Hyta is a platform that scales data contributions and compounds frontier capabilities for AI post-training across industries. It provides trusted human intelligence and a post-training ecosystem to shape the future of AI.

Hyta is an AI agent work experience marketplace that scales data contributions and compounds frontier capabilities for AI post-training across industries. The platform provides a trusted ecosystem where AI developers, researchers, and enterprises can capture, trade, and license authentic agent work experience. By transforming everyday agent interactions into high-fidelity training assets, Hyta accelerates the development of more capable and reliable AI systems. The core value lies in treating agent experience as a tradeable commodity, allowing organizations to iterate faster without relying solely on synthetic or human-annotated datasets. This post-training ecosystem shapes the future of AI by making every task execution a valuable learning resource.

Developing robust AI agents traditionally requires massive amounts of human-curated training data or simulated environments that fail to capture real-world complexity. Agents struggle with edge cases, tool usage, and multi-step workflows because their training data lacks authentic, in-the-wild experiences. Hyta solves this by offering a direct pipeline for post-training using actual agent execution traces captured natively. Instead of reconstructing events from logs or relying on manual review, teams can access verified, high-fidelity work experience obtained in real time. This eliminates the gap between controlled training and production performance, enabling agents to learn from the very scenarios they will face. The result is faster iteration cycles and models that generalize better across diverse domains.

Hyta's Native Capture feature tracks agent activity in real time as work is performed, never relying on post-hoc reconstruction. Every keystroke, API call, and decision path is recorded with complete fidelity, preserving the full state and sequence of actions. Unlike traditional logging that loses context, native capture provides granular visibility into agent behavior. For teams building more capable agents, this raw data is invaluable for identifying failure modes, optimizing workflows, and training on rare but critical edge cases. The real-time aspect allows immediate feedback loops—if an agent makes a mistake, the trace is available instantly for debugging. This feature directly supports the platform's promise of High Fidelity, giving developers the detailed insight they need to iterate rapidly and ship more reliable agents.

Full Coverage ensures that Hyta captures work experience across every domain and workflow type, from mundane daily tasks to specialized, multi-step processes. Whether an agent is composing code, managing customer inquiries, or orchestrating cloud infrastructure, its actions are recorded uniformly. This breadth is critical because agent performance often degrades in specific subdomains where training data is thin. By covering all contexts, Hyta provides a comprehensive dataset that reflects the agent's true operational range. Teams can then analyze strengths and weaknesses, identify patterns across different environments, and fine-tune models accordingly. The Works Everywhere engine integrates seamlessly with existing stacks, turning routine operations into a continuous stream of training-ready intelligence.

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