Support answer drafting
Support answer drafting gives an agent a first reply instead of a blank box. It searches previous resolutions, the help documentation and the engineering tickets behind known issues, then drafts a reply with the sources attached so the agent can check it in a glance. Every reply is approved by a person before the customer sees it.
Step by step
Read the incoming ticket
The ticket reaches the agent through the connection agreed in the co-build, along with the customer's earlier history.
Match against past resolutions
Similar tickets that were resolved, and the replies that resolved them, are pulled together with the documentation that applies.
Check the known issues
Open engineering tickets covering the same problem are checked, so a customer is not told to reinstall something that is already a known bug.
Draft the reply with sources
A reply is written in your support tone with each claim linked to the resolution or page behind it.
Say when it does not know
Where nothing matches, the agent says so and marks the ticket for a human rather than producing a confident guess.
Support agent approves every reply
The draft sits in the queue until a support agent has edited and approved it. Nothing reaches a customer unapproved.
Exactly what this agent can see, touch and change
The same five controls sit behind every ollo agent. These are this one's settings — visible before you build it, not buried in an admin screen afterwards.
Context
What reaches the modelSupport teams answering the same questions in slightly different words all day, and new agents who do not yet know where the answer lives.
Escalation
When it asks a personA support agent approves every reply before it reaches the customer
Applications & Rights
Which tools it uses, and what it may do in each
ConfluenceRead only
NotionRead only
JiraRead only
SlackRead only
ZapierWrites newCreates new records or documents. Never edits, moves or deletes anything that was already there.Verification
How you know it’s rightEvery claim links to the document it came from. A statement the agent cannot cite does not make it into the output — which is what makes the result reviewable in minutes rather than re-read end to end.
Who it’s for
Support teams answering the same questions in slightly different words all day, and new agents who do not yet know where the answer lives.
What you’ll need
- Helpdesk connected through Zapier
- Resolved ticket history available
- Support tone and templates supplied
- Approval queue agreed with the team
What you get
- A drafted first reply
- The sources behind each answer
- A flag when no match exists
What it doesn’t do
It drafts; it never sends. It does not issue refunds, change an account or promise a fix date, and where nothing matches it says so rather than inventing an answer.
We build the first one with you
Not a template you configure alone. We sit with your team, build it on real data, and hand over the controls.
Scope
One session with the people who actually do the work. We agree what the agent reads, what it may write, and who approves.
Co-build
Built on your own data, not a sandbox. You watch it being made, so you know why it behaves the way it does.
Handover
You own the controls. Change the context, tighten the rights, move the approval gate — without coming back to us.
Parts of the work currently spread across the categories below. It does not replace any of those products outright.
Frequently asked
How does it connect to our helpdesk?
Through the Zapier connection we set up together, since that is what carries the ticket in and the draft back. Which fields move in each direction is agreed during the co-build and stays in your control afterwards.
What stops it inventing a workaround?
It only drafts from resolutions and documentation that exist, and each claim in the draft carries its source. Where there is no source it hands the ticket to a person instead, which is the behaviour that keeps the queue trustworthy.
Can it handle an angry customer?
It drafts in your support tone, but a complaint that needs an apology or a commercial decision is flagged for a human rather than answered. Judgment about a relationship is not something to hand to a draft.
Does it learn from the edits our agents make?
Approved replies become part of the resolution history it searches, so the wording your team actually uses is what it draws on next time. That happens because the approved reply is stored, not because the model is retrained on your data.