Since its establishment, Profound has positioned itself in the niche field of "AI search visibility," helping brands monitor and optimize their exposure and citation in generative AI Q&A products like ChatGPT and Perplexity. This positioning has made it one of the early representative companies of the emerging discipline of "AEO" (Answer Engine Optimization), distinguishing it from traditional SEO tool vendors.

From a funding perspective, this round of financing led by Sequoia Capital and Kleiner Perkins signals that traditional venture capital is reallocating funds originally directed towards enterprise SaaS and search engine optimization tools to the new track of "AI-native marketing tools"; the company also announced the expansion of its applied AI research team and recruitment of IOI medalists, indicating a shift in funding focus from mere product growth to foundational model post-training and benchmark testing capabilities, aiming to establish technical barriers rather than solely relying on first-mover product advantages.

This approach of "post-training models for vertical industries and building industry-specific benchmark tests" is highly similar to the paths of previous vertical AI application companies like Harvey (for the legal industry) and Hebbia (for the financial industry)—these companies have chosen not to compete directly with general large model vendors on basic model capabilities, but rather to build scenario barriers that are difficult for general models to replicate through deep understanding of specific industry workflows and post-training. Profound is currently attempting to introduce this vertical AI approach into the relatively underexplored marketing field, positioning itself in the early leading stage of this niche track.

This essentially represents a combination of "technological substitution" and "transfer of pricing power": on one hand, AI-native marketing tools are replacing traditional SEO/SEM tools and manual marketing analysis processes, driven by the migration of content distribution channels from "traditional search engines" to "AI Q&A interfaces"; on the other hand, by building industry-specific benchmark tests and post-training capabilities, Profound aims to control the definition of the evaluation standard for "how to judge the performance of an AI in marketing tasks". Once its benchmark tests are widely adopted in the industry, it will directly influence the perception standards of other competitors and clients in the vertical track regarding "what constitutes a good AI marketing tool," thereby gaining implicit pricing power akin to that of an "industry standard setter."

ABAB News · Cognitive Laws

When the channel changes, businesses that follow the channel must start over.
Whoever defines the evaluation standards defines good and bad.
While others are competing on models, you can compete on scenarios.