AWS provides Amazon Lex, a chatbot building technology.
$0
Per Speech Request
Fin
Score 8.8 out of 10
N/A
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
Agentforce
Score 8.0 out of 10
N/A
Agentforce is a solution that provides intelligent bots created and customized via a low code builder. Agentforce agents operate autonomously by retrieving data on demand, building action plans for any task, and executing these plans without human intervention.
N/A
Pricing
Amazon Lex
Fin
Agentforce
Editions & Modules
Request and Response
$0.004
Per Speech Request
Stream Conversation
$0.0065
Per Speech Interval
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
No answers on this topic
Offerings
Pricing Offerings
Amazon Lex
Fin
Agentforce
Free Trial
No
Yes
No
Free/Freemium Version
No
No
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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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.
If you wish to quickly deploy multilingual chatbots without having to worry about infrastructure and model training, go for Amazon Lex. It is one of the best general-purpose conversational AI solutions in the market. The cherry on the cake is that it also seamlessly integrates with other AWS services, so you would be good there. Performance monitoring is very easy with AWS. It has support for both text and integration. If you are not a pro-NLP expert, Amazon Lex will make your job really easy.
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.
Agentforce has a lot of applications. We are using it in consulting to benchmark other clients, what they're doing, where we stand, how can we have better efficiencies coming in, et cetera. Those are the areas where it is doing exceptionally well. The area where we feel it can do much more better is maybe a market benchmark because it's been used across by so many players and it's a connected ecosystem. If Salesforce can have something where it gives me the market view of things, I can then benchmark rather than in my own universe to the broader university Salesforce and I know where I exactly stand and what more can I achieve, what's my final goalpost. So that would be something really great.
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.
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.
Easy to deploy and very easy to integrate with other AWS services. Automating simple tasks is also very easy with Amazon Lex. We never had NLP experts in our team, but we were still able to deploy chatbots for our support functions with minimal issues. Native integration with other AWS services like S3 and Lambda has been of paramount importance.
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.
The platform offers an intuitive overall experience and the expected strong integration with other Salesforce existent tools. It has a low learning curve for new users on the commom use cases, such as intent classification, routing and knowledge-based answers. It could be improved with more transparency regarding to the AI decision logic.
Community support for Amazon Lex is good. Also, since it is an AWS service, the support has a similar standard as other AWS services. We have had a couple of instances of our bots weren't able to interact with our web apps. We reached out to the support team, and they were able to resolve our issue in no time. The documentation from the Amazon Lex team also makes creating chatbots a breeze.
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.
We did evaluate the EVA bots, which are coming in market for Salesforce effectiveness. Those bots are good, but they're based out of very traditional use cases in the life sciences space. Agentforce is very, very advanced, right? Eva can talk about a typical sales rep coming in, logging in the day, log their entire day, and then probably having a simple text to reporting kind of a view. And that's it. Agentforce gives me a lot of insights, it gives me a lot of actionable insights. It uses its own brain. That's where Salesforce is an AI company. So we trust the Salesforce banner for it to innovate more and more, more and more. And that's where we chose Agentforce over.
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.
