As third-party cookies lose their grip on digital marketing and privacy regulations tighten, marketers haven't lost data; ...

Mobile messaging apps now sit at the center of how billions of people communicate. WhatsApp passed 3.3 billion monthly ...

AI agents have become remarkably good at demonstrations. The harder challenge begins after deployment, when workflows break because a model changes behavior, an API shifts, or an orchestration layer ...

As the global race for artificial intelligence intensifies, how can India use this emerging technology to maximise the ...

In the next wave of healthcare AI, differentiation will turn less on model sophistication and more on the quality and ...

Collaboration aims to tackle one of autonomous vehicle industry’s biggest challenges, namely proving how systems make ...

The business became more agile and IT became less of a friction point, but the operating model of the enterprise largely ...

By Neeraj Aggarwal. Payments is entering a decisive decade—one in which the institutions that thrive will not be the ones with the newest rail, the fastest API, or the most mode ...

Durable workflow engine Obelisk argues a SQLite file plus Litestream backup can replace Amazon SQS and RabbitMQ for AI agent workflows and tenant-isolated pipelines. The open-source, pre-release ...

AI makes costly mistakes, but combining it with humans and software can help avoid them.

Enterprises cannot secure AI agents by making the underlying models more robust and must instead enforce security controls at the system level around them, researchers behind a paper published this ...

The success of agentic AI in financial services depends not just on smarter models, but on an authoritative context data store—one that is accessible, reliable, and governed at scale.