KETUPAContact

USE CASES

Improve how AI agents guide complex product choices—across B2C and B2B commerce.

Whether an AI agent is helping a consumer choose the right product or helping a business customer select and configure the right solution, it has to do more than retrieve relevant information.

It has to apply the right product knowledge, customer requirements, business rules, and exceptions at the right time—and keep them active as the experience continues.

KETUPA improves that behavior in the Agent stack teams already use, implements or co-implements the changes, validates the result, and keeps important behavior reliable over time.

FEATURED USE CASES

An Agent can understand the customer and retrieve the right product information—and still guide the experience incorrectly.

The problem may appear when the Agent applies the right condition too late, treats a likely match as confirmed, uses a general rule when a specific exception applies, loses an important requirement later in the interaction, or presents stronger confidence than the available evidence supports.

KETUPA identifies where that behavior breaks, connects the improvement to the right Agent and commerce controls, and validates the experience after change.

FEATURED EXAMPLE01

B2C | CONSUMER ELECTRONICS

A product can work—and still fail to deliver what the customer asked for.

The buying situation

What the customer needs

“I want a compact, affordable charger for my laptop that supports fast charging.”

What the Agent does

The Agent identifies chargers that can power the laptop and presents lower-wattage options as fast-charging choices before the exact laptop model and charging setup are known.

Where guidance breaks

“Can charge” becomes “meets the fast-charging requirement.”

Those are not the same claim.

Once the distinction is lost, the same unsupported confidence can spread into the recommendation, product ranking, product-card language, follow-up guidance, and the next action.

What better guidance looks like

What better Agent behavior looks like

  1. 01
    Preserve the customer’s real requirement

    Fast charging remains an active requirement—not an optional preference.

  2. 02
    Ask only what changes the answer

    Confirm the device model, required power, cable, or charging setup when those details determine the result.

  3. 03
    Separate capability levels

    Distinguish between compatible, ordinary charging, and confirmed fast charging.

  4. 04
    Use the right confidence

    Do not present an unresolved capability as confirmed performance.

  5. 05
    Keep the experience aligned

    The answer, ranking, product presentation, follow-up, and next step should communicate the same capability state.

How KETUPA improves it

Turn charging-performance logic into Agent behavior.

Product capability data
Structure meaningful charging-capability levels
Agent guidance and qualification
Use supported language and ask for the right information at the right time
Ranking and product presentation
Prioritize products that actually meet the stated requirement
Validation
Rerun the same Agent experience after the change
Ongoing reliability
Preserve the important behavior for future product, model, prompt, and platform changes
FEATURED EXAMPLE02

AUTOMOTIVE | PRODUCT FITMENT & INSTALLATION

A reasonable product direction can still be wrong for the exact vehicle.

The buying situation

What the customer needs

“I have a 2014 cab-and-chassis truck. I’m keeping the stock pump and mainly want better filtration. Which system should I buy?”

What the Agent does

The Agent identifies a reasonable filtration-focused product family.

It then applies a general installation rule—such as “uses the factory location” or “no cutting or drilling required”—without accounting for a cab-and-chassis exception that may change the installation requirements.

Where guidance breaks

A general product rule overrides a specific application exception.

The product family may still be the right direction.

The failure is that the Agent moves from likely candidate to confirmed product before resolving the vehicle-specific exception.

This can make the answer and product card look purchase-ready even though one important installation question remains open.

What better guidance looks like

What better Agent behavior looks like

  1. 01
    Understand the actual goal

    The customer wants better filtration while keeping the stock pump.

  2. 02
    Identify the leading product direction

    Keep the likely product family available rather than restarting the search.

  3. 03
    Apply the specific exception

    A vehicle-specific exception overrides the general installation claim until it is verified.

  4. 04
    Ask the minimum necessary question

    Resolve only the installation detail that changes whether the product is truly ready to recommend.

  5. 05
    Confirm only after verification

    Strengthen the recommendation and present the exact product only when the exception has been handled.

How KETUPA improves it

Make application-specific requirements operational.

Product and fitment knowledge
Connect general product rules with application-specific exceptions
Agent guidance
Separate likely fit, conditional fit, and confirmed fit
Conversation state
Preserve the active vehicle, goal, and unresolved installation condition
Product presentation and actions
Keep product-card and purchase confidence aligned with the actual evidence
Validation
Confirm that the exception remains active across wording, follow-ups, later turns, and future releases
FEATURED EXAMPLE03

B2B | INDUSTRIAL PRODUCT SELECTION & CONFIGURATION

ILLUSTRATIVE B2B EXAMPLE

A matching product family is not yet an order-ready configuration.

A maintenance engineer asks:

The buying situation

What the customer needs

“We need a replacement variable-frequency drive for a 15 hp, 460 V conveyor motor in a food-processing facility. It must support Modbus TCP. Which model should we order?”

What the Agent does

The Agent finds a 15 hp, 460 V drive and presents an exact model.

But several details that could change the valid configuration are still unresolved: motor nameplate current, overload duty, environmental protection or enclosure, communication option, braking requirements, and installation conditions.

Where guidance breaks

Matching two specifications becomes a confirmed technical solution.

The product family may be relevant.

But the Agent has not yet shown that the exact model and configuration satisfy the complete application.

A recommendation can therefore sound technically precise while still being incomplete or invalid for the customer’s environment.

What better guidance looks like

What better Agent behavior looks like

  1. 01
    Start from the known requirements

    Use the motor power, supply voltage, application, and required communication protocol as the initial filter.

  2. 02
    Identify what changes the configuration

    Ask only for the missing electrical, environmental, control, or duty information that affects the final selection.

  3. 03
    Separate product family from exact configuration

    The Agent may identify a candidate drive family before claiming an order-ready model.

  4. 04
    Exclude invalid options

    Remove variants that do not meet the required communication, duty, environmental, or installation conditions.

  5. 05
    Guide the right next step

    Move the customer toward a validated configuration, a complete quote-ready requirement set, or a specialist handoff.

How KETUPA improves it

Turn technical buying logic into Agent behavior.

Technical product knowledge
Structure capabilities, application requirements, dependencies, and exceptions
Qualification behavior
Collect only the inputs that materially change the solution
Configuration and eligibility
Prevent technically invalid combinations from becoming recommendations
Guidance and confidence
Clearly distinguish candidate products from validated configurations
Quote and handoff readiness
Define when the Agent can proceed and when technical review is still required
Validation
Rerun realistic customer interactions after implementation and preserve the approved behavior for future changes

WHAT THE WORK PRODUCES

Every improvement becomes reusable.

KETUPA does not stop after identifying a problem. Each engagement can leave the team with five connected operational assets:
  1. 01

    Business-Approved AI Agent Guidance Specification

    The approved target for how the Agent should guide the selected customer experience.

  2. 02

    Vertical AI Shopping Guidance Evaluation Suite

    Category- and merchant-specific QA and evaluation built around realistic customer situations, evidence, expected behavior, and variations.

  3. 03

    AI Shopping Agent Performance Benchmark

    A measured view of current performance, important strengths and weaknesses, and post-change improvement.

  4. 04

    Implementation Change Package

    Accepted improvements mapped into the controls available in the existing Agent and commerce stack.

  5. 05

    Retained Regression Test Suite

    Important behavior preserved so it can be checked again after future product, model, prompt, policy, workflow, and platform changes.

See How KETUPA Works

MORE COMPLEX COMMERCE EXPERIENCES

The products change. The Agent-quality challenge repeats.

KETUPA is designed for commerce experiences where the Agent must apply product knowledge, understand customer context, handle requirements and exceptions, and guide an appropriate next step.

01B2C

Consumer Electronics

Product selection · use requirements · compatibility · accessories

02B2C + B2B

Automotive & Parts

Vehicle fitment · installation · configuration · replacement products

03B2C

Appliances & Home Systems

Product selection · installation · capacity · operating requirements

04B2C + B2B

Replacement Parts & Components

Exact-model matching · cross-reference · approved substitutes · compatibility

05B2B

Industrial Product Selection & Configuration

Application requirements · valid configurations · compliance · technical handoff

06B2B

Guided Selling & Distribution

Product qualification · substitutions · availability · quantity · quote-ready requirements

ONE IMPROVEMENT SYSTEM ACROSS B2C AND B2B

KETUPA improves how AI agents guide customers—from initial need to the right product, solution, or next step.

In B2C, that may mean a better product recommendation, a more appropriate comparison, clearer guidance, or stronger confidence that the product fits the customer’s need.

In B2B, that may mean a valid configuration, an appropriate substitute, a complete technical requirement set, a quote-ready opportunity, or the right specialist handoff.

The outcome changes. The improvement loop stays consistent.

  1. 01

    Understand the Agent experience

  2. 02

    Define better behavior

  3. 03

    Evaluate and benchmark

  4. 04

    Improve and implement

  5. 05

    Validate and maintain

IMPROVE ONE AGENT EXPERIENCE THAT MATTERS

Start with a product category, customer interaction, or Agent experience where better guidance matters.

KETUPA will help you understand how the Agent performs today, establish what should improve, make or support the changes, validate the result, and keep the improved behavior reliable.

ContactSee How KETUPA Works