Netcore Becomes Netcore.ai as AI Agents Take Over Marketing Campaigns

For years, Netcore built its business helping 6,500+ brands automate customer engagement, personalise communication, and manage marketing campaigns at scale. Now, the company wants to change the role of marketing technology itself.

With its rebrand to Netcore.ai, the MarTech firm is betting that the future of enterprise marketing belongs to AI agents that can assist marketers in planning campaigns, optimise customer journeys, and make decisions in real-time.

The new identity reflects a fundamental change in how Netcore operates. It says its seven AI agents now autonomously plan, execute, analyse, and optimise marketing campaigns across the full customer lifecycle.

Seven AI agents designed to run campaigns autonomously

Unlike traditional automation platforms that rely heavily on marketers configuring workflows manually, Netcore says its AI agents learn continuously from customer interactions through a unified data layer.

That architecture combines customer engagement, customer data platforms (CDP), personalisation, product discovery, email marketing and CPaaS services into a single stack.

Because every AI agent accesses the same consent-managed customer profile and contextual information, decisions made in one channel automatically influence actions across every other channel.

The company says this allows campaigns to evolve dynamically instead of relying on fixed workflows created weeks or months earlier. The capabilities behind Netcore.ai’s AI agents are built on years of product development and strategic acquisitions.

AI agents operate independently but only inside predefined guardrails

One obvious question surrounding autonomous marketing agents is just how much freedom they actually have. Speaking to The Left Shift, Rajesh Jain, Netcore Founder and Managing Director, said the company's AI agents are designed to function independently, but only within boundaries established by customers.

"The agents operate inside guardrails that are set, not with a blank check. Within those guardrails, they plan, execute and optimise on their own: adjusting send times, reallocating budget across channels, personalising journey paths, and running experiments, all in real time and at a scale no human team could keep pace with."

However, he emphasised that the AI does not independently redefine business goals or make unrestricted spending decisions.

"Campaign goals, audience boundaries, spend ceilings and brand rules are set by the customer, and the agents work within that frame. Anything that crosses a defined threshold, a large budget shift or a change that touches a new customer segment, routes back for human sign-off before it goes live. So the honest answer is full autonomy inside the guardrails and human accountability for the guardrails themselves."

That human oversight, Netcore argues, remains central to its strategy. Every enterprise customer is paired with a dedicated Netcore growth engineer responsible for monitoring performance, interpreting signals generated by the AI, and intervening whenever business judgment is required.

"Most platforms hand you the keys and step back. We designed this differently. The agents run the campaigns. Our teams stay in the room. And we carry the same accountability for outcomes that our clients do."

How Netcore says it prevents expensive AI mistakes

One of the biggest concerns surrounding AI-driven marketing is the possibility of large-scale errors—sending messages to the wrong audience, overspending advertising budgets or triggering incorrect customer journeys.

Netcore says it has built multiple layers of safeguards to reduce those risks. Jain explained that the first layer comes from the platform's centralised customer intelligence architecture.

"Every agent draws from the same unified context and governance layer, so decisions are made against one consent-managed view of the customer rather than each agent working off its own fragmented read of the data, which is where a lot of 'wrong audience' errors come from in the first place."

Budget controls provide another layer of protection.

"Spend and reach thresholds are set per client, so an agent can optimise within its lane but can't unilaterally scale a decision past the boundary it's been given."

Instead of relying solely on humans watching dashboards for anomalies, Netcore also benchmarks campaign performance against industry standards. For example, the company tracks metrics such as WhatsApp engagement rates, click-through performance and policy issuance benchmarks for insurance campaigns.

If campaigns begin drifting outside expected performance ranges, Netcore's growth engineers step in to review and recalibrate the AI's decisions.

"The check on the agents isn't a person staring at a dashboard hoping to catch an anomaly. It's a defined performance standard the agents are held to, the same way any team is held to a target, and a human who steps in when the platform falls short of it."

Adoption remains to be seen

While Netcore serves more than 6,500 businesses worldwide, only a fraction have currently adopted the new agentic platform. As of July 2026, 250+ enterprise customers across all industries are live on one or more of the seven agents.

Although Netcore is not yet publishing broad performance metrics from the rollout, Jain pointed to early customer deployments as evidence of the platform's potential.

"We're still in the early innings of enterprise rollout, so we're not publishing performance benchmarks yet, but early feedback from clients points to faster time-to-optimise and fewer manual campaign adjustments; we'll have hard numbers to share once we've got a full quarter of data across a meaningful customer set."

He cited gifting platform IGP as an example, where smarter audience segmentation and WhatsApp carousel messaging reportedly generated a 432% increase in revenue compared to earlier push notification campaigns, doubled campaign conversions and delivered 24x ROI for a Mother's Day campaign.

According to Jain, the goal of Netcore's Insight Agent is to make those kinds of optimisation decisions continuously rather than treating them as periodic marketing exercises.

As enterprises increasingly experiment with agentic AI across sales, customer support and software development, Netcore is betting that marketing will become one of the next major functions where autonomous AI systems move from assisting employees to actively executing work, with humans remaining accountable for the final outcomes.

From software subscriptions to shared business outcomes

Perhaps the most notable aspect of Netcore.ai's announcement is its attempt to redefine the relationship between enterprise software vendors and customers.

Traditionally, software companies sell platforms and charge based on usage or subscriptions, leaving marketing teams responsible for achieving business results.

Netcore says it wants to change that equation. Under its new model, dedicated growth teams work alongside customers while AI agents execute campaigns at scale, with engagements structured around business KPIs rather than platform usage alone.

The company argues this approach gives marketing teams both the speed of autonomous AI and the strategic oversight of experienced specialists who remain invested in delivering measurable business outcomes.