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.
A 1-star score with a comment. Reading the whole ticket before I reply, so the follow-up is real.
The eventual answer was correct and the customer confirmed it worked. The frustration is the two-day wait for a first reply.
First response was 51 hours. That is the thing to own, not the resolution.
How it works
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.
Sampling 2% of live runs · 92% passing this week
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.
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

"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
"The key for us was how we can modularize industry knowledge and the best playbooks, and apply it."
Allen Roh
Senior Marketing Manager, Autodesk
"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
"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
Team it up with more customer support agents
Ticket Resolver
Resolves routine tickets, escalates the rest.
- 1Reproduced the issue
- 2Checked open issues
Filed · clean repro
Bug Report Triager
Reproduces reports and files clean engineering bugs.
SLA Watchdog
Reprioritizes the queue before an SLA breaks.
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.


