Mumbai: Mobavenue AI Tech Limited has announced the release of an AI-led neural network modelling framework through its wholly owned subsidiary Mobavenue Media Private Limited, marking a significant step in its transition towards AI-native advertising platforms.
The newly developed framework leverages deep neural network architectures to identify and match high-intent users with relevant brand offerings. By analysing behavioural, contextual, and real-time engagement signals, the system predicts users with a high likelihood of conversion while dynamically optimising bidding strategies and budget allocation to maximise performance outcomes.
Designed as part of a continuous data science lifecycle, the framework ingests and learns from evolving campaign and user interaction data, enabling near real-time recalibration and performance optimisation. This adaptive learning approach enhances targeting precision, reduces inefficiencies, and improves scalability across campaigns.
According to the company, the AI-led architecture has already demonstrated improved conversion outcomes compared to traditional optimisation models, depending on campaign objectives and market dynamics. The development underscores MMPL’s focus on building scalable, performance-driven solutions that integrate audience intelligence with efficient capital deployment.
Commenting on the launch, Tejas Rathod, Co-founder & Whole Time Director at Mobavenue AI Tech Limited, said, “This release reflects how we are thinking about the next phase of advertising technology, where intelligence is built into every layer of decision-making. The architecture allows us to solve both sides of the problem simultaneously: identifying the right users and allocating capital efficiently. As we continue transitioning our platforms to be AI-native, our focus remains on building systems that learn continuously and deliver more precise, outcome-led results for our customers.”
