread enterprise adoption.
“Mass adoption of AI by enterprises is the key to the next industrial revolution,” said Ori Goshen, Co-CEO of AI21. “AI21’s Maestro is the first step toward that future – moving beyond the unpredictability of available solutions to deliver AI that is reliable at scale. Delivering complex decision-making with built-in quality control, it enables businesses to harness AI with confidence. This is how we bridge the gap between AI potential and real-world solutions.”