Halluminate

Sepal is a data research company on a mission to advance human knowledge and capabilities through safe AI. We partner with the world’s leading AI labs and enterprises to help their models get better at the tasks people actually want them to do. We’ve built a Cloud-Native Agent Dataset Factory which turns the process of generating evaluation and training data from manual, inconsistent, and labor-intensive into something automated, standardized, and scalable. Sepal AI was founded in 2024 by engine

shared extracted concepts: enterprises; shared product terms: model, labs, enterprise, train; same category: AI agents; shared affiliation: Y Combinator

BioStack is building the data engine for healthcare and drug discovery AI. The bottleneck is not models. It is access to high-quality biological data. Clinical and experimental data is fragmented, unstructured, and locked inside hospitals, labs, and CROs, while generating new data is slow and expensive. BioStack fixes this with proprietary clinical and preclinical data pipelines that turn real biomedical workflows into ML-ready training environments. We structure longitudinal multimodal data acr

shared product terms: bottleneck, model, high, quality; shared affiliation: Y Combinator

At Zumo Labs, we generate synthetic training data for computer vision models. Computer vision is the essential technology that powers the products of the future: autonomous vehicles, smart retail, robotics, smart fitness, security and vision-based analytics. These algorithms require huge amounts of training data. This data is currently collected and labeled manually; a slow, imprecise, expensive process that is rife with bias and privacy issues. Zumo Labs solves all of these problems (and more!)

shared extracted concept terms: computer; shared product terms: model, labs, train, computer; shared affiliation: Y Combinator

One Robot builds simulation environments that are realistic to see and realistic to interact with, so robotics teams can train and evaluate robot policies without being bottlenecked by robot time. Today, improving a VLA often means more real-world hours: setting up the scene, running trials, resetting, and repeating. This loop is slow, expensive, and hard to scale. For example, material handling and manufacturing assembly tasks, models need far more training and evaluation data than teams can co

shared product terms: model, train, real, today; shared affiliation: Y Combinator

Scope AR is the pioneer of enterprise-class augmented reality (AR) solutions, delivering AR tools for getting workers the knowledge they need, when and where they need it. Scope AR is revolutionizing the way enterprises work and collaborate with intuitive augmented reality tools that deliver the real-time knowledge sharing needed to conduct complex remote tasks, employee training, product and equipment assembly, maintenance and repair, field and customer support, and more. Remote AR Remote AR is

shared extracted concepts: enterprises; shared product terms: enterprise, train, knowledge, worker; shared affiliation: Y Combinator

Panels is an audio data platform that delivers high-quality speech datasets from vetted, diverse contributors to power training and evaluation of foundational voice models.

shared product terms: model, train, deliver, high; shared affiliation: Y Combinator