Agentic Commerce
On demand
Constraint-Aware Bundle Offer Agent
Build bundles that fit the brief.
Suggest a complete product bundle for a buyer's AI assistant that fits its needs and budget.
Build a four-person podcast kit under £1,000 before tax.
- Mapped four participants to required signal-chain components.
What it does
Choose the essentials before adding optional extras.
Suggest a complete product bundle for a buyer's AI assistant that fits its needs and budget. Built for merchants selling multi-product solutions to buyer agents.
Understand the complete need
Provide the buyer's goal, budget, required items and available products. Validated combinations and ownership costs can make the bundle more complete.
Build compatible bundles
Choose compatible essentials first, then show any useful extras separately.
Explain the remaining gaps
Get a priced bundle with the reasons for each item and any requirements still unresolved.
How it works
Suggest a complete product bundle for a buyer's AI assistant that fits its needs and budget. Built for merchants selling multi-product solutions to buyer agents.
- Approved documents and context
- Approved catalogue prices and component compatibility Solution coverage rules for buyer objectives Optional: validated solution configurations and compatibility test records, to find combinations that cover the buyer's task. Optional: approved running-cost and maintenance requirements, to expose essential costs beyond the initial purchase.
- Reduce effort assembling a complete bundle
- Review compatible essential items with quantities, prices and reasons for inclusion in one recommendation.
- Keep extras and gaps clear
- Separate optional additions from requirements the available products do not yet satisfy, helping the buyer assess the proposed fit.
- Shopify · Read candidate items and prices (read)
- Resolve merchant SKU prices and structured specifications.
- Google Sheets · Read solution compatibility rules (read)
- Load required functional coverage and interface rules.
- Notion · Read approved bundle exclusions (read)
- Disclose items and services not included in the solution.
- Human review and permissions
- Product specialist approves undocumented interoperability and requirement compromises. 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, Notion.
02Check what matters
Choose compatible essentials first, then show any useful extras separately.
03Prepare the result
Get a priced bundle with the reasons for each item and any requirements still unresolved. 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 specialist approves undocumented interoperability and requirement compromises. 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
Knowledge
Notion
Confluence
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
Help buyers assess a compatible set of products against their needs, with a clear total and unresolved requirements visible.
- Reduce effort assembling a complete bundle
- Review compatible essential items with quantities, prices and reasons for inclusion in one recommendation.
- Keep extras and gaps clear
- Separate optional additions from requirements the available products do not yet satisfy, helping the buyer assess the proposed fit.
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.