AI bending and the rise of contextual intelligence

Here is the thing. Most Enterprise AI venom heights talk about scale and speed. Less talk about trust, tone and culture. In this conversation with the Amit Manjhi and Shruti Prakash from IPlay AI, I investigate another path for Enterprise AI, one that combines emotional intelligence with analytical horsepower, so that teams can ask more informed questions about their data and receive answers based in context.

The story of Amit determines the pace. He is a triple founder, a YC-Aluin and a CS-Promovendi that has solved complex problems in mobile, advertising technology and data. Shruti complements that bow with a product lens formed by real operational trenches, from clean rooms to supermarket store analyzes.

Together they built Boostkpi during the pandemic, transformed the natural language into usable insights and then came to Inflection AI to help the company again concentrate on achieving business results. Their shared North Star is easy to say, but still difficult to implement. Make data analysis conversation, accurate and emotionally aware, so that people actually use it.

We unpack the shift from Inflection from PI’s consumer roots to privacy-first Enterprise tools. That history is important because it gives the team a lead over EQ. When you combine a deep well with conversations from people to AI with modern LLMS, you get systems that explain, probe and adjustment instead of dumping and call it a day.

Shruti breaks on how dialogue with data looks in practice. Think of back and forth fairs that transfer from “what happened” to “why it happened”, then to “where otherwise this pattern appears” and “what to do,” all based on the language and values of an organization. Amit takes us under the hood about implementation choices and ownership. If a customer wants on-Prem or VPC, they get it. If they refine models on their vernacular, they can. The model, the insights and the guardrails remain under the control of the customer.

I enjoyed the honesty about adoption. The challenge of AGI gets the headlines, but it helps a merchandising manager rarely find an early decrease in life value or a CX -Lead understands the Churn risk before the end of the quarter. The duo keeps the conversation based on daily questions that stimulate figures and reduce meetings. They describe a path where EQ and IQ come together to form what Shruti calls contextual intelligence, and where brands can trust AI agents to help without losing property or voice.

If you make data useful for more people, and you want ai who sounds like your company instead of a generic assistant, it is something for you. We deal with start -up lessons, the reality of co -designing as a few during lockdowns, and how bowing works with large companies to bring conversation analysis into real workloads. It is a grounded look at where Enterprise AI is going, and a timely memory that technology should raise people, not replacing.

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