Apollo AI Glossary

The AI content center is the heart of Apollo AI. You can provide the content center with your company’s messaging, audience, and common objections, so that Apollo AI can tailor AI-generated content to fit your tone and goals. Think of it like giving Apollo AI a cheat sheet about your business. It helps Apollo AI write better emails, research more productively, and provide outreach that sounds like you. Before you use Apollo AI, set up the AI content center to reflect your business.

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AI filters are smart search filters in Apollo that help you find contacts and accounts based on insights generated by AI research. Instead of just filtering by basic fields like job title or location, you can use AI filters to search by specific research you've uncovered with Apollo AI.

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AI research on Apollo generates insights into people and companies that reduce manual research time and help you craft personalized messages. Leverage the power of public web search and Apollo’s living contributory database in AI research to understand prospects at scale, personalize your emails, and uncover meaningful contact insights. Check out how to use AI research to get started.

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An AI SDR is a setup or workflow that uses AI tools to automate the typical tasks of a sales development representative. It can help find leads, write emails, personalize outreach, and even build sequences, freeing up reps to focus on conversations that close deals. Check out the outbound copilot on Apollo to get started.

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The AI writing assistant helps you draft emails, replies, and subject lines using plain-language prompts. Just tell it what you want to say, and it generates polished messaging that you can send as-is or tweak to fit your voice. It’s a fast way to go from blank page to send-ready email.

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Apollo AI is the suite of AI features at Apollo that helps enhance how teams work across Apollo. Apollo AI is a set of smart tools that help automate, personalize, and improve your sales workflows. Apollo AI includes features like AI-powered writing, research, call summaries, AI search filters, and more — all designed to help you move faster and sell better. Learn more about what you can do with Apollo AI.

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Artificial intelligence (AI) refers to computer systems that can perform tasks that normally require human thinking—like learning, decision-making, and language generation. In Apollo, AI helps automate sales tasks, personalize communication, and deliver insights faster than you could on your own. Learn more about what you can do with Apollo AI.

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Assisted prompting is a guided experience that helps you write better prompts for AI research. Assisted prompts are great for beginners looking to use AI that don't want to figure out prompt engineering from scratch. Assisted prompts help you get stronger, more relevant AI outputs without needing to be an expert.

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Bias in AI refers to unfair or unbalanced outcomes that result from the data or rules used to train a model. If AI is trained on limited or skewed examples, it can reflect those same patterns in its results, like over-personalizing to a certain industry or making assumptions about titles. In sales, being aware of AI bias helps you double-check that recommendations make sense for your real audience. Apollo recommends that you proofread and review any AI response to ensure it meets the voice, tone, and output you expect. Check out AI Prompt Best Practices to learn more.

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A context window is the amount of information an AI model can "remember" while generating a response. If you overload it with too much data, it may forget earlier parts of the conversation or message. By keeping your inputs clear, structured, and focused, you can help AI models stay on track and generate better results. Check out AI Prompt Best Practices to learn more.

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Conversation insights use AI to analyze recorded sales calls and meetings. Apollo AI picks out key moments, tracks engagement, and surfaces insights, like objections raised, product interest, or next steps. Use conversation insights to save you from having to take notes, or as a manager, to coach towards success more effectively.

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A deterministic AI model consistently produces the same output when given the same input under identical conditions. There is no randomness involved in its internal processes. Examples of deterministic AI include traditional spam filters and rule-based expert systems. Learn about how Apollo AI works.

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A dynamic variable is a placeholder in Apollo like {{first_name}} or {{job_title}} often included in meetings or AI research, that automatically fills in personal details from the contact. Dynamic variables let you scale personalization without copying and pasting individual info. You can create 3 types of variables:

1. Basic dynamic variables allow you to insert Apollo prospect data like name, location, or job title.
2. Advanced dynamic variables allow you to string custom dynamic fields with limited conditional logic, like fallbacks if there's no data for a specific field for a contact.
3. Custom dynamic variables are automatically generated when you create a custom field in Apollo, so you can use custom data in sequences, emails, or AI research.

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Explainability is the ability to understand how and why an AI made a certain decision or suggestion. It’s important for building trust, especially when AI is recommending who to reach out to or what to say. Clear explanations help you evaluate whether AI outputs are reliable or need adjustment. Learn how Apollo ensures explainability in its AI models.

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Few-shot learning is when an AI model learns from just a small number of examples. Instead of needing thousands of data points, it can figure out a pattern after seeing just a few. In Apollo, this allows the AI to adapt quickly to new messaging styles or prompts with minimal input. Learn more about what you can do with Apollo AI.

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Fine-tuning is the process of adjusting an AI model using new data to make it better at specific tasks. In Apollo, you can create AI research that builds off existing research.

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Generative AI refers to AI systems that can generate new content, like emails, images, or call summaries. It’s the type of AI that powers tools like ChatGPT, a popular large language model (LLM). Learn more about how Apollo uses different AI models.

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A hallucination happens when AI confidently generates something that isn’t true. This could be a fake stat, a wrong fact, or an incorrect company description. It’s a reminder that while AI can write quickly, you should always review its output for accuracy. Check out AI Prompt Best Practices for more prompting tips.

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Human-in-the-loop means there’s always a person reviewing or guiding the AI’s decisions. In Apollo, it means you can preview and edit AI research, review AI-generated content, approve suggestions, or intervene when needed, so the system works with you. Apollo recommends that you proofread and review any AI response to ensure it meets the voice, tone, and output you expect. Check out AI Prompt Best Practices to learn more.

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A large language model is a type of AI trained on massive amounts of text so it can understand and generate human language. Models like GPT-4 are LLMs, and they power features like message generation and research in Apollo. Learn more about the LLMs that power Apollo AI.

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Lead scoring is a way to rank prospects based on how likely they are to convert. Apollo uses AI to score leads automatically using data like engagement, fit, and buying signals. The higher the score, the hotter the lead, helping reps prioritize the best prospects.

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Machine learning is a branch of AI that trains computers to recognize patterns and make decisions without being explicitly programmed. It’s how Apollo AI learns what kinds of messages work, what a good lead looks like, and how to improve over time. Learn more about what you can do with Apollo AI.

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Model drift happens when an AI model’s accuracy drops over time because the data it sees changes. For example, if your prospects’ behavior shifts, a model trained on old habits might become less helpful. Keeping models updated ensures the AI stays sharp and relevant. Learn how Apollo AI stays up to date.

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Natural language processing is the technology that lets computers understand and respond to human language. NLP allows Apollo AI to write emails, interpret your chat prompts, and summarize conversations in a way that feels natural and clear. Learn more about how Apollo AI works.

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The outbound copilot is a tool in Apollo that helps you launch outbound campaigns faster with AI-powered assistance. The copilot can find contacts, build messaging, and automatically add prospects to sequences or create evergreen lists, so you can go from idea to outreach in less time.

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A prompt is the instruction you give to an AI model to tell it what you want. It can be a simple request like "write a follow-up email" or a detailed question about a company. The better your prompt, the better the AI’s response. Check out AI Prompt Best Practices to learn how to write great AI prompts.

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Prompt chaining is when you link multiple prompts together to get a more advanced or complete result. One prompt might summarize a call, while another prompt could generate an email from that summary. It’s like building blocks for AI workflows. You can use prompt chaining in Apollo when you create AI research that references each other.

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Prompt engineering is the art of crafting prompts that get the best results from AI. It means knowing how to phrase a request so the AI understands what you want, and returns something clear, accurate, and useful. Check out AI Prompt Best Practices to learn how to write great AI prompts.

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Sales automation uses AI and software to take care of repetitive sales tasks—like follow-ups, lead routing, or email generation. Apollo AI automates these steps so reps can spend more time talking to prospects instead of managing workflows. Learn more about what you can do with Apollo AI.

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Sales intelligence is useful data about prospects, like company news, hiring trends, or buying signals. Apollo AI helps you surface the right info at the right time, so you can reach out with better timing and context. Use AI research to learn more about your prospects and get real-time industry updates . When you engage with personalization, you improve the resonance of your message.

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A sequence is a series of outreach steps in Apollo, like emails or calls, that you set up to engage a prospect over time. When you create a sequence with AI, you can generate and personalize these faster so each step feels relevant to the lead.

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Vibe prompting is a way of setting the tone for AI. Instead of just saying, "Write a summary," you might say, "Explain this like you're casually pitching it to a client over coffee." An emotional beat, or vibe, helps the AI match the energy you want, making it more engaging and fitting for the audience. For sales teams, it’s like giving the AI the right sales persona to make content feel natural and aligned with your brand’s voice. Check out AI Prompt Best Practices to learn how to write great AI prompts.

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A workflow is a set of actions you automate in Apollo to move leads through your sales funnel, like assigning owners, sending emails, or updating statuses. When you create a workflow with AI, workflows can adapt to prospect behavior and trigger smarter next steps automatically.

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Zero-shot learning means an AI can perform a task without being given examples first. The AI uses what it already knows to respond to new instructions. That’s why you can ask Apollo AI to write about something it hasn’t seen before and still get a solid result. Learn more about what you can do with Apollo AI.

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