Sales Agents

Streamline your sales process with custom AI agents.

Lead Qualification Agent

  • task:Automatically score and qualify all inbound leads based on predefined criteria, ensuring hot leads are routed instantly to the right sales representative.
  • system access:CRM (e.g., HubSpot, Salesforce), Marketing Automation Platform, Website Forms, Lead Enrichment Tools (e.g., Clearbit, ZoomInfo).
  • data access:Form submission data (email, company, role), lead activity data (website visits, content downloads), and third-party enrichment data.
  • why do this:Manual lead qualification is a time-consuming bottleneck that results in slow response times and missed opportunities. This automates the process to ensure no high-value lead is ever missed.
  • value of doing this:
    • Reduces lead response time from hours to minutes.
    • Increases the percentage of qualified leads delivered to the sales team by up to 40%.
    • Frees up sales development representatives for more strategic outreach.
  • how to do this:Access inbound form submissions, pull and enrich contact data, run the data through a scoring model, and update the lead's status in the CRM based on the score.
  • when to do this:Real-time. The agent should run continuously, scoring leads as they are submitted.
  • frequency:Continuous
  • skill level:Mid-level
  • risks:Medium
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Instructions
  1. Connect to designated website forms and lead enrichment tools.
  2. Monitor for new form submissions.
  3. Upon submission, pull the contact's name, email, and any other available data.
  4. Run the lead's email through the enrichment tool to pull company size, industry, and role.
  5. Run a lead-scoring algorithm based on pre-set criteria (e.g., company size > 50, C-level title).
  6. Update the lead's record in the CRM with the new score and qualification status.
  7. If the score meets the "hot lead" threshold, assign the lead to the appropriate sales rep.

Sales Scheduling Coordinator

  • task:Coordinate and book sales meetings in real-time by automatically finding mutual availability between a sales rep and a prospect, removing all manual back-and-forth.
  • system access:CRM, Calendar Tool (e.g., Google Calendar, Outlook Calendar), Scheduling Platform (e.g., Calendly, Chili Piper).
  • data access:Sales rep availability (calendar data), prospect contact information (name, email), and relevant CRM deal data.
  • why do this:The back-and-forth of scheduling is a major point of friction that slows down the sales cycle and creates a poor prospect experience. This provides an instant, seamless path to the next conversation.
  • value of doing this:
    • Reduces the average time to book a meeting by 80%.
    • Increases sales rep efficiency and time spent on value-added activities.
    • Improves prospect experience and satisfaction.
  • how to do this:The agent will receive a meeting request, access the sales rep's calendar to find an open slot, and send an automated calendar invitation to both parties.
  • when to do this:Real-time. The agent activates immediately upon a scheduling request.
  • frequency:On-demand
  • skill level:Mid-level
  • risks:Low
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Instructions
  1. Connect to the designated calendar and CRM APIs.
  2. Receive a meeting request from a prospect via a form or link.
  3. Access the calendar of the assigned sales rep to find a mutually available time slot.
  4. Generate a calendar invitation for the designated time and send it to both the rep and the prospect.
  5. Update the CRM deal record to reflect the scheduled meeting and send a confirmation to the sales rep.

Quotation Configuration Agent

  • task:Automatically generate accurate, branded product or service quotes for sales representatives based on customer requests, internal pricing rules, and inventory.
  • system access:CRM, ERP (for inventory data), Pricing Engine, Product Database, Quoting Tool (e.g., PandaDoc, Conga).
  • data access:Product SKUs, pricing rules, inventory levels, customer-specific discounts, and prospect details.
  • why do this:Manually creating quotes is a time-consuming, detail-oriented task that is prone to human error and can significantly delay the sales process.
  • value of doing this:
    • Reduces time to quote from hours to minutes, accelerating the sales cycle.
    • Eliminates human error in pricing, ensuring 100% quote accuracy.
    • Frees up sales reps to focus on relationship-building and closing deals.
  • how to do this:Pull product and pricing information from the designated databases, apply a set of pre-configured business rules and discounts, and generate a customized quote document.
  • when to do this:On-demand. The agent is activated when a sales rep or prospect requests a quote.
  • frequency:On-demand
  • skill level:Mid-level
  • risks:High
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Instructions
  1. Connect to the designated CRM, product database, and pricing engine.
  2. Receive a quote request from a sales rep, including the selected products, services, and quantities.
  3. Pull the most current pricing and inventory data for all requested items.
  4. Apply any applicable pricing rules or customer-specific discounts.
  5. Generate a branded quote document (e.g., a PDF) with a unique identifier.
  6. Attach the quote to the relevant deal in the CRM and send it to the prospect.

Deal Outcome Analyst

  • task:Analyze CRM data to identify key patterns and factors that influence the outcome of sales deals, providing actionable insights for sales leadership and teams.
  • system access:CRM, Business Intelligence (BI) Dashboard, Communication Tools (e.g., Slack, Microsoft Teams).
  • data access:Deal records (deal size, deal stage history), communication logs, call and meeting data, and a history of win/loss reasons.
  • why do this:Sales leaders and reps often rely on intuition to understand what drives deal success. This provides a data-driven, objective analysis of performance, enabling smarter strategies.
  • value of doing this:
    • Increases forecasting accuracy by up to 20%.
    • Identifies trends in successful deals to optimize the sales process.
    • Reduces manual data analysis time for sales managers.
  • how to do this:The agent will run a recurring analysis of all CRM deal data, identify correlations between activities and outcomes, and generate a clear, concise report or dashboard for leadership.
  • when to do this:Scheduled. The agent runs at predefined intervals (e.g., weekly, monthly, or quarterly).
  • frequency:Weekly
  • skill level:High-level
  • risks:Low
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Instructions
  1. Connect to the designated CRM API.
  2. On the scheduled date, pull all relevant deal data, including deal status, stage history, and communication activity.
  3. Run the data through a series of analytical models to identify key patterns (e.g., correlation between number of meetings and win rate, or commonalities in won deals).
  4. Generate a summary report that highlights the top insights and trends.
  5. Send the report to sales leadership via email or a designated communication channel.

Pipeline Forecast Analyst

  • task:Analyze the current sales pipeline to generate an accurate, data-driven sales forecast, predicting future revenue and identifying deals at risk.
  • system access:CRM, Business Intelligence (BI) Tools.
  • data access:All current sales opportunities (deal size, stage, close date), historical deal data (win/loss rates by stage), and sales team activity logs.
  • why do this:Manually forecasting future revenue is time-consuming and often based on intuition, leading to inaccurate projections and poor resource allocation.
  • value of doing this:
    • Provides a more accurate and reliable sales forecast.
    • Allows for proactive identification of deals that are likely to stall or fail.
    • Enables smarter financial planning and resource management.
  • how to do this:The agent will ingest real-time pipeline data, apply a predictive model based on historical win rates and deal stage velocity, and generate a rolling forecast report.
  • when to do this:Scheduled. The agent should run at a set cadence (e.g., daily or weekly) to provide a continuously updated forecast.
  • frequency:Weekly
  • skill level:High-level
  • risks:Medium
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Instructions
  1. Connect to the designated CRM API.
  2. On a scheduled basis, pull all open deal data, including current deal stage, estimated close date, and recent activity.
  3. Run the data through a predictive analytics model that uses historical win rates by stage to generate a weighted forecast.
  4. Flag any deals that show low activity or have been in a single stage for too long.
  5. Generate and distribute a forecast report to sales management.