Customer Stories

SaaS support teams that closed their backlogs.

Early customers share what autonomous resolution looks like in practice — the numbers, the surprises, and the tickets they'll never have to answer manually again.

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Case Studies

Real deployments, real results.

Stackfield · Project management SaaS

88% of billing tickets handled without a human — in week one.

Stackfield's two-person support team was processing 40–50 billing tickets daily — duplicate charges, failed payment retries, invoice resends. Every ticket was structurally identical. Their Zendesk macro library had 14 billing templates. Despite the templates, average handle time on billing tickets was 9 minutes because agents still had to cross-reference the billing system, verify the charge, and personalize the response. The work wasn't hard; it was just relentless.

88%Billing ticket deflection
3.2 minAvg resolution time
1 daySetup to first resolution
We were drowning in billing tickets. Resolvemark took 88% of them off the queue in the first week. My team went from firefighting to actual product thinking. — Marcus Chen, Head of Support
Circula Labs · Expense management SaaS

92% FCR on onboarding Q&A — the hardest category to automate.

Circula Labs ran a strong Intercom setup with solid routing and CSAT discipline — but their onboarding FCR sat at 54%. New users asked the same "how do I configure X" questions repeatedly. The answers were in a 200-page Notion knowledge base, but agents were using it inconsistently: different agents found different sections, cited different page numbers, and gave conflicting answers. The KB existed; the problem was reliable retrieval at scale.

92%FCR on onboarding Q&A
62%Reduction in human touches
4.7/5CSAT on auto-resolved tickets
The escalation logic is what sold us. We can tune exactly when a human takes over — it's not all-or-nothing like the big platforms. — Priya Nair, VP Customer Success
Rethink Commerce · E-commerce SaaS

In production within 3 days. No integration project.

Rethink Commerce had piloted two other AI support tools in the previous 18 months. Both required 4–6 week integration projects with engineering involvement, and neither reached production use — the team ran out of runway before reaching go-live. Their support ops lead needed a tool that could work with existing Intercom and Notion infrastructure without opening a ticket with the dev team.

3 daysSetup to production
79%Subscription ticket FCR
0Integration engineers needed
Setup took half a day. We connected our Intercom inbox, pointed it at our Notion knowledge base, and it was triaging tickets the next morning. — Jamie Sousa, Support Ops Lead
Brixa Analytics · BI & data SaaS

Escalation policies that actually build customer trust.

Brixa Analytics served a mix of SMB and enterprise accounts, both in the same Zendesk queue. Enterprise customers on $24K+ annual contracts had contractual expectations of human support for any escalation. But 70% of tickets across the board were routine — billing lookups, export questions, user management. Brixa needed to automate the routine tier without accidentally routing an enterprise escalation to an agent, ever.

85%Overall FCR rate
100%Enterprise escalations honored
+0.6NPS improvement post-deploy
For our enterprise accounts, every escalation rule fires correctly — no exceptions. For SMB and trial tickets, the agent closes them in minutes. It's the first tool that actually respects a tiered support model instead of forcing you to choose between full automation and no automation. — Daniel Osei, Director of Customer Success
Aggregate Results

Across all customers.

91%
Avg. first-contact resolution rate
4 min
Median agent resolution time
4.6
Avg. CSAT score on auto-resolved tickets
3 days
Avg. time to first live resolved ticket
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