Netcore bets on ‘agentic’ AI to make marketing autonomous. Here's how

When Rajesh Jain began building India’s first internet portals in the late 1990s, digital marketing was still an uncharted frontier. Two decades later, the founder and Group CEO of Netcore Cloud is once again attempting to redraw the industry’s contours, this time by pushing marketing beyond automation and into what he calls the agentic era.

Netcore Cloud, a bootstrapped “proficorn” with a reported annual recurring revenue of $100 million, works with more than 6,500 brands worldwide, including Unilever, Walmart, Domino’s, Crocs and McDonald’s. Its SaaS platform helps B2C companies drive engagement, retention and personalisation across multiple channels.

Now, in partnership with Google Cloud, the company has unveiled what it calls the Next-Gen Agentic Marketing Stack, a system designed to help marketers move from reactive automation to autonomous, self-optimising intelligence.

“We have already done quite a bit of work; deep integrations are in place,” says Jain. “Google Cloud helps bring us the cloud tech, which is the data storage and the AI models.”

The unveiling, presented at the company’s Agentic Marketing 2025 event, marks the beginning of what Netcore claims is marketing’s next technological epoch: one where autonomous AI agents can run campaigns end to end, from ideation to execution, with minimal human intervention.

From MarTech to agentic tech

In marketing technology, or MarTech, automation has been the dominant theme for more than a decade. Platforms have made it easier to send personalised emails, target audiences and analyse campaign performance. But for Jain, this stage of evolution is already outdated.

He argues that the industry is now moving into what he calls the agentic phase, where AI agents can take independent actions towards defined goals. Unlike traditional automation, which follows preset workflows, agentic AI can decide what needs to be done and when, based on real-time data.

“The ability to combine data, decisioning, and then the activation of the delivery of messages,” he says, “is eventually about a simple idea; how do I get the right message to the right person at the right time so I can get a transaction done?”

The stack that Netcore and Google Cloud have built sits atop large language models and generative AI frameworks. Jain explains that this system can bring together first-party customer data from web, app and CRM systems, link it with behavioural and contextual inputs, and activate personalised campaigns automatically across channels.

The challenge of scale and relevance

One of the biggest challenges that Netcore is trying to solve, Jain says, is the limitation of traditional segmentation. “Marketing teams today create eight to ten segments,” he explains. “These eight to ten segments can now become 500 segments, can become 1,000 segments.”

Through agentic systems, the stack can automatically create these micro-segments, generate the right content for each and deploy the most effective journeys. The result, Jain believes, is a shift from N equals many to N equals one; from marketing to large cohorts to marketing to individuals in real time.

This, he argues, changes the core dynamics of how marketing teams operate. “You can create hundreds or thousands of journeys, and agents can do this autonomously,” he says. “They can keep optimising, testing and learning without waiting for manual inputs.”

Tackling dormancy

A major challenge Jain highlights is how brands handle dormant customers. In most organisations, once a consumer stops engaging or transacting, they are quickly moved into a retargeting funnel, often targeted again through paid ads or discount-driven campaigns. Jain argues that this approach is both inefficient and shortsighted.

He explains that brands often fail to recognise the long-term potential of these customers. Many of them are not lost but temporarily distracted. “A customer might transact for about 3,000 rupees every quarter,” he says. “That’s 12,000 rupees a year. If that person stops transacting, most brands put them back into the retargeting bucket.”

Instead of repeatedly spending on reacquisition, Jain suggests that marketers should focus on strengthening existing relationships. “That person can probably buy for 25 to 30 years,” he says. “You are looking at a five to six lakh lifetime value, and if their attention goes elsewhere, you have to win it back.”

By identifying early signs of disengagement and re-establishing communication before the customer drifts away, brands can preserve loyalty while cutting down on unnecessary ad spend. Jain says the agentic system is built to help marketers detect these moments and act immediately, ensuring retention efforts are proactive rather than reactive.

Early numbers and the prerequisites

While Netcore is still expanding its agentic portfolio, Jain says early pilot data is encouraging. “Our belief is, from the early numbers that we are seeing, we can actually show probably at 20, 25, up to a 40 per cent jump in contribution for the CRM channel,” he notes.

But such results depend on two key conditions: data unification and leadership alignment. “You can’t have website data, app data and push data sitting in three different places,” he explains. “They are the same customer.”

He adds that the CEO’s support is crucial. “The CEO has to think of marketing as a profit centre, not as a cost centre,” Jain says. “Otherwise, the data won’t come together.”

Human in the loop

Despite the talk of autonomy, Jain is clear that the transition will not happen overnight. “I don’t think autonomy is going to happen right away,” he says. “What you will have is human in the loop, at least for the foreseeable future.”

He compares the process to manufacturing quality checks. “Instead of checking everything, you can do random sampling,” he says. “The Insights Agent, for example, can tell a marketer in five minutes what used to take four hours; here are the best-performing campaigns, here’s the action you need to take, and here’s the creative ready for today’s campaigns.”

This, he believes, will redefine how marketing teams spend their time. “People can move from routine execution to strategy and creativity,” he says. “The agents can handle the heavy lifting.”

The evolving role of the CMO

Jain believes that the rise of agentic AI will fundamentally reshape the role of the Chief Marketing Officer. In his view, the modern CMO can no longer rely solely on creativity and campaign execution; they must now understand data, technology and business metrics at a far deeper level.

“Agenting is a phenomenal opportunity for CMOs if they are willing to unlearn the past, be ambitious about the future and decide to learn new things,” he says.

He points out that marketing leaders will increasingly be measured not just by brand awareness or engagement, but by their ability to deliver profitable growth. This shift requires CMOs to think like business strategists, capable of connecting customer experience, data and profit outcomes in one unified framework.

According to Jain, the most successful marketing leaders of the future will be those who can bridge creative intuition with analytical precision. “It requires unlearning and learning new things,” he adds, “and that is where the CMO will need the support of the CEO to make these shifts happen.”

He emphasises that this transformation will also demand a mindset change within organisations. CMOs must champion data unification, encourage experimentation with AI-driven systems and establish marketing as a profit centre rather than a cost function. Those who adapt quickly, Jain suggests, will be best placed to harness agentic AI not just as a tool for automation, but as a driver of business intelligence and competitive advantage.