AutoSynthData: Generating Training Data for Enterprise Agents
ServiceNow CoreAI has developed AutoSynthData, a pipeline that converts model capability gaps into high-quality training data for enterprise agents. The system generates feasible and realistic tasks by analyzing target model failures and leveraging stronger teacher models to identify learning needs. This approach allows for the continuous refinement of agent performance by focusing on specific weaknesses within complex enterprise environments.
- ▪AutoSynthData uses a target model's failures and a stronger teacher's successes to determine what the model should learn next.
- ▪Generated tasks must satisfy three properties: feasibility, realism, and difficulty relative to the current agent's capabilities.
- ▪The verifier component ensures consistency, soundness, and completeness to reliably check if an agent successfully completed a task.
- ▪The pipeline was illustrated using the EnterpriseOps Gym environment and its released dataset.
- ▪High-quality synthetic data requires both sample-level verification and repair as well as batch-level review.
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| Original publisher | Hugging Face - Blog |
| Canonical URL | https://huggingface.co/blog/ServiceNow-AI/autosynthdata |
| Publication time | Fri, 02 Oct 2026 04:01:31 GMT |
| Retrieval time | 2026-10-02T04:05:43.928Z |
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Back to Articles AutoSynthData: Generating Training Data for Enterprise Agents Enterprise Article Published October 2, 2026 Upvote - Esakkivel Esakkiraja esakkivel Follow ServiceNow-AI Shruthan Radhakrishna shruthan-r Follow ServiceNow-AI Denis Akhiyarov dtanow Follow ServiceNow-AI Sagar Davasam davasam Follow ServiceNow-AI What makes a useful agentic task? System specification Agent-facing task Verifier Overview From model failures to a curriculum Generating and scaling tasks Target Multiply Implementation details High-quality synthetic data needs more than generation Sample-level verification and repair Batch-level review Moving the training frontier EnterpriseOps Gym experiments Hybrid Hybrid results ITSM Closing the loop Enterprises need agents that work well in their own…
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