InternalAutomation

Case Study · SaaS

Deflecting half the ticket queue for a SaaS company

An AI support layer reading docs and account data deflected 54% of tickets, cut first-response time 60%, and let support scale with the customer base instead of headcount.

Client
A B2B SaaS company, ~9,000 customers
Market
Remote, US
Timeline
5 weeks to launch

Anonymized and illustrative of a typical engagement.

54%
of tickets deflected
−60%
first-response time
+22
CSAT points
5 wks
to launch

01 / The challenge

Where the time was going

  1. 01As the customer base grew, the ticket queue grew with it, and most tickets were 'how do I' questions already answered somewhere in the docs. Support was effectively a live search engine for the knowledge base.
  2. 02First-response times slipped as volume rose, which dinged CSAT even when the eventual answers were good.
  3. 03The knowledge base existed but was underused because customers found it faster to just open a ticket.

02 / The build

What we shipped

We put an assistant in front of the queue that actually reads the docs and the customer's own account state.

  1. 01Docs-grounded answersThe assistant answers from the live knowledge base and product documentation, with citations, instead of guessing.
  2. 02Account-aware responsesIt reads read-only account and product data to answer account-specific questions accurately.
  3. 03Confident deflectionRoutine questions resolve in-channel; anything uncertain or complex is escalated with full context.
  4. 04Docs feedback loopCommon unanswered questions are surfaced so the team can improve the docs, which compounds deflection over time.

03 / The results

What changed

Support scaled with customers, not with headcount.

The assistant deflected 54% of tickets and cut first-response time 60%, lifting CSAT by 22 points. Agents moved to the complex tickets that need product knowledge, and the docs got measurably better as a side effect.

54%
tickets deflected
−60%
first-response time
+22
CSAT points

Our support team finally works on the hard problems, and customers get instant answers to the easy ones.

VP Customer Success, SaaS company

05 / FAQs

Questions about this build

Does it make up answers?

No. It answers from your live docs and account data with citations, and escalates when it is not confident.

Does it get better over time?

Yes. Unanswered questions are surfaced to improve the docs, which raises deflection without extra agent effort.

Want a result like this for your team?

Name the work that is costing you the most time. We will map the build, show what is worth doing first, and what it costs. If there is no fit, we will say so.