What is an Agent for sales?

A Sales Agent is an autonomous, AI-powered Agent that can run inbound sales conversations end to end – from first response through qualification and routing – without human intervention. It uses natural language, business context, and product knowledge to ask the right questions, evaluate fit, and guide buyers to the right outcome.

Agents can seek information, make decisions, and take action to qualify and route high-intent opportunities into pipeline.

Core capabilities:

• Engage proactively Agents can proactively engage prospects, responding to context and user behavior to provide relevant guidance and act when intent is highest.

• Guide discovery They can guide prospects through discovery, answering questions about pricing and features, addressing objections, and matching solutions to their needs.

• Qualify intelligently They ask the same questions your SDRs would, applying your existing criteria to identify the strongest opportunities for your team.

• Close with confidence When it's time to act, they can close with confidence, booking meetings via tools like Calendly, guiding qualified buyers into trials or subscriptions, and syncing directly with your CRM to route opportunities to your sales team with full context.

Why are they different from chatbots?

Old-school chatbots follow rigid, scripted decision trees and are limited to just answering questions and escalating sales conversations. Sales Agents ask targeted questions, evaluate responses against your criteria, handle objections using your approved content, and route buyers to the right outcome, whether that's a booked meeting, self-serve trial, or clean disqualification.

They're conversational, engaging, intelligent, and able to adapt to the context of any situation. They enable prospects to get what they need, fast, sales teams to get time back to focus on higher-value work, and businesses to grow pipeline without a linear increase in cost.

How do Agents work?

Agents:

• Deeply understand buyer intent Using large language models (LLMs) and advanced natural language understanding.

• Qualify opportunities and personalize interactions Using prospect data, conversation history, and real-time context.

• Generate contextually accurate answers Using a technique called retrieval-augmented generation (RAG), Agents pull relevant content from your sales knowledge base and other defined sources to craft precise, brand-aligned responses.

• Know when to route to the right outcome They follow your defined criteria to guide each conversation to the right outcome, whether that's a sales meeting, a self-serve path, or disqualification. They pass full context to your sales team to pick up seamlessly.

• Continuously improve through feedback They support a continuous improvement process where teams review performance, analyze conversations, and refine the system over time. This reflects a closed-loop system where AI is both operational and diagnostic.

Important note: not all Agents are built the same way. For example, Fin is powered by in-house AI models and a proprietary Fin AI Engine™ that draws on shared context, deep business knowledge, and seamless integrations to unify the customer and prospect experience.

Fin builds on the foundation of the highest-performing Agent for customer service, introducing an agentic architecture that is purpose-built for inbound sales conversations. It includes:

• A custom retrieval-augmented generation (RAG) system that understands the question, identifies, and ranks content by accuracy and relevance.

• An agentic system that adapts in real time, puts the end user in the driver's seat, and responds to their needs on the spot while guiding them forward to the right outcome.

• Automatic balancing between answering questions and advancing the sale, gathering information, qualifying leads, and routing to the right team without manual intervention.

• Automatic follow-up on abandoned conversations, when a conversation drops off, Fin re-engages leads who left their email to continue where they left off.