Summarise long ticket histories
Bring the right context into Zendesk so agents can act without hunting through other tools.
Applied AI
Zendesk AI automation
Add AI where it helps, with explicit inputs, review steps and operational limits.
In plain English
What does zendesk ai automation mean?
Zendesk AI automation adds a focused AI step to a support workflow—for example, summarising a long conversation, drafting a reply or pulling out key details. We keep the task narrow, make review easy and decide in advance what happens when the output is uncertain.
Where it helps
Built around the way your team works.
Draft replies for agent review
Keep the useful controls close to the ticket and make each action clear before it runs.
Extract intent or structured fields
Fit the solution to your process instead of forcing the team around a generic app.
Route exceptional cases to a person
Test the idea with a small working version before you commit to the full build.
What you get
From a rough idea to something your team can use.
We start with the real workflow, not a long technical wish list. A small prototype often gives everyone something concrete to react to before the full build begins.
- 01
Use-case and risk definition
We start by watching the real workflow and agreeing what a useful first version should solve.
- 02
Prompt and data-flow design
You can review the experience early, while changes are still quick and inexpensive.
- 03
Agent review interface
The build includes the connections, permissions and safeguards the workflow needs.
- 04
Evaluation cases and monitoring
We test the awkward cases, help with launch and leave you with clear documentation.
Hands-on experience
Made by people who build for support teams.
Otisa builds custom Zendesk software and its own Zendesk products, including Promise. That means the advice comes from designing, shipping and looking after real software.
Explore Promise →The right tools for the job
We use Zendesk Apps Framework, APIs, JavaScript, TypeScript, React, databases and automation services where they genuinely help—not just because they are available.
Good to know
A few things teams usually ask.
Will AI send messages automatically?
Only if that is genuinely appropriate and you choose it. Most teams start with drafts, summaries or suggestions that an agent reviews before anything is sent.
Can we keep a human approval step?
Absolutely. Human review can be built into the interface so the AI helps with the work while your team keeps the final decision.
How do you test output quality?
We create a set of realistic examples, agree what a good answer looks like and track where the model succeeds or struggles. That gives us something concrete to improve.
Start with the problem
What do you wish Zendesk could do?
Show us the repeated task, missing connection or awkward workaround. You do not need a technical brief.
Talk through your idea →