That foundation eventually led him to co-found Alpha Insight, where he and his team built the iControl platform – an observability solution ahead of its time. iControl addressed a problem long before it reached mainstream discussion: understanding complex distributed systems in real time, without compromising governance. The platform’s success culminated in its acquisition by HCL Software in 2017, marking not only a milestone exit but also a defining transition.

For Ian, what followed mattered even more than the acquisition itself.

“When you build a company, you think in terms of scrappiness, agility, speed. But when you scale inside an enterprise and compete against platforms like Splunk or Dynatrace, you have to think about global processes, long-term architecture, and transformation at scale. Successfully bridging those worlds – startup and enterprise – has been one of my proudest achievements” he reflects.

Today, Ian serves as General Manager of Full Stack Observability at HCLSoftware, leading a global team of more than 250 professionals with significant commercial responsibility. Yet, despite the scale of his current role, the entrepreneurial spark remains firmly intact. Ian continues to invest in and advise startups within fintech, RegTech, and enterprise AI – Most notably Surety, a next-generation RegTech platform using AI with a locally installed LLM (NeoroTalks) to transform compliance in the data-driven world.

A New Era: From Proprietary Observability to Data Freedom

One of Ian’s most compelling insights is his view that enterprise software – particularly observability – is entering a historical transition point. Over the last decade, telemetry has quietly become trapped in proprietary formats, locked inside closed systems with restrictive pricing, storage limitations, and vendor-controlled access.

As he puts it, “Telemetry has drifted into captivity – indexed, stored, and monetized by vendors who treat customer data as their product. But as AI becomes the dominant operational interface, that captivity becomes intolerable.”

In industries with compliance obligations – finance, healthcare, government – the problem is more than inefficiency. It’s existential.

AI models cannot reason about systems if they are unable to access the data freely. When history, context, anomalies, and operational patterns are locked behind proprietary APIs or limited retention windows, the true promise of AI-driven operations collapses.

Ian believes the shift ahead will not be led by platforms with the most visual analytics – but by those that allow customers to own and control their data and architecture.

“The future won’t be about dashboards” he says. “It will be about autonomy. Who owns the data? Who controls the architecture? Who has the right to apply AI without asking for vendor permission?”

His work today aligns with a clear vision: open data, open architecture, and AI reasoning engines that run locally or on enterprise-controlled environments – without vendor lock-in.

Building AI-Driven Operations with Data Sovereignty

According to Ian, the next decade of observability and platform engineering will be reshaped by a simple but defining rule:

Telemetry must be readable by modern reasoning engines – without restriction.

The existing ecosystem breaks this principle in three ways:

• Restricted access: Telemetry is limited by narrow vendor APIs.
• Abstracted formats: Raw signals are transformed and often lost.
• Short retention: Historical depth – the resource AI needs most – is discarded due to cost.

The result? AI becomes weaker, systems become opaque, and innovation slows.

But the shift toward open data models flips the equation: lower cost, higher freedom, limitless reasoning.

Ian argues that most existing observability platforms cannot adapt to this future – not because of technical incapability, but because their business models depend on the captivity of customer data.

“It’s not just architecture – it’s economics. If vendors allowed full and open telemetry access, it would break their revenue model. Customers are paying not only for technology, but for their own dependency.”

His mission, and the mission he is championing across industry collaboration, is to build the alternative: platforms where organizations – not vendors – owns and manages the data and retention, using inhouse LLMs to provide operational context for the intelligence layer across their digital ecosystems.

The Road Ahead

Today, Ian stands at the forefront of a movement redefining how enterprises will operate in the AI era. His work, whether inside HCLSoftware or alongside emerging innovators, is guided by a belief that autonomy – not dependency – will shape the next generation of enterprise technology.

The leaders of the future will not be those with the largest platforms, but those who give organizations full sovereignty over their operational intelligence.

As the world accelerates into AI-driven automation, Ian Philips is helping shape a future where data is not trapped, reasoning is unrestricted, and innovation is no longer constrained by architectural or commercial barriers.

A future where enterprises – not vendors – control their narrative.