Evaluate AI and human agents against your own quality standards, by role, across every conversation — with recommendations that improve your AI.
| Founded year: | 2026 |
| Country: | United States of America |
| Funding rounds: | Not set |
| Total funding amount: | Not set |
Description
Agent Insight is a quality evaluation layer for teams running AI agents, humans, or both.Most quality programs run on borrowed standards — a generic QA scorecard, or an AI vendor's own opaque score, checked against 2% of conversations. Agent Insight inverts that: you define the metrics in plain language — resolution quality, CSAT, compliance, tone, escalation discipline — and every conversation is scored against them.
Standards are role-based, because a billing specialist and an escalation engineer shouldn't share a rubric. Each role's standard applies to whoever holds it, AI or human, so both sit side by side in one system.
Every score is auditable, with timestamped examples and specific recommendations on what should have happened. Findings route into Evolve, Aissist's optimization layer, closing the AI loop: your AI learns from the agents scoring best under your standards.
Works with Intercom Fin, Zendesk, Freshdesk, Kustomer, Front and Gorgias. About 10 minutes to start.
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