Fin vs. Hugging Face

I can't think of anything off the top of my head regarding less appropriate. However, this product is very customizable. I think with some improvement in reporting it could be better, however, I would recommend due to these types of things. I love the knowledge base and creating those help centers. I would say that it is fairly easy to set up, but once you set it up, not really knowing all the things, it's hard to go back and change, so it would be nice to have an overall idea of guidance prior to the original setup that can just be improved over time.

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If an organisation has more access to data and have access to high end computers like GPUs it’s recommended to use Hugging face as it will give better accuracy than any other models. If an organisation having less data and has less access to GPUsis looking for decent performance then traditional algorithms are more appropriate than hugging face

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• The AI agent can answer our users' questions accurately based on the information available in our Help Center.
• Ability to set up workflows and procedures helps our team automate repetitive tasks.
• The inbox layout is clean and easy to navigate, and we can set views to suit our preferences.

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• Model APIs
• Hugging Face Spaces for deploying demo apps
• Latest updated models available easily
• Vast support for language parsing and other relevant tasks

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• I wish I could pull reports on the conversations that have been closed.
• I wish I could tag fin categories in addition to our live help desk conversations so I can get a good read on the types of questions users are asking.

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• Most of the Hugging face models are of big size, hence difficult to work if there is no access to high computational system like GPU.
• It’s good to have some visualization tool in hugging face for viewing model architecture.
• I recommend to implement hugging face lite version so that it can run on any system with less specifications.

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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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Intuitive is a very accurate descriptor. Features do not seem to be hidden by poor UI. Things are usually where you would expect them to be, and the UI has been designed to make it pleasant to work within the platform. The platform also scales really well. Both small and large organizations can achieve a great return on investment by using it.

always there

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Fin is super quick and top notch.

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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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It was great. We were able to walk through step by step and get our questions answered along the way.

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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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Fin far surpasses these other options in platform features and capabilities. Fin allows for side-by-side use by both the Marketing and Support teams, while none of the other similar products did that well. Most platforms are designed for one or the other, not both.

There are some other services offer similar capacity as to Hugging Face, but not entirely the same. For example, amazon web services have a machine learning service called Comprehend, which offer a set of easy to use APIs to do machine translation and entity recognition and some other common NLP use case.

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The product is very scalable and has helped us scale our user base and onboard 10x the users in just one month. We couldn't have done it without Fin

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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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• Hugging Face is cost and time saving.
• Pay is less, you pay what you use, doesn't affect much.
• Overall positive impact on business.

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