If you can measure it, Converra can optimize for it. These are the most common use cases and optimization goals teams bring across Output Quality, Behavior, Deployment, and Performance.
Get reliable, grounded responses.
Ungrounded claims that erode trust and create liability
KPIs: Groundedness score, citation accuracy
Agent ignores or misuses available retrieved context and sources (RAG: retrieval-augmented generation)
KPIs: Context coverage, answer supported by context rate
Structured outputs from the agent break downstream systems
KPIs: Parse success rate, schema compliance
Wrong tools, bad arguments, failed executions
KPIs: Tool success rate, argument validity
Agent ignores or partially follows user instructions
KPIs: Instruction compliance rate, constraint adherence
Keep your agent within bounds.
Conversation state breaks, forgets constraints, contradicts itself
KPIs: Contradiction rate, state-consistency score
Agent refusal behavior is too strict or too permissive on policy boundaries
KPIs: False refusal rate, safe-helpfulness score
Agent takes actions beyond its intended scope
KPIs: Scope adherence, escalation rate
The agent stays within safety and compliance guidelines
KPIs: Policy violation rate, safety score
The agent maintains voice consistency across interactions
KPIs: Brand alignment, tone consistency
The agent knows when to hand off to humans vs. keep trying
KPIs: Escalation accuracy, false escalation rate
Responses are too verbose or too terse for the context
KPIs: Length appropriateness, user satisfaction
Ship changes with confidence.
Change prompts without breaking what works
KPIs: Regression rate, A/B lift
The metric that matters: did the user succeed?
KPIs: Task success rate, resolution rate
Switch models without breaking behavior
KPIs: Cross-model parity, migration success rate
Track what changed and safely rollback if needed
KPIs: Version comparison, rollback frequency
Keep your agent fast, cheap, and stable.
Agent performance degrades as models update and usage shifts
KPIs: Week-over-week metric stability
Token usage spikes without clear visibility into the cause
KPIs: Cost per conversation, tokens per turn
Response times creep up and hurt user experience
KPIs: p50/p95 response time
The same inputs produce different outputs across runs
KPIs: Response variance, determinism score
Converra works with any AI agent. These playbooks show how teams apply the use cases and optimization goals above to specific agent categories.
Improve deflection rates and resolution accuracy without risking regressions.
View playbookOptimize qualification and conversion without breaking what works.
Get notifiedIncrease activation and completion rates through guided experiences.
Get notifiedPlaybooks are rolling out progressively. The product is not limited to these categories—Converra works with any AI agent.
CSAT, NPS, conversion rate, escalation quality, custom evals—if you can score it, Converra optimizes for it.
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