Inside Polestar Analytics and the Future of Converged Data E…

As AI continues to reshape industries and business models, Polestar Analytics is positioning itself not just as a service provider but as a strategic partner by helping organisations align data, decisions and transformation. 

In a conversation with Polestar Analytics’ co-founders, Chetan Alsisaria (CEO), Amit Alsisaria (COO) and Ajay Goenka (CFO), AIM discussed how they envision AI evolving, what enterprise readiness truly means and why convergence is the next frontier for data-driven businesses.

Rethinking Enterprise AI

Reflecting on how enterprise AI has changed over the last two years, Chetan said the biggest realisation has been that success in AI is as much about defensibility as it is about innovation.

“The real gap lies between AI ambition and enterprise readiness,” he explained. “Many organisations still operate in silos across teams, technology and processes, leaving no clear path from pilot to production. The need of the hour is alignment, convergence, ownership and trust—not just algorithmic brilliance.”

He added that as hyperscalers and startups pour billions into AI, true differentiation will come from domain context, agility and trust by building IP that is industry-aware, outcomes-driven and closely aligned with the business.

Ajay, on the other hand, believes the next wave of AI leadership will require both technical fluency and human intelligence. “The next generation of AI leaders will need to connect data science with empathy, ethics and domain fluency,” he said. “We’re moving from a world of coders to a world of contextual thinkers.”

Betting on Convergence

Meanwhile, Amit described Polestar Analytics’ strategic bet on what he calls “the great convergence of data and process”.

He pointed out that while 80% of enterprise data is unstructured, most organisations still design their AI strategies around the structured 20%. “That’s like trying to understand human behaviour by only reading spreadsheets,” Amit said.

Amit explained that the real winners in the next decade won’t be the ones building the most advanced models, but those who can turn unstructured data—like emails, documents, conversations and videos—into actionable and operational intelligence.

AI Adoption in India

According to Ajay, Indian enterprises are at an inflexion point in their AI journey.

“A few years ago, the conversation was around AI experimentation. Today, it’s about how to scale responsibly and drive measurable outcomes,” he said.

Across the world, industries are no longer evolving through incremental change. They’re reimagining entire systems with AI that is contextual, cost-efficient and outcome-first.

“The biggest opportunity lies in convergence,” Ajay added. “True transformation will happen when data, decisions and delivery operate in one connected ecosystem.”

From Services to Platforms

Polestar Analytics recently raised new funding to accelerate the development of its 1Platform, an enterprise-grade AI and data convergence stack.

“Our fundraiser is a strategic step towards transforming from a services-led organisation into a platform-driven AI company,” Chetan said. 

The company plans to deploy capital across three areas: IP development, enterprise expansion and global growth. “We’re doubling down on the convergence of data, decisions and automation, helping enterprises scale faster with governance and measurable impact built in from day one,” he said.

Amit cited a recent project with a consumer goods company where 1Platform unified production, sales and supply chain data into a single intelligent layer.

“Earlier, leaders were making decisions on outdated dashboards,” he said. “With 1Platform, they can now ask, ‘What’s putting my Q4 targets at risk?’ and get real-time, contextual answers.”

Collaborating Across the Ecosystem

On partnerships, Amit shared that Polestar Analytics’ collaborations with hyperscalers, startups and academia go beyond traditional alliances.

“With hyperscalers like Microsoft and Databricks, we’re doing co-creation—building joint solutions using Azure and Databricks stacks,” he said. 

Polestar Analytics also partners with institutions like IIM Calcutta for the PGDBA programme. “We help universities align with real-world industry needs while tapping into fresh thinking,” Amit said.

On startups, he pointed out, “It’s about speed and specialisation. Startups bring focused innovation; we bring market access and implementation expertise.”

When asked what sets Polestar Analytics apart, Chetan said enterprises should seek partners that understand both business context and technical complexity.

“The right AI partner connects data, workflows and outcomes,” he said. “They take a neutral, interoperable approach and commit to ROI and governance from day one. That’s exactly what we’ve built with 1Platform.”

He added that the company’s differentiation lies in “speed to value, contextual intelligence and measurable business transformation.”

Balancing Ambition and Responsibility

For Ajay, responsible scaling is central to Polestar Analytics’ growth philosophy.

“It’s not about how quickly you can innovate, but how responsibly you can scale,” he said. “Every AI solution we build touches data, people and decisions. That comes with immense responsibility.”

Polestar Analytics embeds governance and ethical checkpoints into its delivery model. “Responsibility means ensuring every solution reflects our values as much as it drives value,” he added.

Through its centre of excellence, the company tests every emerging technology internally before deploying it for clients. “When we walk into a client meeting, we’re not speaking theoretically; we’ve already used it ourselves,” Amit said.

Looking Ahead to 2030

According to Chetan, many enterprises struggle to derive measurable value from GenAI due to poor governance and a lack of alignment.

“My advice: start small, but start with purpose,” he said. “Treat every pilot as if it’s going to scale. Build governance and LLMOps from day one.” 

He shared that GenAI creates real value only when it’s built on an organisation’s own data, workflows and context, and when success is measured through meaningful metrics such as adoption, accuracy and tangible business impact. 

Chetan described Polestar Analytics’ long-term goal as enabling organisations to operate as truly AI-first enterprises, where data, intelligence and execution function as a single, seamless system.

“If we’ve done our job right, enterprises will operate with greater agility, lower friction and higher trust,” he said. “Success is when AI isn’t a project anymore—but the default way enterprises think, decide and act.”

The post Inside Polestar Analytics and the Future of Converged Data Ecosystems appeared first on Analytics India Magazine.

Generated by RSStT. The copyright belongs to the original author.

Source