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
IBM watsonx Orchestrate
Score 8.3 out of 10
N/A
IBM® watsonx™ Orchestrate® leverages AI to automate complex workflows. The solution helps build, deploy, and manage AI assistants and agents. It offers a catalogue of pre-built agents and tools, low-code agent builder, multi-agent collaboration capabilities, and integrations with enterprise apps.
$530
per month
Microsoft 365 Copilot
Score 8.1 out of 10
N/A
For enterprises, Microsoft 365 Copilot (or just Microsoft Copilot) is a generative AI operating as an intelligent virtual assistant for work. Through a chat interface, business users can use it to solve a variety of complex tasks.
$31.50
per month per user
Pricing
Fin
IBM watsonx Orchestrate
Microsoft 365 Copilot
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
Essential
$500
per month per subscription
Essentials
$500
per month Per subscription
Standard
Enterprise
Standard
Enterprise
per month Per subscription
Microsoft Copilot
$31.50
per month per user
Offerings
Pricing Offerings
Fin
IBM watsonx Orchestrate
Microsoft 365 Copilot
Free Trial
Yes
Yes
No
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
Yes
No
Entry-level Setup Fee
No setup fee
Optional
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.
IBM watsonx Orchestrate can be deployed and run on IBM Cloud, AWS, or on-premises. Prices shown are indicative, may vary by country, exclude any applicable taxes and duties, and are subject to product offering availability in a locale.
Pricing shown is based on an annual commitment. Discount available for annual payment.
I think Fin by Intercom stacks up well for the specific niche of using AI to provide customer support and business uses. The other AI products I've used are more general LLMs which, while great, would be a struggle to use/build to provide the same experience.
The only reason is that we have been using some other products of IBM, and the trust on their company, so we chose to use IBM Watsonx Assistant, that's it.
Verified User
Project Manager
Chose IBM watsonx Orchestrate
IBM Watson Assistant has a competitive cost structure, is easy to integrate with Intercom, and is more scalable as we look to future enhancements such as speech-to-text, document upload/analytics, and natural language processing across multiple languages.
A prospect lands on my site to ask about building profile sizes, wind/snow ratings, installation timelines, or warranty coverage. What Fin does well is deliver instant, consistent answers, pull from approved specs and positioning, and keep the conversation moving without human involvement.
In our case, it is well-suited for workday integration, which allows us to automate the entire workflow. However, we are still working on the O9 platform integration, which we feel is less appropriate, and integrating the workflow into the platform.
I highly recommend its usage in Teams meetings to prepare a session transcript, meeting minutes, next steps and recognize speech by person. Also within the meeting recording, there is separation between the people talking at the time. The Copilot image creation is very accurate and useful to customize my PowerPoint presentations and other documents
New and improved natural language processing yielding better results helps the assistants understand the intention behind the query.
Preserves context of communication, allowing the customers to establish inquiries on the website and continue on the mobile app without having extra informational input.
Intelligent conversations mean that complex paths that are branched based on the user's inputs allow for a much more natural flow of the conversation than fixed scripts.
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.
I think that it needs to be able to integrate better with the knowledge catalogs. It currently provides a default database, which isn't quite large enough for enterprise use. We can connect that then to an external source, but it'd be nice if we could able just to instantiate one straight away.
The quality of image generation in Microsoft Copilot could be improved. Compared to other AI platforms, Copilot's images often fall short in quality and frequently contain typos.
When generating agents and chatbots, Microsoft Copilot currently doesn't appear to support file download functionality.
The email reply function is useful, but the responses can sometimes be overly elaborate. It would be helpful to have more options for adjusting the tone.
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.
Currently we are using to develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. Action flow and dialog flow we are currently in chatbot.
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.
With the growing use of AI and chatbots, it's very easy to use, and the conversational language makes it easier than keyword searches in a document. The contextual language processing is impressive. It's easy to integrate into our internal portal. The use of this tool would depend on each company's security and data sensitivity.
it is nearly perfect and it’s usability one of the main factors and contributing to the score is how versatile this tool is. it is vastly usable in a multitude of circumstances, and has a few limitations, but overall this product works well for what it is intended. It is very helpful for some otherwise time consuming tasks.
To develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. IBM Watson library anyone can easily learn and develop chatbots.
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.
We've rarely had to engage support, but they've always been prompt in responding and very attentive. Support experiences have been extremely positive (but we're mostly happy that we just don't have any cause to routinely need support in the first place!).
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.
Make has more community of workflows to follow that have been redeveloped and are available for download. Selecting WxO is based on our trust level with IBM and the propositions of the Granite model being less biased, more business trained, and the ecosystem allowing for expansion with Assistant and Discovery.
I think It lost the race for now. I don't think Microsoft will keep investing on it since we have better tools outside their environment. In my opinion, Microsoft Copilot is not even in the benchmark tools and in the race for AGI. I think Microsoft is way behind and Microsoft Copilot suffered the lack of investment like the one made by its competitors.
From past 3+ years I am using IBM Watson in our current project easily can implement and manage and monitor user how their using. Is there and update also just update dialog is just enough to change no need to touch any other templates. Multiple language will support, and action and dialog speak recognize chatbot we can create as per client requirement. Overall, as of now good experience with IBM Watson.
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.
By automating tasks that would otherwise require human intervention, organizations may achieve cost savings in terms of labor, especially for handling large volumes of routine inquiries.
Virtual assistants can handle a large number of simultaneous interactions, making them scalable to accommodate growing customer bases and increasing workloads without a linear increase in staffing.
