Palmata measures how agents describe you. Not whether they can buy from you.

Contentful launched Palmata on June 23. Read past the product announcement, and it is the clearest signal yet that the measurement layer for agentic commerce is now a category, not a feature.

Palmata's core argument is one the practice has been making for months: visibility is only the starting point. Most AI discovery tools tell a brand whether it shows up in ChatGPT, Gemini, or Perplexity, how often it is cited, and how its share of voice compares. Those are the right questions to ask second. They are not the questions that change anything.

The questions that change something are the ones Palmata is built to answer. How is the brand being represented? Why are answer engines describing it this way? What content should change first? That is the difference between knowing you have a problem and knowing what to do about it.

Two things about this launch matter beyond the product itself.

The first is what it says about where the money is moving. Contentful acquired the team behind this (Writ) and built it into a standalone platform, launched independently from the core CMS. Salesforce paid a billion dollars for Contentful, in part, for the content architecture underlying exactly this kind of capability. The measurement and representation layer of AI discovery is now attracting acquisition capital and dedicated product investment. When that happens, the category has crossed from emerging to established.

The second is the framing Palmata uses, because it maps precisely to the layered model brands should already be working from. Palmata measures and improves how a brand is represented at the discovery layer, the moment before a buyer reaches an owned channel. This is the recommendation layer. It determines whether an agent surfaces and describes a brand accurately when a consumer asks for a recommendation.

Which is exactly why the measurement story does not end here.

Palmata answers how a brand is represented when an agent talks about it. It does not answer whether an agent can transact with that brand once it decides to recommend it. Those are two different readiness questions with two different measurement problems. Discovery representation is a content and evidence problem, and Palmata is built for it. Transaction execution is an infrastructure problem, and it needs a different instrument entirely.

The brands that will navigate the next two years well are the ones that measure both. Representation at the discovery layer, so they know how agents describe them. Transactability at the infrastructure layer, so they know whether agents can actually complete a purchase once the recommendation is made.

Palmata is a real step forward. It makes the discovery-representation problem measurable, which is the prerequisite to fixing it. The launch is worth attention not just for what it does but for what it confirms: measuring your brand's AI reputation is no longer optional infrastructure. It is becoming table stakes, and the tooling is arriving to make it possible.

The next instrument the market needs measures the layer below representation. When an agent decides to buy on a consumer's behalf, can it actually transact with you? That report does not exist yet. It will.