Fin is an AI Agent for customer service. It automates complex queries, improves resolution times, and delivers consistently high-quality support at scale.
$0.99
one-time fee per outcome
Landbot
Score 7.0 out of 10
N/A
Landbot.io is a no-code chatbot platform used by businesses to build frictionless conversational experiences from end-to-end. With the goal of turning conversations into profitable outcomes, Landbot helps Marketing, Operations, and Customer Service teams increase their efficiency and cut operating costs. Whether it's for WhatsApp, Web, or Messenger, the user can create automated chatbot flows to better engage customers and…
$39
per month
Pricing
Fin
Landbot
Editions & Modules
Fin with your current helpdesk
$0.99
one-time fee per outcome
Copilot add-on
$35
per month per user
Pro add-on
$99
per month For analysis of 1,000 conversations
Fin with Intercom’s Helpdesk
from $39 + $0.99 per Fin outcome
per month per seat
Sandbox
$0
Per Month Per User
Starter
$39
per month
Pro
$99
per month
Business
Starting at $300
per month
Offerings
Pricing Offerings
Fin
Landbot
Free Trial
Yes
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Fin comes with a 90-day money-back guarantee. Here's how it works:
Intercom states that users who sign up for the Fin Guarantee Success Program and do not achieve at least a resolution rate of 65% will be paid $1M. This program is designed for high volume customers.
Eligibility criteria:
High volume customers (over 250k monthly conversions) in North America and Europe. Intercom states that phase one of this program will admit customers on Intercom Helpdesk or Zendesk.
Fin is fantastic at answering simpler inquiries, where the range and types of questions are easier to categorize. Thereby reducing the subset of possible answers. Where it has shown great improvement - but still needs more improvement - is by becoming a true Agentic AI support engineer that is capable of answering more technically nuanced questions. Our product has a lot of variables used for troubleshooting that cannot be adequately captured in documentation. Even though we provide thousands of pages of spec docs, each issue is unique. Training and empowering Fin to be as good as a Level 1 support engineer is still very challenging.
Well Suited: If you are looking for a bot - - that is easy to build, that requires no IT person - that has competitive prices - that has a clean and easy reporting option, which can help the data analytics. Not Well Suited: Though it has Dialogflow integration, you cannot use it as a complete self-learning bot solution. If you are looking for a bot that is self-learning you have to go for IBM Watson Assistant/Dialogflow/SAP Conversational AI.
It seems some users really struggle to figure out how to escalate to a human (especially through email).
Not excited about how "soft" resolutions still count as resolutions and are paid for. Though some abandoned cases appear to be able to be concluded as "the user got the answer they needed", there are others where they clearly didn't, because they just open up another chat (or even more), trying to get more info. This pads the resolution stats and makes it seem more effective than it actually is.
Cost -- Fin is quite expensive. It helps us with scaling coverage, but we're not really saving money.
Keywords Jump Feature: As a feature, it is good. But there is a scope of improvement that I see. In our Business, there are a lot of words that are similar for example Bearing/Bear ring/Bearing. So, at times the bot takes some time to find the exact keyword what the user wants and then route it accordingly. Most of the time, it does right, but at times it doesn't.
We have been and will be continuing our journey with Intercom and nothing too concerning has happened that I have experienced or heard of that has us on the edge yet. If it ever happens it will be something along the lines of "Outgrowing" the use of need of the platform.
The platform is overall clear and intuitive. As with any new platform, there's a learning curve, but that wasn't an issue for our team (and it shouldn't be an issue for others). Fin options are scattered across several submenus, and I'd like them grouped together, but I also like having all those training-related tabs open at all times, so it's not much of a real issue for me.
I can get help by asking Fin questions about itself. It answers accurately, citing its own Help Center resources with visuals. It can reason and dialogue well. But when it comes to getting human support for Fin, it is not as quick. It can sometimes take a few days. They are polite and well-meaning. Some things aren't their fault (product limitations), but there was one occasion where something took a long time to resolve with lots of back and forth but it was I who found out the error in the end that they missed, so they didn't really help resolve it.
There are so many AI platforms available, and you could theoretically build a system using the available AI API's from any of the big platforms. However, I dont think it's as easy as this. Intercom is deliberately built for customer service, the features they are releasing a based on providing the best customer experience. If we were to build this ourselves or to use another platform we would be taking on the upkeep, using Fin is just much simpler as it's also our chosen ticketing platform so anything that Fin is not able to answer yet and escalated directly to our team with no extra effort required from our side.
Drift is quite pricey, on the cost part, Landbot was much better with almost similar features. Also, on the UI front, Landbot was a pretty decent tool compared with Drift or MobileMonkey. The usage was easy, the reporting was very easy to get. Considering all these parameters, we chose Landbot for our Organization.
New role opportunities — Using the “Fin-first” approach has reduced the workload for our Tier 1 team, giving them more time to focus on their own career growth. It’s also opened the door to a dedicated, AI-focused role, where a team member regularly reviews Fin’s answers and makes updates to help it perform even better.
Enabling Fin has also reduced our response time and allowed us to meet SLA's.
