QA, scorecards & human handoff
Keep your agents good and keep a human on hand for the hard cases. Mirakash scores every conversation with LLM-judge scorecards, flags issues by rule into a review queue — plus human-in-the-loop escalation that routes a hard case to a human provider or another agent and resumes the caller.
Agent quality drifts silently until customers complain
Nobody reviews ten thousand calls by hand, so bad answers slip through unseen, the same failure repeats, and there's no path for the one call the agent truly can't handle. The first sign of a problem is a churned customer.
The flow, end to end
Score
Each conversation is graded by an LLM judge against your scorecard the moment it ends.
Flag
Flagging rules open an issue on any call that breaches a threshold and queue it for review.
Escalate
A case the agent can't close routes to the human-in-the-loop queue for a provider or agent.
Resume
The human answers; the agent takes the answer back to the caller and continues the call.
What's in the box
LLM-judge scorecards
Every conversation is scored by an LLM judge against your rubric — no manual sampling.
Flagging rules
Rules flag conversations that breach a threshold and open an issue for review.
Review queue
Flagged calls land in one queue for a human to review, confirm, or dismiss.
Human-in-the-loop
Hard cases escalate to a queue that routes to a human provider or another agent.
Consult-and-resume
The human answers, and the agent resumes the caller — a consult, not a blind transfer.
Human-in-the-loop that answers the agent, not takes over the call
When an agent hits a case it can't close, it escalates to a queue that routes to a human provider or another agent, gets the answer, and resumes the caller itself — a consult-and-resume loop, not a blind transfer that drops the customer into a cold hold.
- ✓Escalations route to a human provider or another agent
- ✓Consult-and-resume: the caller stays with the agent
- ✓Every escalation is a tracked, resolvable record
Score every call, flag the bad ones, review what matters
An LLM judge grades every conversation against your rubric, flagging rules open issues on the calls that breach a threshold, and a review queue puts exactly those in front of a human. What you learn feeds back into the agent — a flywheel, not a one-time audit.
- ✓LLM-judge scorecards on every conversation, no sampling
- ✓Rule-based flagging opens issues into a review queue
- ✓Findings feed back into the agent's instructions
Analytics & dashboards
Turn every conversation into insight — containment, escalation, sentiment, duration, and cost per agent.
Learn moreWorkflows & automation
An event-driven, node-graph engine that turns any signal into the right action, automatically.
Learn moreAgent builder
Design a voice or chat agent with no code — persona, voice, knowledge, tools — and test it live in the browser.
Learn moreReady to put an AI agent on every call?
Book a walkthrough and see the voice pipeline, telephony, workflows, QA, and human handoff working together — on one platform.