Customer support · Production

Fundrise resolves 50% of support volume with Intercom's Fin AI agent

The problem

Fundrise's Investor Relations team handled all support via email and phone with no chat capability, fielding questions ranging from basic account issues to complex investment inquiries. Routine low-complexity questions consumed resources that should have been spent on high-value cases, creating an unsustainable load and forcing trade-offs between response speed, quality, and team size.

Workflow diagram · grounded in source
1
Customer submits support question
trigger
“The questions we get range from being incredibly high-level, like "What is Fundrise?," to the typical support requests around password resets, to complex questions around our investment strategy and property underwriting.”
2
Fin trained on existing content
ai_action
“we quickly trained Fin on our existing help center content, investor updates, and marketing site”
3
Phased rollout with metric monitoring
validation
“Being able to monitor the success metrics as we rolled Fin out to bigger and more important audiences gave us the confidence we needed to execute quickly. It also helped to ensure that the answers being provided were right and actually m…”
4
Fin handles low-complexity cases
ai_action
“We engaged Intercom specifically to use its AI Agent Fin as a way of handling those low-complexity cases”
5
Complex cases routed to IR team
human_review
“carving out sufficient resources for our team to spend on providing thoughtful answers to the questions that warranted them”
6
Accuracy improvement feedback loop
feedback_loop
“our Product and Investor Relations teams have worked together to take the accuracy of Fin's responses from 80% to north of 95% – with zero technical resources required”
Reported outcome

Less than three months after launching Fin, more than 50% of Fundrise's total support cases are handled by AI.
During the seasonal tax spike Fin fielded almost the entirety of the volume, yielding a nearly 50% year-over-year reduction in cases. Fin's response accuracy improved from 80% to north of 95% without any technical resources, and the tool reshaped Fundrise's hiring roadmap for the Investor Relations team.

Reported metrics
support cases resolved by Finmore than 50%
Year-over-year case reduction during seasonal spikenearly 50%
Fin response accuracy improvementfrom 80% to north of 95%
Time to resultsless than three months
Show all 5 reported metrics
support cases resolved by Finmore than 50%
year-over-year case reduction during seasonal spikenearly 50%
Fin response accuracy improvementfrom 80% to north of 95%
time to resultsless than three months
hiring selectivitymuch more selective about how and when we grow the team
Reported stack
IntercomFin
Source
https://www.intercom.com/customers/fundrise
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Less than three months after launching Fin, more than 50% of Fundrise's total support cases are handled by AI.

What tools did this team use?

Intercom, Fin.

What results were reported?

support cases resolved by Fin: more than 50%; Year-over-year case reduction during seasonal spike: nearly 50%; Fin response accuracy improvement: from 80% to north of 95%; Time to results: less than three months (source-reported, not independently verified).

How is this customer support AI workflow structured?

Customer submits support question → Fin trained on existing content → Phased rollout with metric monitoring → Fin handles low-complexity cases → Complex cases routed to IR team → Accuracy improvement feedback loop.

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