Agentic Commerce
On demand
Buyer-Agent Product Configuration Agent
Check the fit before the quote.
Help a buyer's AI assistant choose a product setup with compatible parts that meet their requirements.
Configure ten design workstations requiring 32GB RAM, two display outputs and a case no wider than 180mm.
- Extracted three hard constraints and fleet quantity.
What it does
Choose compatible components for the buyer's requirements.
Help a buyer's AI assistant choose a product setup with compatible parts that meet their requirements. Built for merchants selling configurable equipment through buyer-agent enquiries.
Capture the product needs
Provide the buyer's requirements, available products and compatibility rules. Compatibility test results and end-of-life notices can improve configuration choices.
Check compatible components
Select suitable components and check that they work together and meet the essential requirements.
Present complete options
Get a proposed configuration with item quantities and any unresolved choices.
How it works
Help a buyer's AI assistant choose a product setup with compatible parts that meet their requirements. Built for merchants selling configurable equipment through buyer-agent enquiries.
- Approved documents and context
- Versioned product specification catalogue Owned component compatibility and obsolescence matrix Optional: manufacturer compatibility tables and validated configuration test results, to check combinations beyond individual product specifications. Optional: firmware requirements, known incompatibilities and end-of-life notices, to avoid a configuration that will be difficult to use or maintain.
- Spend less time assembling the right products
- Review proposed products, components and quantities with the reasons behind each choice.
- Catch unresolved compatibility questions
- See which requirements are confirmed and which need a technical answer before the configuration is accepted.
- Shopify · Read product variant specifications (read)
- Use configured structured metafields for compatibility IDs; do not infer from marketing titles.
- Google Sheets · Read approved compatibility matrix (read)
- Retrieve machine-readable component constraints and owner version.
- Google Drive · Read product technical sheets (read)
- Attach source-backed dimensional and electrical evidence.
- Human review and permissions
- Product engineering approves undocumented component combinations before offering them. If something fails, pause the affected request and check what actually happened. Correct the source information, repeat the checks and renew approval if the proposed action changed. Keep a record of the issue.
01Gather the context
Bring together the relevant information from Shopify, Google Sheets, Google Drive.
02Check what matters
Select suitable components and check that they work together and meet the essential requirements.
03Prepare the result
Get a proposed configuration with item quantities and any unresolved choices. What has been checked, what still needs a decision and whether any requested action actually completed. Keep private internal notes out of the buyer's response.
04Review proposed changes
Product engineering approves undocumented component combinations before offering them. If something fails, pause the affected request and check what actually happened. Correct the source information, repeat the checks and renew approval if the proposed action changed. Keep a record of the issue.
Integrations
Commerce
Shopify
WooCommerce
Structured records
Google Sheets
Airtable
Notion databases
Documents
Google Drive
Microsoft OneDrive
Choose the platforms your team already uses—you don’t need every example shown. Confirm the required features and configure access during implementation.
What you get
Turn a buyer's requirements into a reviewable product configuration with compatibility gaps visible before purchase.
- Spend less time assembling the right products
- Review proposed products, components and quantities with the reasons behind each choice.
- Catch unresolved compatibility questions
- See which requirements are confirmed and which need a technical answer before the configuration is accepted.
More for agentic commerce teams
Agent-Readable Offer Publisher
Turn your product and service information into clear offer details that buyers' AI assistants can read.
Source-Backed Buyer Enquiry
Answer a buyer's AI assistant using your product details and policies, with links to the relevant information.
Buyer-Agent Selection Test Lab
Test whether an AI assistant can understand your offer and match it to a buyer's needs.
Start with a blueprint. Build it around your business.
We’ll adapt it to your workflows, connect your systems and build an agent your team can put to work.
30 minutes. One bottleneck. Leave with a clear system concept.