Build and Deploy Production-Ready Agents at Enterprise Scale
OpenTrek is an end-to-end agent development platform that empowers enterprise developers to build across data, development, deployment, and operations. It provides agent development, runtime, operations, model training and inference, along with the gateway and execution environment.
Solutions
Orchestrate Intelligent and Autonomous Agents in Your Organization
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Rich Scenarios
Deploy faster with out-of-the-box role templates for various use cases such as R&D, financial and tax management, city operations, and more.
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Secure and Controllable
Run agents stably and securely in sandboxes 24x7 with self-evolving based on long-term and short-term memory.
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Asset Accumulation
Manage six types of AI assets (character templates, knowledge bases, skills, memory, tools, and prompts) centrally in one platform, and quickly turn workflows into reusable skills in Skills Hub.
Move AI Agents from Prototype to Production with Security, Elasticity, and Low Cost
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Unified Entry
AI Gateway provides one entry to all LLMs, with real-time Token observability and business-level billing.
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Secure and Easy to Use
AgentRuntime provides a production-grade sandbox for enterprises, 90% lower cost.
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Open Ecosystem
AI Open Platform (HiMarket) delivers one-stop operations for enterprise Agent assets.
Transform Dormant Data to AI-ready Knowledge Base for your organization
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Visible
Ingest and manage heterogeneous data from different sources through high-performance integration modules.
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Understandable
Understand and parse documents, tables, and business with accuracy.
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Regeneration
Transform data into AI-ready knowledge bases and datasets.
Large-scale Model Training and Efficient Fine-tuning
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Multimodal training
Perform model training on foundation models, industrial models, and sovereign models that support text, image, video, and audio.
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Fine-tuning algorithms
Reduce fine-tuning costs with built-in SFT, RL, and LoRA, and proprietary PVPO/VCRL.
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Efficient model evaluation
Evaluate models in multi-dimensions with root cause analysis and improvements on bad cases, achieving up to 95% human-AI evaluation consistency**.
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