One scorecard
The same rubric for an AI agent and a person, so the comparison means something.
Platform / AI agent management
Palera ranks every AI agent you run, from any vendor, against the people doing the same work, on your conversations and your QA form. Most AI vendors grade their own homework on their own conversations.
The AI scores every closed conversation on your rubric. A manager overrides, and the override is what trains the agent.
How a score becomes training
In Palera, your AI QA agent scores every closed conversation against your QA form, and a manager reviews, overrides and approves the score before anything trains the model.
What the benchmark shows
Ranking agents on a single criterion, such as speed or empathy, often reverses the order an overall average shows. Two agents can look level overall and be nothing alike underneath. Speed and empathy are different skills, and almost nothing is good at both. Palera can show this because every agent, AI and human, writes to one conversation record.
With a ranking per criterion, a contact center can route the work that rewards speed to one set of agents and the work that rewards empathy to another. Resolution times fall and CSAT climbs, and neither result is a trade you had to guess at.
Why this is rare
Nearly every AI vendor will show you their agent's analytics. Very few will run a competitor's agent at all, and the quality platforms that do are not your contact center. Palera is both a contact center and a platform that runs any vendor's agent, which is why the comparison is possible in Palera and almost nowhere else.
Palera gives AI agents and people one scorecard, a human review of every score, vendor evidence from your own conversations, and scoring on every conversation instead of a sample.
The same rubric for an AI agent and a person, so the comparison means something.
Every score is reviewable and every override is recorded before it trains anything.
Decide which AI vendor to keep using your conversations, not their demo.
Every conversation is scored, not the 2% a QA team can listen to.
Run your current AI vendor inside Palera for a month and see how it scores against your floor.
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