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DeepIntent is launching Cora, an agentic AI platform for pharma marketing. Instead of using individual AI functions only for text or recommendations, Cora is meant to connect several specialized agents in a shared workflow – from market and audience analysis through to the activation of omnichannel campaigns.
This matters mainly because it moves adtech further from classic dashboard automation towards agentic campaign management. According to DeepIntent, Cora is initially available as an open beta for existing customers.
Multiple agents instead of a single chatbot
According to DeepIntent, marketing teams can control Cora in natural language. The platform is said to distribute tasks such as market intelligence, audience planning, media planning, activation and optimization across several specialized agents.
The important difference from an ordinary AI assistant lies in the move from analysis to execution: the system is not only supposed to deliver answers, but also trigger and connect work steps within the existing advertising stack.
This development fits a trend we already see in AI agents in CTV media buying, where agents already take over planning, buying and optimization. At the same time, the share of largely automated ad spend is growing overall, as our analysis of AI-driven ad spend shows.
Cora builds on DeepIntent's healthcare data stack
Cora is not being built from scratch. In March 2026, DeepIntent had already introduced a healthcare marketing cloud with Helix and then expanded Helix AI. There, customers can query healthcare data in natural language, create audiences and activate them directly in DeepIntent's Cortex DSP.
DeepIntent cites its data base as more than 3,7 million healthcare professionals and more than 240 million patient lives. These figures come from the provider itself and describe the US market; they are not an independent reach benchmark.
Cora now extends this principle into a more strongly agentic workflow. The provider describes, among other things, shared workspaces for brands, agencies and AI agents, as well as the linking of planning and activation across multiple channels.
Why pharma is an interesting test market
Pharma marketing is a particularly demanding use case for agentic advertising. Campaigns work with specialized audiences, health and media data, and strict data protection and compliance requirements. DeepIntent therefore explicitly positions its infrastructure as HIPAA-compliant and designed for regulated healthcare data.
This makes the launch interesting for marketers outside the pharma sector: if agentic systems are used in a heavily regulated environment, from research through audience building to campaign activation, it shows how quickly the role of classic DSP interfaces could change.
For German and European companies, however, DeepIntent's specific stack is not directly transferable. HIPAA is US law; in Germany and the EU, different data protection and advertising rules apply. What matters, therefore, is less the concrete targeting model than the technical direction: data, planning and activation are moving into a shared AI workflow.
Agentic advertising shifts the media buyer's job
The more campaign steps an agent carries out itself, the more the work shifts from manual operation to goal definition, data quality, approvals and oversight. This applies especially to systems that not only make suggestions but can actually activate budgets and audiences.
This also increases the demands on governance. Teams need to be able to trace which data an agent uses, which actions it may perform and where human approval remains necessary. For marketers, not only the quality of the model becomes relevant, but the quality of the guardrails around the model.
Cora is not yet evidence that fully autonomous media teams are imminent. The launch is, however, another signal that advertising platforms are evolving from individual AI features into systems meant to take over entire workflows.