In this article, we'll explore the key aspects that differentiate Cassidy from ChatGPT Enterprise, focusing on Cassidy's models, core features, security, support, and more to understand its advantages for implementing AI into your organization.

AI Models and Flexibility

Cassidy supports multiple AI models, including OpenAI's GPT-4o & GPT-4, Google Gemini, and Anthropic Claude. This approach offers a broader range of capabilities and a higher level of reliability depending on the use-case. For instance, we’ve found that Claude is the best for content writing, while GPT-4o is the best for internal Q&A. Unlike ChatGPT, which relies on OpenAI's models alone, Cassidy provides a more versatile AI experience.

The important part about being model agnostic is that when newer and better models are released, they will get added to Cassidy automatically. There’s no fear of purchasing and investing in an AI model that will quickly become outdated.

Knowledge Base

ChatGPT Enterprise, similar to other Large Language Models (LLMs), faces the inherent challenge of potentially generating misinformation or 'hallucinations'. A key limitation in this context is the model's inability to provide source citations for its generated content.

More specifically, ChatGPT Enterprise doesn’t support the ability to directly integrate with and store files in a centralized Knowledge Base. As of the latest update, you can add Google Drive and Microsoft Sharepoint files via the “chat” feature, but there’s no way to integrate or store them (and have it live sync when changes are made in your Google Drive, SharePoint, etc.). This makes Cassidy more ideal for use cases that require robust internal knowledge management and searching across thousands of files- unlike ChatGPT which is only ideal for one-off uploading of files.

Cassidy's Knowledge Base securely connects with over 100 tools and updates in real-time, prioritizing privacy. This comprehensive knowledge management system empowers Cassidy's AI capabilities with a rich context for generating accurate and relevant responses. Whenever it generates a source, it cites its sources so you can assure the accuracy of all your information.

AI Assistants

Cassidy's AI Assistants, powered by the Knowledge Base, perform specific tasks such as drafting replies to customer emails and assisting internal HR operations while maintaining contextual consistency across teams.

While ChatGPT Enterprise has GPTs that function similarly to Assistants, there are a few key reasons that Cassidy’s Assistants perform better:

1. The ability to add context via your Knowledge Base allows for much higher accuracy compared to solely having detailed roles.
2. The ability to easily share Assistants across your entire team for consistency (e.g. customer responses, RFP builders, blog post creation, etc.).
3. Beyond Chat, you can take your assistants into multi-step workflows for greater creativity (more on this in the next section).

Multi-step Workflows

While ChatGPT focuses strictly on chats, Cassidy allows you to build and run multi-step workflows without the need for back and forth chatting. This feature is ideal for automating specific processes that you run in a similar way every time - it’s more effective to set it up once and just have to run it versus always having to chat back and forth.

With workflows, we can integrate with tools that ChatGPT for Enterprise can’t. For example, via Workflows, you can integrate with Zendesk and automate customer support. You can plug into Slack and easily deploy Slackbots to answer employee questions. We integrate with Zapier so you can plug into 6,000+ other apps and use Cassidy as the “AI Glue” to scrape the internet, craft customized content, and search your Knowledge Base - all with actual context on your business.

Our workflows allow you to bulk run as well - this is great for automating processes that require multiple iterative runs rather than a single run. Good examples: Responding to an RFP that has questions in hundreds of rows, uploading a sales lead list, and automatically generating dozens of custom cold emails, etc.

Integrations

Cassidy integrates with key business tools like Google Drive, SharePoint, Notion, Slack, Zapier, and much more. There is also a Webhook for incoming data and an API (both GET and POST) which allow you to securely integrate data from practically anywhere. This connectivity allows for seamless integration of AI Assistants. With Cassidy, you get access to thousands of integrations to trigger actions (e.g., drafting emails, sending Slack messages, responding to tickets, creating contacts, publishing blog posts) that are not possible with ChatGPT Enterprise.

Security and Data Privacy

Cassidy prioritizes data security with enterprise-grade protocols, ensuring user data safety. Both are SOC2 compliant and follow the industries top practices for security and privacy.

Support and Onboarding Process

Unlike ChatGPT for Enterprise, Cassidy believes in onboarding all of its Enterprise teams and providing ongoing support. From setting up your integrations to setting up complex workflows with your team, our goal is to continue unlocking new use-cases that make your team more productive.

More specifically, with your workspace, your team gets access to:

1. Your own Dedicated Account Manager to help your team build AI assistants and workflows customized to your use cases.
2. Team training sessions to train specific functional teams (sales, marketing, customer support, etc.) on how to best use Cassidy.
3. Weekly Office Hours to help get questions answered live on calls.
4. Slack channel with the Cassidy team to answer questions quickly or create requests for new integrations.

Because we can provide so much support & onboarding, Cassidy actually enables your team to effectively roll out AI, rather than just being another software tool in the mix.

Reach out to learn more

If you’re interested in learning more about our Enterprise offering, reach out to our sales team at team@cassidyai.com.

This article will explore the critical differences between Cassidy and Microsoft Copilot. We will focus on Cassidy's diverse features, robust Knowledge Base, and seamless integrations to understand its advantages for organizations looking for efficient AI workspaces.

AI Models and Flexibility

Cassidy supports multiple AI models, including OpenAI's GPT-4o & GPT-4, Google Gemini, and Anthropic Claude. Microsoft Copilot, on the other hand, relies solely on OpenAI. Given Microsoft's partnership with OpenAI, their models are limited to the OpenAI ecosystem. By being model agnostic, Cassidy allows for newer and better models to be added automatically, mitigating the risks of investing in outdated AI models. You also have the added flexibility that certain models are better than others at certain tasks, so you can selectively choose the best models based on your tasks.

Knowledge Base

While you can integrate your SharePoint files within Microsoft 365, you cannot connect other third-party tools like Google Drive. Cassidy's Knowledge Base securely connects with over 100 tools, ensuring real-time updates and privacy. This provides a more comprehensive knowledge management solution to generate accurate and relevant responses across thousands of files, for your entire time.

AI Assistants

Cassidy's AI Assistants, powered by the Knowledge Base, perform specific tasks while maintaining contextual consistency across teams. Microsoft Copilot offers Copilot GPTs that function similarly to Cassidy Assistants; however, they:

1. Cannot access the same level of context via the Knowledge Base.
2. Are limited to the Microsoft ecosystem and cannot be used in workflows with non-Microsoft tools.
3. Are restricted to developer-centric solutions, while Cassidy is a no-code solution accessible to both technical and non-technical users.

Multi-step Workflows

Microsoft Copilot Studio offers limited workflow automation with a focus on deploying Copilot GPT-type assistants to different tools. Unlike Cassidy, which enables users to build and run multi-step workflows for end-to-end automation, Copilot Studio is more technical and less accessible to non-developer users. Their automations, similar to their Assistants (Copilot GPTs), are Sharepoint-centric. Cassidy’s no-code workflows enable comprehensive automations from enriching inbound leads to triggering internal slack messages to your team.

Integrations

Cassidy integrates with key tools like Google Drive, SharePoint, Notion, Slack, Zapier, and many more, allowing for seamless integration of AI Assistants. In contrast, Microsoft Copilot is limited to Microsoft applications like SharePoint and does not integrate with Zapier. Cassidy’s extensive integrations enable you to trigger actions that are not possible with Microsoft Copilot.

Security and Data Privacy

Both Cassidy and Microsoft Copilot prioritize data security with enterprise-grade protocols and follow the industry's top practices for security and privacy. Both platforms are SOC2 compliant. Learn more about Cassidy’s security at trust.cassidyai.com.

Support and Onboarding Process

While Cassidy ensures onboarding assistance for all enterprise teams, Microsoft Copilot offers self-help resources, admin self-help, support plans, partner assistance, and sales contacts. Cassidy's support includes a dedicated account manager, team training sessions, weekly office hours, and a Slack channel to help teams build AI assistants and workflows tailored to their specific use cases. This level of support allows Cassidy users to effectively roll out AI solutions within their organization.

Reach out to learn more

If you're interested in learning more, contact our sales team at team@cassidyai.com.

Which AI model should I use?

This is the #1 question I get asked.

Well…why not all of them?

Over the last year, 3 AI models have emerged as frontrunners in the AI race: OpenAI's GPT-4, Anthropic's Claude 2, and Google's new model Gemini.

But not all of these models are the same. Each has their own strengths and weaknesses. That’s why I believe you shouldn’t just be using 1 model. You should be using every model. 

Let me explain why.

GPT models are reasoning engines

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“GPT models are actually reasoning engines, not knowledge databases,” wrote Dan Shipper, CEO of Every. “Even though our AI models were trained by reading the whole internet, that training mostly enhances their reasoning abilities, not how much they know. And so, the performance of today’s AI models is constrained by their lack of knowledge”

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Dan is spot-on. While most people are trying to use GPT models as encyclopedias—and have even run into fines in court from thinking GPT delusions were true—, they should be using GPT models as an assistant to speed up workflows and reasoning on projects. 

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While GPT-3.5 quickly generates text, it lacks the nuance of GPT-4. GPT-4 can only handle 32,000 tokens, but it has extremely powerful reasoning and understanding skills. For most tasks, it pays to use the more expensive GPT-4 or GPT-4 Turbo if possible with 128,000 tokens.

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One biophysicist Jeffrey Perkel wrote in a Nature article that using GPT-4 as an assistant lowered his time spent on some coding tasks from days to “an hour or so.” Content agency owner Randy Ginsburg said, “One of my favorite ways to use ChatGPT is as both a copy and developmental editor. It quickly catches any typos or spelling mistakes and often suggest new angles for the article that I previously haven’t thought of.” Notion engineer Linus Lee uses GPT-4 to come up with travel recommendations. 

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Perhaps as GPT models increase in power, their ability as a knowledge database will increase too, but for now, it looks like GPT-4 will have to be content being an assistant.

Claude 2’s giant context windows

Do you want speed or quality? Ah, the everlasting question in business.

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Claude 1 generates text in seconds, but the tradeoff is that its output is a much lower overall quality. “For use cases emphasizing fast turnaround over output sophistication, Claude 1 excels” explains Copy.ai’s Nathan Thompson. “But those needing higher accuracy, reasoning, and consistent quality are better served by Claude 2 or other models like GPT-3.5 and GPT-4.”

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Because Claude 2 can handle 100,000 tokens (2-3 hours of YouTube transcript or an entire novel) and you need to pay for GPT-Turbo (can do 128,000 tokens), summarizing long pieces of content has become one of the main competitive advantages of Claude. 

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Creator Riley Brown uses Claude to summarize 2-hour YouTube videos in seconds. AI strategist Christian Ulstrup tweeted about how he used Claude to summarize 5 of his meeting transcripts and give him follow-up questions to think about. Writer Darren Broemmer uploaded a large dataset to Claude and was able to ask questions about the data.

PaLM 2 → Gemini 

Since May of 2023, Google Bard has been running on the PaLM 2 model. 

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Things weren’t going great for the tech behemoth. PaLM 2 has an 8,000 token context window and still isn’t getting massive adoption despite its ability to connect to the Google ecosystem. “Bard sucks and is pretty comparable to open-source alternatives,” tweeted Dan Shipper. 

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Well, it looks like things are changing.

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Two weeks ago, Google released a demo for AI model Gemini that took over the internet. 

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If you missed it, the demo—which felt like a piece of sci-fi—showed Gemini's ability to reason and interact with the real world from identifying a rubber duck to creating games from scratch.

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Reports show that the Gemini model is currently beating GPT-4 at 30 out of 32 categories. Google DeepMind CEO Demis Hassabi says "Each of the 50 different subject areas that we tested on, it's as good as the best humans in those areas.”  

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Unfortunately Google won’t be integrating Gemini into Bard until 2024, but we’re counting down the days. Let’s hope they don’t pull the plug on this project 😂

Get access to all models: 

If 2023 was the year of everyone testing out GPT-4, then I think 2024 is going to be the year of everyone experimenting with new AI models. 

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This is the beauty of competition, right? We're going to keep seeing better AI models released into the world. While I’ll always have a soft spot in my heart for ChatGPT, every model has its own purposes. GPT-4, Claude 2, and now Gemini each bring something unique to the table. 

That’s why you need to have access to all of them.

By using Cassidy, you can access all of these models in one workflow. No more switching websites and logging in and out of apps. No lost time or data. You can switch between GPT-4, Claude-2, Gemini, and even more open-source models to build assistants and workflows for everything from marketing to coding to product management. 

Ready to try Cassidy? Sign up here.