- 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.--(BUSINESS WIRE)--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.”
From autonomous research to cumulative scientific discovery
PRAXIST deploys multiple autonomous research peers to explore approaches in parallel, test hypotheses, investigate failures, and validate promising results. Unlike the tree-like search used by other similar systems, where each candidate inherits from one parent and weaker branches are pruned, PRAXIST uses a generation-layered research graph that preserves what every experiment teaches. This allows later generations to combine valuable mechanisms, evidence, and constraints across different lineages, including failed attempts. Rather than searching for the single best branch, PRAXIST constructs stronger solutions from discoveries made across branches.
Expansion and scale at speed
For organizations with limited AI or machine learning capabilities, PRAXIST can provide an AI research layer alongside existing domain expertise; for sophisticated teams, it can augment existing capabilities and increase the scale and breadth of R&D. A traditional robotics company, for example, can define problems, objectives, and constraints from an engineering perspective while PRAXIST conducts the AI research, experimentation, and validation needed to develop solutions, effectively serving as an in-house AI research team without requiring the company to build one.
Partner engineering results further illustrate this potential. In a partner-provided rocket-landing simulation, PRAXIST improved baseline to 100% within 12 hours, demonstrating a proof-of-concept capability at Technology Readiness Level (TRL) 3. In an industrial robotic SLAM problem, a partner team achieved 9.37cm of accumulated error after several months of development. PRAXIST reduced the error to 5.01cm within three days.
System application
PRAXIST can operate with proprietary data in private or customer-controlled environments, giving organizations greater control over their research infrastructure and sensitive intellectual property.
Initial applications are focused on sectors with intensive R&D requirements or highly measurable or simulatable optimization problems, including AI, engineering and robotics, manufacturing, finance, and health and drug discovery. Over time, Sapient Intelligence aims to extend PRAXIST beyond traditional R&D into broader business optimization, from inventory and sales to logistics and shipping.
“AI has mastered executing what we know. The next frontier is discovering what we don’t,” said Jin Li, Chief Scientist of PRAXIST. “PRAXIST is our first step toward making autonomous discovery a practical capability for organizations tackling complex problems. As we continue to develop the platform, we will look to expand beyond traditional R&D. Our ambition is to give organizations a fundamentally greater capacity to explore what is possible, enabling existing teams to pursue more experiments, approaches, and innovations while keeping human expertise and judgment at the center.”
About Sapient Intelligence
Founded and headquartered in Singapore, Sapient Intelligence is developing a new generation of AI systems that move beyond answering questions and executing predefined tasks to autonomously discover, reason, and optimize across complex problems without predefined solutions. By combining autonomous research systems with novel foundation-model architectures, Sapient Intelligence advances autonomous discovery through deeper reasoning, self-evolving capabilities, greater adaptability, and enhanced interpretability.
At the center of this vision is PRAXIST, the company’s flagship autoresearch system enabling breakthroughs in real-world R&D and business challenges. Sapient is also the creator of the Hierarchical Reasoning Model (HRM), a novel, brain-inspired foundation model architecture designed to enable deep reasoning with substantially greater training efficiency.
With a global team of more than 50 researchers and engineers operating across Singapore, Palo Alto, and Beijing, Sapient brings together experience from leading AI organizations and research institutions. The company connects foundational AI research with demanding applications in finance, healthcare, manufacturing, and logistics, developing original AI systems for enterprises, researchers, and institutions worldwide.
Learn more about PRAXIST here.
Contacts
The Hoffman Agency on behalf of Sapient Intelligence
Sapient@hoffman.com
