Fin by Intercom vs. Kore.ai vs. Rasa

It's excellent when users often have trouble understanding certain aspects of your product, so you don't have to manually share the same information every time. It's less appropriate if your user problems are user-specific, as then you probably don't have every expected case covered in your documentation, which then requires Fin to have access to your codebase, at which point you might want to consider building your own agent.

It is a very flexible virtual assistance tool that is easy to develop enterprise-level complex bots without the knowledge of highly skilled programming. The platform has a straightforward and user-friendly interface. It has excellent documentation and answers all the possible questions of clients. Moreover, its customer support is really great. It is one of the fastest chatbot development platforms that are scalable, easy to integrate, and provides various domain support. Overall I had a great experience with Kore.ai.

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Rasa Pro is well suited for corporate use and for chatbots which require backend connections. Smaller chatbots with a few flows might be better served with a simple dialogue engine and custom AI agents, or Rasa Open Source. Rasa does not come with its own complex vector database, just in-memory FAISS and connectors to external vector DB's such as Milvus and Qdrant. It provides only a basic document parser and embedder for FAISS. If you need to build a RAG focused chatbot around a large knowledge base with complex documents, e.g. lots of MS Word or PDF files, you'll have to build a separate document parser and embedder, as well as your own semantic search engine

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• It is very easy to train
• It does a great job of recommending answers when little context is given.
• I love the ability to create a snippet to address issues in the moment or in the long term, based on FAQs.

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• Virtual Assistants.
• Customer Journeys.
• Bot Development.

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• Rasa team has Top notch AI knowledge
• Greate customer support, by listening towards the clients needs.
• And building future proof solutions around client Business Requirements within dazzling timeframes

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• 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.

• No-code apps could be improved
• Online docs can be messy
• Steep learning curve

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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.

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FIN is easy to set up and pretty quick to get everything the way you need (some things could be handled better), and you can preview how it's going to work before it's available to everyone. Since you can use FIN on multiple channels, you can save a lot of time by not having your team work on multiple chat platforms as well.

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For new users, it has one of the best UI/UX experiences. One can easily get used to the platform and integrate enterprise-level intelligent chatbots. It uses many AI algorithms that understand the queries very effectively and helps resolve client issues. You don't need any prior high-level experience in coding to build chatbots and can easily integrate a chatbot with the Kore.ai platform.

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With the help of dedicated team - documentation and video resources it is relatively easier to build. We prioritized pro-code usage to begin with launch.

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always there

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works perfect

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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.

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Our experience using Kore.ai makes it one of the best AI chatbot platforms we have ever used. Kore.ai bot builder is extremely easy to use and does not require technical expertise to make it live. A change in the flow can be made whenever required with the bot.

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Rasa support has been very responsive, trying to fix any reported issues ASAP. They've also listened to many requests for improvement. The Rasa features and changelog are well documented

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Easy to know the learning path

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The implementation was surprisingly easy but we are having to adapt from our old process to work well with Intercom.

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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.

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• 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.

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• Assisted in solving customer questions.

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• Cost Savings & Efficiency
• Increased Conversion Rates
• Improved Customer Satisfaction
• Operational ROI

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