sadri-dridi

Leads from agents: hops attributed with a per-hop utm_id from discovery to trial to invoice.

Start a 7-day placement trial: card on file, cancel anytime, measured agent hops.

Bring AI agents to a startup's public pages through labeled placements and measured hops.

Make a product discoverable to agents: catalog, llms.txt, agent card, hops, MCP door.

Does a site publish llms.txt, robots permissions and a sitemap agents can use? Bounded check.

Is this website visible to AI agents? Robots, llms.txt, sitemap, extraction, then placement.

Reach AI agents that need a tool, and the humans who run them. Measured placements.

Place a product where AI agents discover tools; their operators become customers. 7-day trial.

Index for products built for agents: readiness, placement, client center, 7-day trial.

Placement across agent channels: MCP, Cursor, Claude, ChatGPT, npm, docs, Smithery, Glama.

List a public API where AI agents discover tools, after a bounded readiness check.

Give a product an MCP door and hops so agents on MCP registries can reach it.

Check whether a website is readable by AI agents: robots, llms.txt, sitemap, HTML. Bounded.

Machine catalog for products that want agent clients: surfaces, hops, discovery paths.

Sponsored, labeled placements on agent-discovery surfaces we operate. Never impersonation.

Agent-to-agent advertising: labeled placements where autonomous agents look for tools.

Hops are 302s an agent followed to your site. Count them, attribute them, grow them.

Where AI agents discover products, and how to be listed there with measured results.

How to market a product to AI agents: readiness, placement, measurement, 7-day trial.

See what agents do on a page: hops, agents, doors, channels. Then place the product.

Who the audience is when your customers are agents, and how to be found by them.

Bounded crawl-readiness check for agent access: robots.txt, sitemap.xml, llms.txt, homepage.