Case Studies

Mar 31, 2026

How Wefunder Cut Response Time From 7 Hours to 15 minutes While Handling 2x the Volume

How Wefunder Cut Response Time From 7 Hours to 15 minutes While Handling 2x the Volume

From inbox overload to breathing room in four months.

From inbox overload to breathing room in four months.

Leonardo Maestri

IN this article

How Wefunder cut response times from 7 hours to 15 minutes while handling 2x the email volume, without adding headcount.

Snapshot

  • Company: Wefunder, equity crowdfunding platform connecting founders and investors

  • Challenge: 1k+ support emails per week, 7 hour average response time, no capacity for higher-impact work

  • Avg response time after Fini: 15 mins (down from 7 hours)

  • Volume handled: 2x previous capacity in the first two weeks

"Fini looks complex and complete. Not complex in a way that it's difficult to use, but complex in a way that you can tell they've thought about all the different things that need to be considered by an AI agents built for fintech.” - Kai

The Company

Wefunder is an equity crowdfunding platform that lets anyone invest in startups. They connect founders raising capital with everyday investors who believe in them.

Their Success team supports both sides of that equation, founders navigating raises and investors managing their portfolios. Every interaction carries weight. As Kai Moon, who leads the Success team, put it: the goal is to give every user an “11-star experience”, a bar borrowed from Airbnb’s philosophy of going far beyond what’s expected.

The Problem: Volume Without Capacity

Wefunder’s Success team was receiving 1,000+ emails per week. Questions ranged from routine how-tos to complex account actions: password resets, email unsubscribes, 2FA fixes, withdrawal inquiries. The kind of work that demands accuracy but consumes disproportionate time. The kind of work that’s necessary but repetitive.

Response times averaged around 7 hours. The team was maxing out at roughly 600 emails per week. There was zero capacity left for higher-value work: improving processes, building better experiences, or tackling the complex cases that actually needed a human.

“Every investor and founder deserves prompt, reliable support. But with the volume of incoming messages, we couldn’t do that dependably.” — Kai Moon, Success Team Lead

The team faced a binary choice: hire more people, or find a smarter way to handle the routine volume without adding headcount.

The Solution: What did Fini do?

Before Fini, Wefunder only had email support. If an investor had a question mid-investment or a founder needed help with their campaign, they'd send an email and wait, often ~7 hours for a reply.

Fini changed that on two fronts.

First, Fini plugged an AI agent into Front, Wefunder's help desk. It reads incoming emails, pulls answers from Wefunder's knowledge base, and either handles it or passes it to the team. Most routine stuff never needs a human.

Second, we set up live chat for founders through the Fini widget: giving Wefunder real-time support for the first time. Before this, there was no way for a user to get an instant answer. Now founders with critical questions about their withdrawals can get help in seconds, right where they are. Investors are next.

And critically, Fini doesn't just answer questions: it takes actions. Password resets, marketing unsubscribes, 2FA fixes, withdrawal-specific responses. Instead of telling users what to do, it actually does it for them.

And Wefunder's team stays in the loop the whole time. Escalation rules, keyword triggers, tone controls, and a shadow-testing mode meant they could see exactly how the agent would respond before it ever talked to a real user.

Why Fini

Kai joined Wefunder in September. By October, it was clear they needed responsive but sophisticated AI agent.

“I chose Fini because of its solid reputation, capacity for complexity, and history of working with fintech startups which need complete accuracy and strong compliance guardrails built into the product.” - Kai

They evaluated several AI support platforms and sat through demos with competitors. Fini stood out on four dimensions:

  • Depth of guardrails and escalation logic. Fini’s agent instructions, keyword handling, and content structure showed a level of thought that competitors hadn’t reached.

  • Maturity of the knowledge management system. The help center, article structure, and similar-questions engine were built with years of iteration behind them.

  • The Fini Rulebook. Most AI tools just reply. Fini's Rulebook combines LLM intelligence with deterministic rules, so the agent knows when to act and exactly how to execute with strong guardrails. Password resets, unsubscribes, 2FA fixes, withdrawal lookups: handled automatically, reliably, at scale.

  • Product maturity overall. As Kai noted: “The alternatives hadn’t been around as long. They were kind of thrown together. Fini has been around for several years.”

Implementation: Thorough by Design

Every phase was deliberate:

1. Prompts and guardrails. Writing and refining the instructions that control the agent's tone, actions, and escalation logic.

2. Complete knowledge base overhaul. The most intensive phase. Every existing help article was reviewed. Many were consolidated into more comprehensive overview articles. **Content was added, removed, and restructured, as if building a help center from scratch.

3. Shadow testing with real traffic. Using Fini's Front integration, they turned on "comments" mode mid-implementation. Fini posted draft replies as internal comments, visible only to the Wefunder team, so they could evaluate and adjust before going live.

4. Action configuration. Two dedicated weeks wiring up agent actions: password resets, marketing unsubscribes, 2FA fixes, and withdrawal-specific responses.

Results: First Two Weeks Live

Before Fini, the team maxed out at ~600 emails per week with 7+ hour response times. Here’s what happened when they flipped the switch:

After Fini: they handled more volume and responded faster.

Metric

Week 1

Week 2

Messages received

1,500 (1k new convos)

1,400 (900 new convos)

Messages sent (total)

1,300

1,200

Fini messages

900

1,000

Team messages

440

240

Avg response time

3 hours

25 mins

By the second week, Fini was handling over 80% of outbound messages. Response time dropped from 7+ hours to 25mins. The team sent fewer than 250 messages, not because they were doing less, but because Fini was handling the routine work for them.

In total, Fini answered roughly 2,000 emails in the first two weeks.

What Users Actually Said

Even when users recognize they're talking to an AI agent, the response has been positive.

A few real examples from the first weeks:

“Thank you so much for your quick response. Phenomenal!” — Founder, after receiving fundraising strategy guidance

“Thank you! I appreciate the clear directions.” — Investor, after step-by-step guidance on increasing an investment

“Awesome! That was really fast and helpful, THANK YOU!” — User, after support merging accounts

From Wefunder's President

Wefunder President Jonny Price shared the results publicly:


image.png

48 reactions. 5 reposts. When leadership shares results like this unprompted, it speaks louder than any case study.

What’s Still Being Refined

Kai was upfront about the edges that still need work:

“Last week we saw a couple of cases where the bot told someone it took care of something it actually couldn’t and didn’t flag it. We saw it, are fixing it, and watching closely for anything else like it.”

This is normal for any AI agent deployment, especially in the first weeks. The important thing is that the team is actively monitoring, catching issues quickly, and tightening the system in real time.

The Real Impact: Capacity, Not Just Speed

Faster response times are the easy metric. The bigger story is what the team can do now that they couldn’t before.

“Now investors and founders will get the 11-star support and service they deserve, and the team will have time back that we can fill with more impactful projects, instead of being heads down and reactive in the inbox.”

“There’s room to breathe now, and instead of trying to add and train more people, we can thrive at our current size.”

The Success team is already using freed-up capacity for higher-impact work: vibe coding an end-to-end investment transfers tool, optimizing the identity verification process, and building a faster IRA investment flow for investors.

These are the projects that improve the platform for everyone, and they weren’t getting done when the team was buried in routine email.

The Takeaway

Wefunder’s challenge wasn’t unique. High-volume support teams in fintech face it constantly: routine queries consume all available capacity, response times slip, and the work that actually moves the business forward gets pushed to “someday.”

Four months after starting implementation, Wefunder is handling 2x the volume with 6x faster response times, at the same team size. More importantly, the team has capacity to do work that matters.

👉 Book a demo to see how Fini can give your team that room back.

FAQs

Leonardo Maestri

Leonardo Maestri

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