Published at: 2026-09-17
Smart quote agent
The smart quote agent turns scattered inquiry details into executable quote actions.
It fits the front stage of sales response and helps your team move faster and more consistently from inquiry intake to quote generation.
Overview
Product positioning
The smart quote agent is an AI assistant for sales teams, sales operations, and quote management, or CPQ, scenarios.
It focuses on questions such as what the customer needs, how the price should be calculated, and how to return a quote fast.
It is not a simple Q&A bot.
Its core value is to convert inquiry details from chats, emails, and Attachment Content into structured pricing judgment and then generate the follow-up transaction record through pricing rules.
Core concepts
Inquiry parsing
Inquiry parsing means the system identifies customer needs from text, voice, screenshots, emails, POs, or PDFs.Price matching
Price matching means the system matches the right Price Book, sellable scope, and Pricing Policy based on the Product Price, quantity, region, and Account Type conditions.Quote recommendation
Quote recommendation means the system returns executable price suggestions and discount strategies based on pricing rules.Industry know-how
Know-How is the set of industry rules that covers pricing systems, regional differences, product strategies, customer tiers, and business exceptions.
It determines how the system decides what price should apply and how the result should be structured and delivered.Typical business scenarios
| Scenario | Typical question | Best-fit task |
|---|---|---|
| Online inquiry response | A customer just sent a requirement. How do you answer fast? | Understand the demand quickly and return an initial pricing suggestion. |
| High-volume product inquiries | There are many products and complex prices. Manual lookup is too slow. | Match Standard Price and pricing strategies across many products fast. |
| Regional or customer-specific pricing | Different regions and customers follow different rules. | Align regional pricing and customer policies in one process. |
| Attachment-based inquiry handling | A customer sends an inquiry through a screenshot, email, or PO. | Parse the Attachment Content directly and return a quote suggestion. |
| Quote generation | The price is confirmed. How do you create the quote fast? | Generate the quote and pass it to the next workflow. |
Scenarios that do not fit
Do not start with the smart quote agent in these scenarios:
- You only need Data Statistics and do not need a pricing judgment.
- Customer materials are already confirmed and you need to create an order or contract directly.
- The issue is account management or opportunity analysis rather than quote handling.
When the problem has moved from asking for price to generating a formal transaction record, switch to the smart order agent.
Core value
Sales teams often face these problems in the quote stage:
- Inquiry sources are scattered and time-consuming to organize.
- Pricing systems are complex, so manual lookup and rule matching are error-prone.
- Regional pricing, promotion policies, and customer conditions often follow inconsistent logic.
- After the result is ready, the team still needs to re-enter the data into a formal transaction record.
The smart quote agent delivers value in four ways:
- Faster response: It reduces the time spent on copying, price lookup, and manual rule comparison.
- Consistent pricing logic: It uses pricing rules and industry know-how to reduce person-to-person differences.
- Lower risk: It reduces mistakes in manual pricing, discount application, and regional policy matching.
- Faster downstream conversion: The result can continue into quote generation and prepare the next step for orders and contracts.
Why industry know-how matters
The smart quote agent does not fit every company with one universal template.
In real business, industries and companies differ in these areas:
- Regional pricing structures
- Product Bundle strategies
- Promotion and Pricing Policy rules
- Customer tiers and sellable scope
- Cost and margin boundaries
Because of that, the quality of pricing judgment depends on your company-specific industry know-how.
The system combines company rules and business context to decide which matching logic, recommendation strategy, and output wording to use.
Quick start
Learning goals
- Complete one basic inquiry
- Receive a pricing recommendation from the system
- Generate one quote
Prerequisites
- You have access to the smart quote agent.
- You prepared the product, quantity, region, or Account Type conditions.
- For attachment-based inquiries, you prepared screenshots, emails, POs, PDFs, or Word files.
Shortest path
- Open the smart quote agent.
- Enter or upload the customer inquiry.
- Review the pricing recommendation from the system.
- Generate the quote and move into edit or submission.
Completion signs
- The system returns a usable pricing recommendation.
- You can continue to generate a quote.
User guide
How to start an inquiry
You can open the smart quote agent from the
ShareAgent entry point.
You can also enter a quote-related instruction directly and let the system route the request to the right agent.Common prompts include:
- Help me check the price for this product.
- How should I quote this customer in the current region?
- Which discount strategy fits this product set?
- Generate a quote from the attachment.
Typical workflow
Step 1: Provide inquiry information
Enter the product name, quantity, Account Type, and region.
If the information comes from a chat screenshot, procurement attachment, or email, you can Upload Attachments directly.
The source manual also states that the agent supports text, voice, and attachments. This makes it useful for online customer response and mobile work scenarios.
Step 2: Review the pricing recommendation
The system matches the price book, sellable scope, and marketing policy based on the available information.
If the conditions are incomplete, the system asks for the customer, region, or another key factor.
After you add customer information, the system can match a more precise Price Book Price result.
Step 3: Confirm and generate the quote
After the pricing recommendation is acceptable, continue the conversation to generate the quote.
The system carries the quote data into the next page and lets you complete the final review.
If the inquiry comes from social chat content or an attachment, the system also identifies the key details automatically and returns the quote recommendation with next-step guidance based on the Attachment Content.
The source manual also notes support for batch quote and product verification in complex product scenarios.
How to read the output
A useful quote result should answer these questions:
- Which conditions produced the current price
- Whether the result is limited by region, customer status, or policy
- Whether more information is still required
- Whether you can generate the quote directly
If the system says that conditions are incomplete, add the customer, region, and product information first.
If the system already returned a complete pricing recommendation, continue into transaction record generation.
How the result is reused
The smart quote agent mainly supports downstream business actions.
Common reuse patterns include:
- Read the pricing recommendation directly in the conversation.
- Generate a formal quote.
- Use the structured result as the basis for downstream order or contract handling.
Admin guide
Configuration prerequisites
Admins need the required product permissions, pricing rule maintenance capability, and the business extension permissions that fit the scenario.
If your company uses a standard pricing model, you can start testing quickly.
If your company uses complex regional pricing, customer pricing, or special promotion strategies, govern those rules first.
What to prepare
Baseline pricing rules
Prepare these items:
- Price books
- Sellable scope
- Regional pricing logic
- Promotion or marketing policies
Industry know-how or company rules
If your company relies on complex pricing logic, use the Skill Center to extend company-specific scenarios.
Examples include:
- Industry-specific Product Bundle quote rules
- Discount logic for special customer groups
- Exception handling for special products
The source manual uses this entry path: Agents > Skill Center > Create Skill.
You can import a skill or let AI create one to extend your company-specific business scenarios.
Validation after configuration
Use a set of real but low-risk test inquiries for validation.
Check these points:
- Whether the system identifies the key inquiry details
- Whether the matched price books and pricing strategies are correct
- Whether special rules work as expected
- Whether the quote contains the required fields
FAQ
Which input formats are supported
The smart quote agent supports text, voice, images, screenshots, Word files, PDFs, emails, and other common inquiry materials.
Can the company define its own pricing policies
Yes.
If standard strategies do not cover your business case, admins can extend the logic through business rules or custom skills.
Why can the pricing logic differ across customers
Because the result depends on the region, customer conditions, product strategy, and company know-how together.
The same product does not always use the same pricing logic in every context.
When should you switch to the smart order agent
When the inquiry stage is over and the customer starts to provide formal procurement materials for direct order or contract generation, switch to the smart order agent first.