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Contextual Automation: The Next Chapter of AI

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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.

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Cassidy vs. ChatGPT Enterprise: Contextual AI Automation vs. Standalone Chatbot
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Cassidy vs. ChatGPT Enterprise: Contextual AI Automation vs. Standalone Chatbot

AI models

Overview

While both Cassidy and ChatGPT Enterprise utilize AI to enhance productivity, they serve distinctly different purposes. Cassidy is a robust, contextual AI automation platform designed to create custom workflows, integrate deeply into your existing tools, and leverage multiple AI models. ChatGPT Enterprise functions primarily as a standalone conversational chatbot built exclusively around OpenAI’s models, lacking deep workflow automation or extensive integrations.

Cassidy provides enterprises with adaptable AI solutions that scale across business units, ensuring contextually intelligent automation tailored specifically to your workflows.

Feature Comparison

Feature Cassidy ChatGPT Enterprise
Automation ✅ Flexible AI workflows ❌ Chat-only interaction
AI Models ✅ Multiple AI models (GPT-4, Claude, Gemini) ❌ Single model (GPT-4)
AI Assistants ✅ Integrated in Slack, Teams, Chrome ❌ No external integrations
Knowledge Base ✅ Unified enterprise-wide knowledge ❌ No central knowledge base
Support & Onboarding ✅ Dedicated enterprise support ❌ Generalized, limited support

Flexible AI Models vs. Single Provider Limitation

Cassidy allows your business to leverage multiple leading AI models, ensuring that you always have access to the best tool for the job. ChatGPT Enterprise restricts users to OpenAI’s proprietary models only, significantly limiting your flexibility and potentially future innovation.

Workflow Automation, Not Just Conversations

Cassidy empowers enterprises with comprehensive workflow automation, seamlessly linking multiple business tools and processes to perform tasks end-to-end without human intervention. ChatGPT Enterprise lacks automation capabilities, serving only as a conversational assistant without any capability for task automation or execution across multiple apps.

Integrated AI Assistants vs. Isolated Chat Experience

Cassidy's custom AI assistants integrate seamlessly into everyday business platforms like Slack, Microsoft Teams, and Chrome, delivering contextual support and real-time actions. In contrast, ChatGPT Enterprise offers a closed interface without built-in external integrations, restricting AI interactions to basic conversational exchanges within its own environment.

Centralized Enterprise Knowledge Management vs. Fragmented Storage

Cassidy provides a unified enterprise-wide knowledge base that continuously updates and enriches the context available to your entire organization, ensuring accuracy and relevance. ChatGPT Enterprise’s knowledge storage is ephemeral, restricted to individual sessions, and lacks permanent enterprise-wide knowledge management.

Dedicated Enterprise Support vs. Generic Onboarding

Cassidy offers personalized, white-glove onboarding, dedicated account management, and comprehensive training, ensuring your enterprise successfully adopts and scales AI across teams and processes. ChatGPT Enterprise provides general self-service onboarding with limited personalized support, potentially hindering widespread adoption.

Cassidy: The Smarter Enterprise AI Solution

ChatGPT Enterprise is suitable for standalone, conversational interactions, but Cassidy offers a far more powerful, scalable, and contextual AI solution designed specifically for enterprises. With its extensive integrations, multi-model flexibility, robust workflow automation, and enterprise-grade knowledge management, Cassidy empowers your business to fully harness the potential of AI across your entire organization.

Discover how Cassidy can elevate your enterprise workflows by booking a demo today.

Optimizing Your Website Content for AI Search Engines: How to Effectively Boost Conversion Rates
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Optimizing Your Website Content for AI Search Engines: How to Effectively Boost Conversion Rates

Industry news

Over the past year, AI search engines like ChatGPT, Perplexity, and Bing AI have begun to change how people discover brands online. Instead of scrolling through 10 blue links on Google, users now get curated answers directly inside conversational interfaces. That shift means companies need to rethink how they structure, distribute, and monitor their content.

Why AI search matters for conversion, not just visibility

Traditional SEO chases ranking. AI search distributes trust. When a user asks a question, they often see a single synthesized answer. If your content is cited or your brand is mentioned, you earn disproportionate attention. The goal is not traffic for its own sake. The goal is to influence qualified buyers at the moment of intent and move them to a clear next step.

What changes in an AI search world

  • Fewer results, more synthesis. You must be quotable, citable, and easy to reuse.
  • Credibility beats volume. Clear, narrowly scoped, and well supported pages are more useful than generic long reads.
  • Distribution happens across formats. YouTube, Reddit, and Wikipedia often appear in answers. Your plan should treat them as first class channels.

What recent data suggests about AI search behavior

Use these directional takeaways to shape your plan. The specific percentages below are from a recent study.

  • Relevance and quality beat raw traffic. ChatGPT and Perplexity often reference low traffic sites. About 44.88% of links in Perplexity and 47.31% in ChatGPT go to sites with minimal traffic. New sites can surface if the content is clear, useful, and well structured.
  • Domain age patterns differ by engine. ChatGPT and Bing frequently use younger domains, often under 5 years old. Google AIO skews older, with 49.21% of links going to domains older than 15 years. If you are new, prioritize Bing and ChatGPT tactics while you build long term authority for Google.
  • Bing prefers short, direct answers. Average response length is about 398 characters with about 3.13 links per answer. Write concise, plain language summaries that can be quoted.
  • YouTube and user generated sources matter. ChatGPT links to YouTube in about 11.30% of answers, Perplexity in about 11.11%. ChatGPT often cites Reddit and Wikipedia. Create helpful video content, contribute responsibly to community sources, and use clear references on your pages.
  • Diversify your cited sources. ChatGPT and Perplexity overlap in their domains by about 25.19%, and both pull from a wide set. Bing often references practical sites such as WikiHow, and also health oriented sites like Healthline. A broader reference strategy helps your pages appear alongside familiar authorities.
  • Balance keywords. Niche and specific keywords increase the odds of citation in ChatGPT and Perplexity where less popular domains can win. Target your content to answer the questions that real buyers ask.

These signals are directional. You do not need to memorize the numbers. You need to shape content so that it is reusable by AI systems and persuasive to humans.

Strategy pillars

  1. Relevance and clarity
  • Write to a single search intent per page.
  • Lead with an answer, support with proof, then add depth.
  • Use descriptive headings, short paragraphs, and lists that AI can parse.
  1. Channel fit by engine
  • For Bing: short, simple answer blocks, minimal jargon, clear definitions, and practical steps.
  • For ChatGPT and Perplexity: authoritative walkthroughs with citations to credible, diverse sources and helpful visuals.
  • For Google AIO: long term credibility, consistent terminology, stable URLs, and evidence of expertise over time.
  1. Format portfolio
  • Text pages that answer specific questions.
  • YouTube videos with transcripts and chapters.
  • Wikipedia involvement if appropriate and compliant with policies.
  • Reddit participation in relevant communities.
  1. Ethical participation
  • Follow rules for Wikipedia and Reddit. Disclose affiliations where required. 
  • Avoid spam and contribute useful information that stands on its own.
  1. Conversion alignment
  • Every page and post should include a logical next step. 
  • Offer checklists, calculators, templates, or short demos. 
  • Build credibility before a call to action.

Tactically Putting It Into Practice

Here’s where companies often hit a roadblock: creating and distributing this volume of content consistently across multiple platforms. That’s where automation helps.

Cassidy-enabled workflows that reduce manual effort

Automation helps you keep up with the surface area of AI search while staying on brand. The following workflow recipes are examples. They are useful even if you build them in a different tool. Cassidy makes them easy to connect to your systems and to run on a schedule. Book a demo call with us to see the following workflows in action!

Workflow 1: Reddit brand mention monitor and guided engagement

Goal: Identify brand mentions on Reddit and prepare helpful, non promotional replies.

Trigger: Hourly or daily search across relevant subreddits for your brand name, product names, and category keywords.

Inputs: Keyword list, list of allowed subreddits, brand voice rules, compliance guardrails.

Steps

  1. Fetch new threads and comments that match filters.
  2. Classify intent. Examples: product comparison, how to, troubleshooting, procurement, off topic.
  3. Score priority by reach, subreddit relevance, and recency.
  4. Draft a reply that follows the response rubric. Include sources and a link to a neutral resource first.
  5. Route to a human for final review and posting.

Output: Suggested replies in Slack or email with direct links. Status tracked in a simple dashboard.

Guardrails

  • Respect subreddit rules. Do not mass post. Always disclose affiliation if required. 

If you want to see this in action live, book a demo with us.

Workflow 2: Blog to social to Reddit distribution

Goal: Repurpose every blog post into short posts for LinkedIn, X, and suitable Reddit communities.

Trigger: New post published or updated.

Inputs: Blog URL, summary paragraph, three key takeaways, two external citations to include as context.

Steps

  1. Generate one LinkedIn post, one Instagram post, and one X post that summarize the main lesson.
  2. Generate a Reddit friendly version that removes promotional language and adds a neutral resource.
  3. Create UTM tagged links for attribution.
  4. Schedule posts and alert owners for manual Reddit posting where rules require human participation.

Output: Platform ready drafts with tracking links and a checklist for the human poster.

If you want to see this in action live, book a demo with us.

Workflow 3: Category question monitor for weekly outreach

Goal: Track recurring high intent questions such as “best HVAC company in Houston” or “how to evaluate RFP automation.”

Trigger: Weekly scheduled run.

Inputs: Question patterns, geo filters, list of forums and Q and A sites.

Steps

  1. Collect new threads that match patterns.
  2. Summarize the question and current best answers.
  3. Suggest a helpful contribution that cites neutral sources. Include a short disclosure line.
  4. Propose a one paragraph answer block and a link to a non promotional guide.

Output: A short brief per thread with suggested text. Owner can post or adapt.

If you want to see this in action live, book a demo with us.

Workflow 4: YouTube topic radar and script draft

Goal: Publish videos that align with high intent topics that AI engines often cite.

Trigger: Weekly or biweekly scheduled run.

Inputs: Topic list, competitors, associated blog posts, brand voice.

Steps

  1. Identify trending questions and gaps in your library.
  2. Propose a title, a hook, and a 5 step structure.
  3. Draft a script with on screen prompts and a CTA.
  4. Generate a blog companion outline and cross links.

Output: A script draft and outline ready for recording and publishing.

If you want to see this in action live, book a demo with us.

Conclusion: The New SEO Playbook

AI search engines are not replacing SEO—they’re rewriting the rules. The old game of chasing rankings with keyword-stuffed content is giving way to a new model where:

  • Clarity beats complexity.
  • Credibility beats volume.
  • Distribution beats centralization.

By focusing on relevance, diversifying your presence across platforms AI engines actually cite, and automating the grind with workflows, brands can not only be seen—they can be trusted. And trust at the point of intent is what drives conversions.

Facts and figures courtesy of https://seranking.com/blog

Cassidy vs. Loopio
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Cassidy vs. Loopio

About us

AI Automation Platform vs. RFP Response Software

When evaluating automation platforms, Cassidy and Loopio often surface as contenders for streamlining RFPs and proposal management. However, these platforms differ significantly in their scope and flexibility. Loopio is a narrowly focused RFP response tool, providing structured, predefined workflows specifically built around proposal generation. In contrast, Cassidy is a powerful, contextual AI automation platform designed to dynamically adapt to your unique enterprise processes, far beyond just RFP responses.

Cassidy not only accelerates RFP responses, but automates complex, context-driven workflows across sales, customer support, operations, HR, and beyond. Loopio’s rigid structure may speed up repetitive proposals but lacks adaptability, restricting its usefulness.

Feature Comparison

Feature Cassidy Loopio
Automation Approach ✅ Contextual, AI-driven workflows tailored to unique processes ❌ Rigid, predefined proposal workflows only
AI Flexibility ✅ Adaptive AI that learns and evolves dynamically ❌ Static AI limited to content retrieval and reuse
Customization ✅ Fully customizable automation based on your unique needs ❌ Limited customization; forces users into preset formats
Real-time AI Assistants ✅ Interactive AI assistants embedded in Slack, Teams, Chrome ❌ No interactive AI; basic platform-based content retrieval
Knowledge Integration ✅ Unified knowledge base usable across multiple business functions ❌ Siloed RFP-specific content not accessible enterprise-wide
Enterprise Onboarding ✅ Dedicated onboarding, ongoing training, and personalized support ❌ Limited onboarding focused solely on proposal teams

Contextual AI Automation vs. Static Content Lookup

Cassidy’s AI-powered automation goes far beyond simple content retrieval. Its contextual AI understands and dynamically adapts to your business processes, continuously improving workflows by extracting information, generating context-aware responses, and automating complex tasks end-to-end.

Loopio’s automation is essentially limited to suggesting previously stored answers from its content library. This static approach requires significant manual upkeep and struggles to handle non-standard or complex RFP scenarios, often forcing users back into tedious manual work.

Custom Workflows Tailored to Your Enterprise

No two businesses handle proposals or processes the same way. Cassidy recognizes this and provides highly customizable AI workflows precisely adapted to your company’s specific requirements. You can define your processes, tone, and even AI behavior, creating workflows that perfectly match your operational style.

Loopio, however, restricts teams to predefined structures. Its limited customization options mean that if your proposals vary significantly, your team might frequently revert to manual interventions, reducing the platform's value.

Unified Enterprise Knowledge

Cassidy’s enterprise-wide knowledge base centralizes your critical business content—whether proposal answers, customer interactions, internal policies, or sales materials—in one intelligent repository. This interconnected knowledge powers all of Cassidy’s automation tools, ensuring consistency and continuous improvement.

Loopio’s knowledge management is isolated to RFP-related content, creating data silos and limiting your enterprise’s ability to leverage insights across different departments or workflows.

Interactive AI Assistants Where You Work

Cassidy embeds intelligent, interactive AI assistants directly into Slack, Microsoft Teams, Chrome browsers, and web applications. This enables employees across your enterprise to access real-time, contextual support seamlessly within their daily workflow.

Loopio provides no interactive AI assistance outside its own interface, restricting content lookup and limiting employee engagement and accessibility.

Scalable AI for Enterprise Teams

Cassidy prioritizes scalable enterprise adoption with comprehensive onboarding, dedicated account management, ongoing training, and personalized support. This approach ensures quick implementation, team-wide adoption, and continuous optimization across various business units.

Loopio’s onboarding and scalability are limited strictly to proposal teams, with minimal ongoing support or adaptability to broader organizational needs.

Cassidy: The AI Platform Built for Your Entire Business

Loopio offers efficiency strictly within rigid, predefined proposal workflows. Cassidy, however, delivers expansive, contextual AI automation that adapts to your unique processes, breaks down knowledge silos, and supports dynamic, enterprise-wide workflows. Cassidy represents the smarter long-term investment, equipping your business for success beyond RFPs.

Ready to unlock the full potential of AI-driven automation?

Book a Demo today and experience the Cassidy difference firsthand.

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