Relevance AI
Relevance AI
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Every low score answered, not just counted

The CSAT Responder follows up on every low rating, works out whether the agent or the product let the customer down, and routes the fix to whoever can actually make it.

CSAT · 1 of 5 · “took forever”
CSAT Responder

A 1-star score with a comment. Reading the whole ticket before I reply, so the follow-up is real.

Reading the ticket thread and the CSAT comment4s

The eventual answer was correct and the customer confirmed it worked. The frustration is the two-day wait for a first reply.

Confirming the response timestamps2s

First response was 51 hours. That is the thing to own, not the resolution.

Sending a recovery reply that names the delay3s
Followed up properly. The answer was right, but the first reply took 51 hours, so my recovery message owns that delay specifically, apologizes for the wait rather than the outcome, and offers a direct line if it happens again. A generic “sorry you were unhappy” would have missed the actual grievance. The driver is logged as slow first response.

How it works

CSAT · 1 of 5 receivedCSAT · 2 of 5 · commentLow chat ratingWeekly CSAT roll-up
Recovery reply sentDriver logged for trendsProduct gap routed, not the agentHollow apology withheld

Triggered by low CSAT ratings

The moment a low score lands in Zendesk, the agent pulls the ticket behind it and reads what actually happened.

Separates the miss from the gap

It works out whether the score reflects handling the team could improve or a product limitation no agent could fix, and routes the theme to whoever can actually act on it.

Recovers or records

A genuine grievance gets a recovery reply that names the specific failure. A resolved, comment-less score gets logged for trends, not a hollow apology.

Without Relevance

With Relevance

Low scores pile up in a dashboard nobody has time to act on.

The agent reads the ticket behind every low score and follows up while the frustration is still fresh.

A templated “sorry to hear that” goes out that names nothing the customer actually said.

The agent reads what went wrong and writes a recovery reply that owns the specific failure.

A low score reflects on the agent, whether or not the agent could have done anything.

The agent tells apart a handling miss from a product gap and routes the theme accordingly, without blaming the wrong party.

Only a sampled handful of low scores ever get a human follow-up.

Every low rating gets read and handled, not just the ones a manager spot-checks.

Whether a detractor hears back at all depends on who owns the queue that week.

The same follow-up and the same driver analysis on every low score, week after week.

An automated apology fires on every low score, even when nothing is left to fix.

When the issue is resolved and there is no comment to act on, the agent logs it rather than sending a hollow apology.

Held to a quality bar, on every run

Every follow-up is checked against eval test cases written for this exact job before it reaches the customer. If a run fails the bar, it never ships.

CSAT Responder
92959890

Sampling 2% of live runs · 92% passing this week

Recovery replies name the real failure
96%
Product gaps are not blamed on the agent
93%
Every low score is read, not sampled
87%
No hollow apology on a resolved ticket
91%

Shaped by your team, not a template

Experts and engineers tune CSAT Responder to your playbooks. Every change ships through the same evals.

Drag and drop

Compose agents and workforces on a visual canvas. Drag in agents, tools, and approvals in a flow anyone on the team can read.

Drag and drop

Compose agents and workforces on a visual canvas. Drag in agents, tools, and approvals in a flow anyone on the team can read.

Build with AI

Describe the agent in plain language and Invent builds it: the prompt, the tools, and the evals to prove it works.

Build with AI

Describe the agent in plain language and Invent builds it: the prompt, the tools, and the evals to prove it works.

Build with MCP

Engineers drive the same platform from Claude Code, Codex, or Cursor. Create agents, link knowledge, and run evals over MCP.

Build with MCP

Engineers drive the same platform from Claude Code, Codex, or Cursor. Create agents, link knowledge, and run evals over MCP.

Built for enterprise teams

Run agents on your real data with the access controls, audit trails, and residency guarantees enterprises require all built in.

AICPASOC 2TYPE II
SOC 2
GDPR
GDPR

Security & data privacy

  • Data residency
  • PII masking
  • Audit logs
  • No training on your data

Access & controls

  • Role-based access control
  • SSO / SAML
  • Human-in-the-loop approvals
  • Version control

Monitoring & oversight

  • Real-time monitoring
  • Full agent tracing
  • Cost visibility
  • OTEL & Delta Share export
KPMG
"The ability to be vendor agnostic and the ability to scale across a breadth of functions is a really key feature."

Levi Watters

Partner, KPMG Australia

Read more
Autodesk
"The key for us was how we can modularize industry knowledge and the best playbooks, and apply it."

Allen Roh

Senior Marketing Manager, Autodesk

Read more
Canva
"We're looking for every place where AI can allow sellers and customer success reps to be more engaged with customers."

Rob Giglio

Chief Customer Officer, Canva

Read more
"The ability to be vendor agnostic and the ability to scale across a breadth of functions is a really key feature."

Levi Watters

Partner, KPMG Australia

Read more

Team it up with more customer support agents

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Knowledge Base Writer

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Bug Report Triager

Reproduces reports and files clean engineering bugs.

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Reprioritizes the queue before an SLA breaks.

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Voice of Customer

Synthesizes the week of tickets into clear themes.

Hi Sam, you’re right that the export failed. Here’s the fix and why it happened.

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Reply Drafter

Drafts on-brand replies for an agent to send.

Every agent you add shares one stack

These agents all run on one platform: one gateway, one router, one eval suite, one audit trail. Every agent after the first ships faster.

  • Triggered by key events or signalslike Zapier
  • Given access to contextlike Zep
  • Connected to your appslike Composio
  • Access to all LLMslike OpenRouter
  • Performance evaluatedlike Braintrust
  • No-code agent builderlike Dust.tt
  • Coordinated into teamslike CrewAI
  • Kept alive through long-running worklike Temporal
  • Traced at every step of every runlike Langfuse

Put the CSAT Responder to work this quarter

We partner with enterprise teams to take this work off their plate. An agent built with you, proven against your quality bar, and live in weeks.