Announcing Cassidy’s $3.7M Fundraising

AI Automation vs. Enterprise Search

Cassidy and Glean serve different purposes in the enterprise AI space. Cassidy is an AI automation platform that executes multi-step workflows, while Glean is primarily an enterprise search tool designed to help teams find and retrieve information.

The biggest difference? Cassidy doesn’t just find information—it takes action. Whether automating RFP responses, triaging support tickets, or generating approvals, Cassidy applies AI to automate real work, while Glean focuses on retrieving knowledge across enterprise systems.

Here’s a quick feature comparison:

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Cassidy: AI That Works For You

Cassidy isn’t just about surfacing information—it’s about automating work. It can:

• Draft & process RFPs in seconds, pulling from company knowledge.
• Triage and route support tickets automatically, reducing workload.
• Enrich and update CRM records, helping sales teams move faster.
• Generate personalized emails, reports, and summaries with real business context.

With no-code workflow automation, teams can deploy Cassidy quickly for immediate value—no IT-heavy setup required.

Glean: Search, Not Automation

Glean specializes in enterprise knowledge retrieval, making it easy for employees to find information across wikis, emails, and files. It’s designed to:

• Reduce internal support tickets by giving employees self-service answers.
• Help new hires get up to speed by centralizing company knowledge.
• Improve decision-making by surfacing relevant reports and past work.

Glean’s AI-powered search is fast and accurate, but it doesn’t automate tasks or workflows—users still have to take action manually.

Speed of Deployment: Quick Wins vs. Heavy Rollout

• Cassidy: Deploy in days, not weeks, by targeting a single high-impact use case (e.g., automating customer support responses or drafting proposals). AI assistants and workflows can be embedded directly into Slack, Teams, and email without deep integrations.
• Glean: Requires indexing the entire organization’s data before it’s useful. Companies must integrate Glean with all tools and set up permissions before employees can start using it.

Cassidy delivers value immediately, while Glean is a long-term IT investment.

Automation Workflows vs. AI Agents

• Cassidy: Users build clear, step-by-step workflows—for example, analyzing an incoming request, updating a system, and drafting a response—all automatically. It’s predictable, structured automation that businesses can rely on.
• Glean: Introduces AI “Agents”, which attempt to dynamically generate workflows on the fly based on broad user goals. While promising, this approach lacks fine control and predictability, making it less suited for critical business processes.

Enterprise Readiness & Security

Both platforms meet enterprise security standards, including SOC 2 compliance and strong access controls.

• Cassidy provides role-based access and data privacy controls, ensuring AI assistants only access relevant information.
• Glean enforces strict user permissions, making sure employees only see data they are authorized to access.

While both platforms prioritize security, Cassidy is faster to implement without requiring full company-wide data integration.

Who Should Use Cassidy vs. Glean?

Use Cassidy if you need:

✔️ AI-powered workflow automation that acts, not just retrieves data
✔️ Fast, no-code deployment for targeted automation use cases
✔️ Real-time AI Assistants in Slack, Teams, and Chrome
✔️ Automations that replace manual tasks like RFPs, support triaging, and CRM updates

Use Glean if you need:

✔️ Enterprise-wide search to help employees find existing knowledge
✔️ A centralized knowledge hub that connects to all your company’s data sources
✔️ AI that retrieves information but doesn’t take action

Final Thoughts: Why Cassidy Wins

Glean is a powerful knowledge retrieval tool, but Cassidy goes further—using AI to actually get work done. If your goal is to automate business processes, reduce manual effort, and deploy AI-powered workflows quickly, Cassidy is the clear choice.

Ready to see Cassidy in action? Book a demo today.

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There are two primary categories for integrating AI into your business:

1. Boosting Internal Productivity - In other words, figuring out how to make your employees and workflows more efficient, so you can deliver better results faster.
2. Enhancing the Customer Experience - Exploring what you can offer on top of your existing products and services to make your customers even happier.

Focusing on internal productivity will help cut costs, while improving the customer experience will help you earn more.

Internal Productivity

In my view, it’s easier to start with internal productivity. Greater AI adoption within your team or even by yourself will lead to a substantial increase in overall productivity. The right AI strategy will turn everyone in your organization into a top performer.

Of course, figuring out the best AI strategy can be tricky. But, I think it’s important to not overthink it. Just starting to use AI tools and sharing them with your team can pave the way for in-depth AI integration across your organization. It’s crucial for everyone to have that “Aha” moment with AI.

At CassidyAI, we’re all about this mission. While we’re still slowly rolling out early access, we’ve been documenting our process publicly because we believe everyone can benefit from the thinking we’re putting into how to build features that truly speed up internal workflows.

We showcased our plugin feature that allows you to bring an AI assistant, custom-trained for your business, virtually anywhere on the internet. It’s been a game-changer for sales, customer success, and marketing teams.

(Check out the demo here. You can also signup for the Cassidy waitlist here)

The point is this: When integrating AI into your business, consider the workflows and tasks that currently exist and explore how AI could be introduced to enhance them. Never assume AI can't help--even small steps towards incorporating AI eventually become meaningful time savings.

Customer Experience

On the other hand, you can drive significant customer retention and growth by thoughtfully using AI in your products and services. This approach requires creativity, as it is not as simple as purchasing an off-the-shelf solution for internal workflow optimization.

AI-enabled features in your products and services could include personalized recommendations, an AI chatbot, or simple AI features that make it easier for people to use your product. The catch is that these features must be unique to your business.

For instance, Shopify customers struggled to optimize their stores properly, so their AI sidekick was developed to do it automatically. Another example: I recently spoke with a personal trainer who introduced an AI chatbot for fitness-related questions because clients struggled with guidance on days they weren’t seeing the trainer.

When considering AI implementation, think about the biggest pain points for your current customers. Why do people churn? Is something stopping them from using your product or service more often? What are their unmet needs?

It’s within these questions, you’ll find opportunities to enhance the customer experience using AI.

Picture an AI system that doesn’t just answer questions or move data around, but truly understands what it’s doing. 

It knows your brand policies, notices patterns in text, pulls the right documents when needed, and takes meaningful actions — all without you writing a single line of code.

That’s contextual automation, and it’s at the heart of what Cassidy is building.

Let’s explore what contextual automation is, why it’s different from old-school automation, and how Cassidy brings it to life in a way that feels both futuristic and easy to grasp.

What is Contextual Automation?

Traditional automation often relies on simple triggers: “When X happens, do Y.” This works well when you’re dealing with neat, structured data — like updating spreadsheets or sending emails. But modern businesses deal with messy, unstructured information, such as emails, chat logs, PDFs,  and policy documents. 

These sources don’t follow a tidy format, and they can hide key details in plain text.

Contextual automation takes things further by letting AI read and interpret that unstructured data. Instead of just passing it along, the system understands why it matters. It can cross-reference facts from documents, product specs, or internal policies, then take the right action without requiring you to manually dig through it all.

Advantages of Contextual Automation 

Contextual automation improves two things: the speed at which you access information and your ability to act proactively. With accurate, up-to-date insights available in seconds, your team can make better decisions and achieve outcomes faster.

Context-Driven Actions
Cassidy goes beyond simply sharing data. It understands the context and takes the right actions, whether that means drafting a response, sending timely updates, or verifying that you’re being compliant. 

Empowering Your Team
Our workflows are essentially going to act as virtual agents, offering valuable insights and context for your employees. Whether you need background information on a video call participant, detailed company reports, or alerts on competitor activity, there are different ways to help your team get their job done faster and more efficiently. 

Built for Everyone
You don’t need technical expertise or prior knowledge of AI to set up powerful workflows with Cassidy. Every department can benefit from contextual automation. If you’d like to see some examples, explore the dozens of templates on our use-case page and see how easy it is to get started.

Why Standard Automation Falls Short

Old-school tools shine with structured tasks. If you want to copy data from one cell to another, they work great. But they tend to break down when handling open-ended or ever-changing content. 

Most of them weren’t built for large volumes of text, making them blind to the deeper context hidden in emails or documents.

They also struggle to chain multiple AI steps together. Many platforms offer a simple “AI step” to summarize text, but they don’t let you blend knowledge from different sources or apply complex logic. 

That’s where contextual automation stands out: it goes beyond a single prompt, bringing real understanding and multi-step reasoning into the mix.

How Cassidy Makes it Happen

Cassidy’s platform is built to handle these complexities from the start. We combine AI models, knowledge indexing, and no-code workflow design to deliver a seamless experience.

Unified Data Model

All of your information — from PDFs to support centers to spreadsheets — can be indexed in Cassidy’s knowledge base. If the AI needs to confirm any kind of policy, it can jump right to the correct section of your policy document. If it’s summarizing a support ticket, it can also review past chats for context.

Multi-Step AI Workflows

Rather than relying on a single rule, Cassidy chains multiple AI actions into a seamless workflow. Let’s say you want a full picture of a new lead and an updated lead score in your CRM as soon as their email lands in your inbox. 

Cassidy starts by gathering the basics, like name and email, then enriches the profile with insights from LinkedIn and the company’s online presence. Next, it calculates a lead score with a brief explanation and updates your CRM, all in one smooth, connected flow. Every step builds on the last, ensuring your team receives a complete, context-rich lead profile that’s ready for action.

No-Code Building Blocks

We offer drag-and-drop “building blocks” for tasks like sentiment analysis, text comparison, or drafting replies. You snap these pieces together to form custom workflows that match your needs. This makes it easy for non-technical users to build advanced automations without learning to code.

Flexible and Future-Ready

As AI evolves, Cassidy evolves too. If a new large language model comes out, you can plug it into your existing workflows. That means your automations can keep improving without needing a total rebuild.

Real Possibilities with Contextual Automation

Contextual automation isn’t just for one team or department. It can reshape how entire organizations handle their day-to-day operations. Here are a few examples:

Sentiment and Policy Checks
Have the AI scan user comments or support tickets, then compare them to your policies. If certain keywords suggest an urgent issue, it can draft a response or alert the right person — all in real time.

Smarter Knowledge Base Searches
Save your employees countless hours by making all your information easy to access. Instead of having to manually search through vast knowledge resources, Cassidy scans your data to quickly pull together the best answers and present them in clear, plain language.

Live Document Review
Whether it’s a contract or a compliance form, Cassidy reviews your documents by cross-referencing them with your guidelines or any instructions you may have. It quickly identifies potential issues or discrepancies, reducing human error and speeding up the review process.

Task Routing with Context
When a new ticket arrives, the system examines its content, references relevant documents, then sends it to the right department with a suggested plan of action.

Where Contextual Automation Is Headed

AI is moving fast, and contextual automation opens the door to even bigger possibilities. Large language models are gaining the ability to handle longer and more detailed text. They’re also getting better at reasoning, remembering past conversations, and adapting as new data comes in.

Adaptive Learning
Workflows will watch how users respond and automatically improve their logic over time.

Multi-Model Strategies
Different AI models might be used for different steps — one for drafting content, another for fact-checking. Cassidy is built to let you combine models as you see fit.

Custom AI Agents
Imagine having an AI “co-worker” who speaks your brand’s language, knows your product lines, and aligns with your unique processes. Giving you all of the accurate and most up-to-date information possible. 

Enhanced Oversight
As AI grows more powerful, tools for auditing and tracking decisions will also advance, keeping everything accountable and transparent.

Embracing Contextual Automation with Cassidy

The idea of software that truly understands your operations has been a dream for years. Now, with contextual automation, it’s reality. Instead of juggling countless tools that handle only fragments of your workflow, you can unify everything under one AI-driven system that references all the context it needs.

Cassidy is leading the charge by creating a no-code platform that ties AI reasoning together with real-world tasks. If you’ve ever wondered how to automate those “complicated” processes that involve lots of back-and-forth or too many documents to count, we’re here to help you make it simple.

Join us in shaping the future of AI

Check out we bring contextual automation to life. Whether you’re a small team looking to scale everyday tasks or a large enterprise aiming to handle massive volumes of information, our approach adapts to your needs.

Welcome to the next chapter of AI — where automation does more than just shuffle data. It thinks, it interprets, and it delivers truly contextual results. That’s the promise of contextual automation, and we can’t wait to see how you’ll use it. Sign up for a free demo today.