Agentic Commerce
On demand
Agent-Readable Offer Publisher Agent
Make offers buyer-agent ready.
Turn your product and service information into clear offer details that buyers' AI assistants can read.
Prepare the Atlas Team offer for buyer-agent discovery.
- Read approved price, scope and capacity records.
What it does
Make prices, inclusions and terms easier for AI assistants to read.
Turn your product and service information into clear offer details that buyers' AI assistants can read. Built for merchants exposing an owned offer catalogue to buyer agents.
Gather approved offer facts
Choose the offer and provide its current prices, inclusions and terms. Buyer questions and product change history can reveal missing or outdated offer details.
Prepare a clear offer
Organise the details into a consistent format and flag anything missing or contradictory.
Verify the published version
Get an offer draft ready for approval, with clear dates and exclusions.
How it works
Turn your product and service information into clear offer details that buyers' AI assistants can read. Built for merchants exposing an owned offer catalogue to buyer agents.
- Approved documents and context
- Owned offer schema and approved product facts Versioned pricing and delivery capacity records Optional: recurring buyer questions and failed offer-validation examples, to identify details an assistant needs but cannot currently find. Optional: approved product change logs and canonical specification records, to update offer fields consistently.
- Help buyer agents understand the offer
- Present consistent product, price, inclusion and term details in an offer draft prepared for approval.
- Resolve ambiguity before buyers encounter it
- Highlight missing or conflicting information, dates and exclusions so your team can clarify the offer before publishing.
- Contentful · Read and stage approved offer entries (draft)
- Read merchant facts and prepare an unpublished entry revision.
- Shopify · Read product variants and prices (read)
- Resolve current merchant catalogue fields through a configured Admin API adapter.
- Notion · Read delivery terms and source ownership (read)
- Retrieve approved service commitments and their effective dates.
- Human review and permissions
- Catalogue owner approves price and scope changes; delivery owner confirms dated capacity claims. 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 Contentful, Shopify, Notion.
02Check what matters
Organise the details into a consistent format and flag anything missing or contradictory.
03Prepare the result
Get an offer draft ready for approval, with clear dates and exclusions. 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
Catalogue owner approves price and scope changes; delivery owner confirms dated capacity claims. 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
Content management
Contentful
WordPress
Commerce
Shopify
WooCommerce
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
Make your offer easier for a buyer's AI assistant to understand, with the details checked before publication.
- Help buyer agents understand the offer
- Present consistent product, price, inclusion and term details in an offer draft prepared for approval.
- Resolve ambiguity before buyers encounter it
- Highlight missing or conflicting information, dates and exclusions so your team can clarify the offer before publishing.
More for agentic commerce teams
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.
Policy-Constrained Quote
Prepare an itemised quote for a buyer's AI assistant using your prices and agreed discount rules.
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.