Sapient Intelligence Launches PRAXIST (Beta) to Accelerate a New Era of Autonomous AI-led Research and Development

• 49 gold-medal outcomes across 75 machine learning competitions from MLE-Bench achieving approximately US$3,000, versus 34 for Claude Code at US$38,000

• Rocket-landing accuracy reached 100% within 12 hours, demonstrating a proof-of-concept capability at Technology Readiness Level (TRL) 3

PALO ALTO, Calif., August 28, 2026--Singapore-headquartered artificial general intelligence research company Sapient Intelligence today announced the launch of PRAXIST (Beta), an autonomous AI research and development (R&D) system that takes on complex technical problems and independently tests and validates potential solutions.

While AI has rapidly accelerated productivity in content generation and other well-defined workflows, R&D remains inherently difficult to automate and scale. Breakthroughs require testing multiple hypotheses, learning from successes and failures, and continuously determining which paths to pursue. Organizations must address this all while balancing specialist expertise, time, cost, and infrastructure.

A capacity multiplier

PRAXIST addresses this challenge as an R&D capacity multiplier. Rather than executing a predefined path, it independently explores which technical approach can best achieve a measurable objective. Users define the goal, parameters, and budget; PRAXIST then autonomously experiments and evaluates the strongest solution.

The approach has demonstrated promising results in controlled internal evaluations. On 75 challenging Kaggle competitions from MLE-Bench, a benchmark designed to test how well AI systems tackle complex, real-world machine learning problems across, PRAXIST achieved the highest-level result in 49 competitions at an approximate recorded model cost of US$3,000, compared with 34 highest-level results for Claude Code at approximately US$38,000 under the same evaluation conditions.

"Unlike general coding agents, which are built primarily to execute a specific task, PRAXIST is designed for long-horizon R&D, where the problem-solving approach itself may need to be discovered and adapted," says William Chen, Co-Founder at Sapient Intelligence. "A conventional research team is ultimately constrained by the number of experiments its researchers can realistically run and evaluate. PRAXIST is designed to provide organizations with the ability to augment their existing teams with additional research capacity, enabling them to explore problems with a breadth and speed that would otherwise require significantly greater specialist resources."