Monitors Google Drive for transcripts, analyzes calls with Claude/GPT, generates SOW and pricing, creates PandaDoc quotes, routes for Slack approval, emails the final quote with HTML templates, and updates the CRM after signature.
The AI agent ingests meeting transcripts and calendar context to understand client needs. It delegates tasks to specialized sub-agents to craft SOW content and pricing, then populates a PandaDoc quote. It handles Slack-based review, Gmail delivery with branded HTML, and CRM update after signature.
Performs end-to-end quote creation from transcripts and context.
Ingests transcripts from Google Drive and cleans formatting.
Maps transcripts to calendar data to identify the client.
Generates Problems, Solutions, and Action Items via SOW Agent.
Calculates pricing using service catalog and market research.
Creates PandaDoc quote with all tokens populated.
Sends the quote for Slack approval and tracks status.
The before state shows manual, error-prone quoting from scattered transcripts and no automated pricing. After implementation, quotes are generated quickly with consistent scope and pricing, approved through Slack, delivered via branded emails, and CRM is updated on signature. Before: transcripts not aligned to client, pricing guesswork, inconsistent quotes, slow delivery, manual CRM updates. After: accurate client matching, data-driven pricing, repeatable quote templates, fast approvals, and automatic CRM onboarding.
A simple 3-step flow that non-technical users can follow.
Google Drive detects a new transcript in the designated folder, the AI agent cleans the text, and associates the client using calendar data.
A central orchestrator analyzes the call, then delegates tasks to SOW Agent and Pricing Agent for tailored content and pricing.
PandaDoc creates the quote, Slack handles human approval, Gmail sends the branded HTML quote, and Notion/CRM is updated after the signature.
A realistic scenario showing time-to-quote and outcomes.
A 28-minute discovery call transcript is saved to Google Drive. Within 2 minutes, the AI agent cleans and maps the transcript to the client in the calendar. The SOW Agent produces the Problems, Solutions, and Actions, while the Pricing Agent proposes three service tiers. PandaDoc fills the quote tokens and creates a proposal; Slack notifies a reviewer for approval. After approval, the quote is emailed to the client with a branded HTML template, and after signature, the CRM (Notion) is updated and a welcome email is sent.
Roles that can leverage automated quoting from transcripts.
Need scalable, consistent quotes across multiple clients
Require rapid proposals after discovery calls
Standardize pricing and documentation workflows
Deliver professional quotes quickly to win engagements
Align quotes with project scope and milestones
Ensure CRM reflects signed deals and onboarding steps
The AI agent works inside and across your tools to automate the flow.
Monitors for new transcript files and stores processed data.
Identifies client context and maps transcripts to the correct contact.
Creates the quote document and token population.
Provides LLM capabilities for analysis and task delegation.
Gathers market research to inform pricing.
Handles human-in-the-loop approvals and status visibility.
Sends the final HTML quotes to clients.
Updates CRM client status after signature.
Concrete scenarios where this AI agent adds value.
Practical answers to common concerns about the AI agent.
The agent accesses transcripts stored in Google Drive, calendar context for client matching, PandaDoc templates, and Notion CRM. It uses OpenRouter for LLM-based analysis and pricing, Perplexity for market research, and Slack/Gmail for approvals and delivery. Data handling follows your configured permissions and security settings. All actions are logged for auditability.
Yes. The Pricing Agent considers the catalog and market data to propose multiple service tiers or bundles. The SOW Agent structures corresponding problems, solutions, and actions for each tier. The PandaDoc document then stacks the chosen options with accurate pricing and terms.
Pricing combines service catalog data with market research from Perplexity. The Pricing Agent applies your target margins and currency rules, ensuring consistency across quotes. Real-time adjustments can be made if inputs change, and the final pricing is populated into the PandaDoc template.
Data is processed within your integrations and governed by your existing security policies. Access is limited to the AI agents, with logs and approvals available for review. Sensitive client data can be masked or excluded from transcript exports if required.
After the quote is generated, Slack sends a notification to the designated reviewer with approve/reject actions. The reviewer can add comments, and the system will only proceed to delivery after explicit approval. This keeps governance intact while accelerating the cycle.
Notion is used for client status and onboarding tracking, and PandaDoc templates are used for quotes. You can customize the templates and tokens, and the agent will populate them automatically during the quote creation step.
Yes. You can tailor the trigger folder, calendar matching rules, pricing margins, template fields, and approval workflows. The AI agent is designed to adapt to your specific service catalog and contractual terms while preserving the end-to-end flow.
Monitors Google Drive for transcripts, analyzes calls with Claude/GPT, generates SOW and pricing, creates PandaDoc quotes, routes for Slack approval, emails the final quote with HTML templates, and updates the CRM after signature.
