AGENTUM provides a reliability layer for AI agents operating in production, observing every step across frameworks and vendors to diagnose failures and automatically repair them. The platform classifies incidents into four failure families—hallucinated outputs, broken tool calls, context loss, and orchestration errors—and offers continuous reliability scoring with audit-grade reports for regulated industries. Integration requires only a base-URL swap or two-line SDK wrap, with no agent rewrite needed.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents in production fail frequently due to hallucinated outputs, broken tool calls, context loss, and orchestration errors, yet these incidents are typically handled with one-off scripts and human intervention that negate the economics of automation. This reliability gap is the primary barrier to scaling agentic AI systems.
Solution
AGENTUM provides a vendor-neutral reliability layer that observes every agent step, tool call, and token in production, then automatically diagnoses failures and repairs them. The platform classifies incidents into four failure families, executes corrected retries, restores lost context, and re-grounds outputs—only escalating to humans when confidence thresholds are not met. It integrates via a base-URL swap or two-line SDK wrap, requiring no agent rewrite, and works across any framework, model, or provider. The system also delivers continuous reliability scoring and audit-grade reports for regulated industries.
Target Audience
Primary customers are engineering teams and platform operators at enterprises deploying AI agents in production who need automated failure detection, diagnosis, and repair across heterogeneous AI stacks.
Features
- Full tracing of every agent step, tool call, and token across any framework or provider
- Automated root-cause classification into four failure families: hallucinated outputs, broken tool calls, context loss, and orchestration errors
- Replayable incident timelines for detailed post-mortem analysis
- Corrected retries and context restoration with human escalation only below confidence thresholds
- Continuous reliability scoring and audit-grade reporting for compliance with EU AI Act and SOC 2
- Vendor-neutral integration requiring only a base-URL swap or two-line SDK wrap