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Once PG:AI is connected to your AI tool, you interact with it using natural language. Here are real-world examples of how sellers, BDRs, and sales leaders use PG:AI through Claude, Cursor, and other AI assistants.

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Meeting Preparation

The most common use case. Ask your AI to prepare you for an upcoming meeting, and it pulls together everything PG:AI knows about the account.
Prompt:
I have a meeting with Airtable tomorrow. Help me prepare.
What happens: Your AI calls pgai_company with include: ["profile", "insights", "financials", "technologies", "contacts_summary", "events"], then synthesises everything into a briefing.You get: Company overview, recent strategic insights, financial highlights, technology stack, key contacts, and any recent events - all in one response.

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Account Research

Quickly understand any account without opening multiple tabs or dashboards.

Technology Intelligence

“What technologies does Frasers Group use? Are there any recent job postings for data roles?”
Pulls technology stack and filtered job postings in a single response.

Strategic Insights

“What are the latest insights about Tesco? Anything related to digital transformation?”
Returns AI-generated strategic insights, filtered to your question.

Financial Overview

“Give me a financial summary of Snowflake - revenue, growth, and analyst estimates”
Pulls financials, share price data, and analyst consensus in one go.

Competitive Landscape

“Who are Airtable’s main competitors and what’s their tech stack compared to ours?”
Returns competitor data and technology comparisons.

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Contact Discovery

Find and research the right people at your target accounts. Find contacts by role:
“Search for VP of Engineering contacts at my tracked accounts”
Research a specific person:
“Find Sarah Chen at Airtable and get her full contact details”
Discover new contacts:
“Research the top 10 data and analytics contacts at Harness”
Save a contact you found externally:
“Save this contact: James Wilson, Head of Data Engineering at Tesco, [email protected], linkedin.com/in/jameswilson”
Contact discovery works best as a two-step conversation. First search for contacts, then ask for full details on the ones you’re interested in.

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Content Generation

Let PG:AI generate personalised, intelligence-backed sales content.

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Emails

“Write a professional email to the VP of Data at Frasers Group about our analytics platform. Focus on their recent cloud migration.”
Your AI calls pgai_generate with type: "email", pulling in the latest insights about Frasers Group to personalise the message.

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Email Sequences

“Create a 4-step email sequence for Airtable focused on data governance. Keep the tone consultative.”
Generates a multi-touch sequence where each step builds on PG:AI’s intelligence about the company.

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Call Scripts

“Build a call script for reaching out to the CTO at Harness about observability”
Produces a structured script with an opening, discovery questions, value propositions, and objection handling - all tailored to Harness.

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Account Management

Keep your PG:AI account up to date through natural conversation. Add a new company:
“Add Stripe to my tracked accounts”
“Start tracking datadog.com - I want to keep an eye on their hiring trends”
Save contacts:
“Add Sarah Chen as a contact at Airtable. She’s the VP of Engineering. Email: [email protected]”

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Advanced Workflows

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Value Pyramids

“Generate a value pyramid for Snowflake - focus on data engineering and cost optimisation”
Creates a structured value proposition framework showing how your solution maps to the company’s priorities at executive, management, and operational levels.

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Enablement Guides

“Create an enablement guide for the Tesco account focused on their digital transformation initiatives”
Produces a comprehensive guide your team can use to ramp up on the account.

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Multi-Step Research

Have a natural conversation that chains multiple tools together:
You: “What companies am I tracking in the EMEA territory?” AI: Lists your EMEA companies from the territories resource. You: “Which of those are hiring for data roles?” AI: Searches job postings across those companies. You: “Great - generate meeting prep for the top 3 that are actively hiring” AI: Creates tailored prep packs for each company.

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Tips for Better Results

Instead of “Tell me about Airtable”, try “What are Airtable’s latest strategic insights and what technologies are they using?” - this helps the AI request exactly the right data sections.
PG:AI fuzzy-matches company names, so “Airtable”, “airtable”, and “Airtable Inc” all work. Use whichever feels natural.
Your AI remembers context within a conversation. Start with research, then ask for content generation based on what you learned - the AI will connect the dots.
When generating emails or call scripts, specify the tone: professional, casual, formal, or consultative. If you don’t specify, PG:AI uses sensible defaults.
When looking at job postings, include a keyword: “Show me Airtable’s job postings that mention machine learning” - this filters results before they reach you.