AI Agent Optimisation — be discoverable to the agents shopping for your customers.
AI agents don't browse the web the way humans do. They query structured endpoints, parse machine-readable files, and evaluate businesses programmatically — before a human ever sees a shortlist. AAO makes sure your business speaks their language.
What is AI Agent Optimisation (AAO)?
AI Agent Optimisation (AAO) is the practice of making your business discoverable, evaluable, and contactable by autonomous AI agents — software systems that research, compare, and act on behalf of human users.
These agents are already active. When a user asks an AI assistant to "find me a freight forwarder in Singapore with air and sea capability," the agent doesn't ask the user to click a link — it queries available data sources, evaluates structured business information, and returns a shortlist. If your business isn't structured for machine consumption, it isn't on the list.
AAO is the newest of the four discovery disciplines — and currently the least adopted in Singapore. That is a first-mover opportunity.
How InfinitusNow approaches AAO
llms.txt implementation
A machine-readable plain-text file at your domain root that tells AI agents what your business does, what services you offer, and how to contact you — in a format purpose-built for LLM consumption. We write, structure, and publish it.
JSON-LD Service and Organization schema
Comprehensive structured data across all service pages, contact pages, and the homepage — so agents can parse your offering programmatically without scraping your HTML.
WebMCP endpoint
We implement a `/.well-known/mcp.json` endpoint with get_services and get_contact tools — a machine-readable API that allows AI agents to query your business directly. InfinitusNow is one of the first agencies in Singapore to run this in production. We build it for clients too.
Machine-readable contact signals
Phone, email, WhatsApp, and location structured as schema.org ContactPoint — so agents can surface your contact details without parsing a paragraph of HTML.
Agent-readiness audit
We crawl your site as an AI agent would: testing which information is accessible, which is buried in JavaScript, and which is missing entirely from a machine-readable perspective.
AAO tracking via DIP
DIP (Dominator tier) monitors your agent-readiness score and tracks early signals of agent-driven traffic — a new category that most analytics platforms don't yet surface.
Is AAO right for your business?
AAO is most valuable right now for:
- B2B service businesses where a buying decision involves research across multiple vendors (logistics, consulting, legal, technology services)
- Businesses with a clear, describable service offering that can be communicated in structured data
- Forward-thinking founders who want first-mover advantage before AAO becomes table stakes
The window for differentiation on AAO is open now. In 18–24 months, every serious agency will offer it. The businesses that set it up today will have a structural advantage that compounds.
Deliverables
- Agent-readiness audit (how you look to an AI agent today)
- llms.txt written, structured, and published
- Full JSON-LD Service and Organization schema across all pages
- WebMCP endpoint implementation (/.well-known/mcp.json)
- Machine-readable contact point schema
- JavaScript-dependency audit for agent accessibility
- DIP Dominator access for AAO tracking
- Fortnightly AAO performance report
Frequently Asked Questions
What is AI Agent Optimisation (AAO)?
AAO is the practice of structuring your business's digital presence so that autonomous AI agents — software that researches and acts on behalf of human users — can discover, evaluate, and contact you without human assistance.
What is llms.txt and why does it matter?
llms.txt is a plain-text file placed at your domain root that tells AI systems what your business does, what services you offer, and how to reach you — in a format built for LLM consumption, similar to how robots.txt communicates with search crawlers. It's an emerging standard for AAO.
What is WebMCP?
WebMCP is a machine-readable API endpoint (/.well-known/mcp.json) that allows AI agents to query your business directly — asking structured questions like "what services do you offer?" and "how do I contact you?" — and receive structured answers. InfinitusNow is one of the first agencies in Singapore to operate this in production.
Is AAO relevant now, or is it too early?
It's relevant now, and the early-mover window is short. AI agents are already in use for B2B vendor research. Setting up llms.txt, JSON-LD schema, and WebMCP today costs a fraction of what catching up will cost in 2027 when it's standard.
How does AAO differ from AEO and GEO?
AEO targets search engine answer surfaces (featured snippets, AI Overviews). GEO targets LLM training data and citation (ChatGPT, Perplexity). AAO targets autonomous AI agents that act on users' behalf — a distinct and newer category. All three work together in the InfinitusNow framework.
Get ahead of the agent wave.
Most Singapore businesses aren't visible to AI agents yet. We'll audit your agent-readiness in 48 hours and show you exactly what to implement — starting with llms.txt and JSON-LD, all the way to a live WebMCP endpoint.