The agentic web is coming. A future where every business has an AI agent that can represent it, answer questions, negotiate and complete transactions. Your personal assistant does not browse websites. It talks directly to the agents representing hotels, restaurants, retailers and service providers.
In that world aggregators stop making sense. Discovery happens dynamically, on demand, without permanent middlemen taking a cut.
The technology exists. The economics work. The standards are forming.
But there is a problem most people skip over. How does your personal assistant find the right agents?
The discovery problem
Imagine you tell your assistant: “I need a quiet hotel in Barcelona with a rooftop pool, under 200 euros per night, for next weekend.”
In the agentic web vision your assistant contacts many hotel agents at once, gets real answers, compares offers and books directly. No aggregator. No 25 percent commission.
The obvious question is this: how does your assistant know which hotel agents exist in the first place?
Today, assistants do not talk to hotel agents. They search the web or query aggregator partners. The assistant becomes a conversational front end on top of the same infrastructure that has dominated for decades. That is not the agentic web. It is the old web with a chat interface.
What is missing is a discovery layer that can take a natural language request and return a list of verified agents that can actually fulfil it. Not websites. Not listings. Agents.
What discovery really requires
Agent discovery is not simple. Several things have to work together.
First, semantic understanding. The system needs to understand that “somewhere to stay” means hotels, apartments and guesthouses, that “rooftop pool” is a specific amenity, and that “quiet” is a preference some agents can meaningfully address.
Second, verified identity. Anyone can spin up an agent and claim to represent a hotel. A discovery layer has to verify that an agent belongs to the organisation it claims to represent, which means identity checks at registration and validation that continues afterwards. That is not a directory. It is a trust layer.
Third, capability matching. Some agents can negotiate. Some can book. Some only answer questions. Discovery has to match user intent to what agents can actually do.
Fourth, communication details. Once an agent is discovered, the assistant needs to know how to talk to it: which protocol, how authentication works, what formats are supported.
Without this infrastructure, assistants will default to aggregators because it is easier and safer. The old model wins by inertia.
The trust problem no one can ignore
In the agentic web, every agent is a black box.
On today’s web you rely on visual cues. URLs. Branding. Design. These are imperfect, but they help you judge legitimacy.
In an agentic world your assistant sends a message and gets a response. An agent claims to represent a well known hotel. How does your assistant know that is true?
Fraud on the traditional web is already widespread. In the UK alone, people reported losing £11.2 million to holiday booking fraud in 2024. Remove the visual signals entirely and the problem gets worse, not better.
Without a trust layer the agentic web becomes a fraud playground. With one, it becomes viable. That is why KPATH exists.
Discovery and trust for AI agents
KPATH is building a search and trust layer designed specifically for AI agents. When a personal assistant needs to fulfil a request, it queries KPATH, and KPATH returns a list of verified agents that can help along with the information needed to communicate with them safely.
There are two core pieces, and both ship today inside the platform rather than as products of their own.
Discovery is a semantic search for AI agents. Every agent listed is verified. Organisations go through identity checks before registering agents. Each agent carries structured metadata covering capabilities, domains and supported actions. Results return verified agent endpoints, not web pages.
Enforcement handles what happens once an assistant has found an agent. It governs permissions and the calls between the two, so an agent reaches only what policy allows and every exchange is recorded. That is the governed service directory and the enforcement layer around it.
Trust infrastructure sits under both. Agent verification, reputation signals and transaction history give assistants confidence that the agents they interact with are real and accountable.
How this works in practice
You ask your assistant for a quiet hotel in Barcelona.
Your assistant queries KPATH with that request. KPATH reads the intent, location, constraints and preferences, and returns a list of verified hotel agents that match. Each comes with details about what the agent can do and how trustworthy it is.
Your assistant contacts several hotel agents directly. They respond with real availability, pricing and specific answers. This is first party data from the hotels themselves.
You choose one. The booking happens directly. No aggregator takes a cut.
That is what the agentic web looks like when the right infrastructure exists.
A reference personal assistant
KPATH has built its own personal assistant to demonstrate the flow end to end. It is not the product. It is proof.
It connects to agents across multiple sectors and shows that discovery, communication and transaction can work together. Any assistant can use the same infrastructure: consumer assistants, enterprise assistants, custom internal tools. KPATH builds the roads, not the vehicles.
Why timing matters
Personal assistants are scaling fast. Around 800 million people use ChatGPT every week, and hundreds of millions of users now interact with assistants daily.
Right now most assistants are partnering with aggregators. Every booking routed that way reinforces the old model and increases switching costs. If no alternative discovery layer exists, the agentic web will recreate the aggregator economy with a conversational face.
KPATH is the alternative: infrastructure that enables direct agent to agent interaction, restores direct relationships and removes the permanent middleman tax. The window to build it is now, while standards are still forming and habits are not yet fixed.
The infrastructure the agentic web needs
The traditional web needed DNS, HTTP and search engines to work. The agentic web needs agent registries, discovery layers, trust verification, secure routing and payment rails.
KPATH is building the discovery layer that makes the rest possible. Without it, your assistant cannot find the agents it needs. With it, the agentic web becomes real.