By When a vendor reprices its platform or changes its model, organizations with proprietary data infrastructure face a brutal choice: absorb costs that destroy application economics or re-architect everything under pressure. At AI scale, where workload costs are already unpredictable, that exposure is not a future risk. It is a present one. Data sovereignty regulations like CRA add a compliance dimension that proprietary single-cloud deployments are increasingly unable to satisfy.
In this interview on TFiR, Bianca Lewis, Executive Director at the OpenSearch Software Foundation, breaks down why vendor neutrality has become a non-negotiable priority for data infrastructure teams and how open platforms enable organizations to retain sovereign control of their data regardless of how AI costs and compliance demands evolve.
Guest: Bianca Lewis, Executive Director at OpenSearch Software Foundation
Show: Let’s Talk
LinkedIn: Bianca Lewis
Watch the discussion on YouTube
Here is what every platform engineer and data infrastructure team needs to know.
Technical Deep Dive
Q: Why has vendor neutrality become a non-negotiable requirement for data infrastructure teams?
Bianca Lewis, Executive Director at the OpenSearch Software Foundation, ties vendor neutrality directly to the economics of AI scale. Organizations cannot reliably predict what AI workloads will cost them, and a vendor repricing or changing its model mid-growth forces a full re-architecture of data infrastructure. Compliance obligations, including CRA and data sovereignty regulations, compound the risk for teams that have committed to a single proprietary platform or cloud provider.
“The safest progress in this present time of uncertainty is to develop on an open infrastructure where you own your own data infrastructure in a sovereign way.”
Bianca Lewis, Executive Director, OpenSearch Software Foundation
Q: How do unpredictable AI workload costs make vendor lock-in a business-level threat?
Lewis points out that the token economy and associated AI buzz have not resolved the core question: what do AI applications actually cost at scale? If an application turns unprofitable at production scale, the business impact is immediate. When that application’s data infrastructure is tied to a single vendor, fixing the economics requires re-architecting infrastructure under financial pressure, which is a compounding problem most organizations are not prepared for.
“How much do my applications really cost me at AI scale? And if we find ourselves losing money on an application, what does that mean for the business?”
Bianca Lewis, Executive Director, OpenSearch Software Foundation
Q: What compliance pressures are accelerating the shift away from proprietary data platforms?
Lewis names CRA and data sovereignty requirements as active drivers, not future concerns. Proprietary vendor and single-cloud architectures create compliance exposure because organizations do not fully own or control where their data lives or how it is governed. Open infrastructure gives teams direct control over their data estate, which is increasingly the only architecture that satisfies emerging regulatory requirements across multiple jurisdictions.
“What about all the compliance like CRA and data sovereignty that are coming up here? The challenges are very numerous if you put your eggs into a proprietary vendor or a single cloud.”
Bianca Lewis, Executive Director, OpenSearch Software Foundation
Q: What is the right strategy when AI cost structures and vendor pricing are still unclear?
Lewis recommends deferring commitment. With AI workload economics, compliance requirements, and vendor pricing models all in flux, the priority is to avoid locking into any single approach before the picture becomes clear. She argues that the one-year, two-year, and three-year picture will become clearer, but the cost of being wrong inside a proprietary architecture is too high to justify early lock-in.
“The priority at the moment is not to lock into any one approach. And there’s no better system for that than the open platform of OpenSearch.”
Bianca Lewis, Executive Director, OpenSearch Software Foundation
Resources & Documentation
- OpenSearch, open source search and analytics platform enabling vendor-neutral, sovereign data infrastructure
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👇 Click to Read Full Raw Transcript
Swapnil Bhartiya: When it comes to data, because apps work can come and go. Data is something which is really, really critical to organizations. The report also found that 71% of organizations now treat deploying independently of any single vendor. Because that does raise the risk of of course, vendor lock in. It is becoming a strategic priority. Can you talk about why has vendor neutrality became such a non negotiable topic for data infrastructure? And what role is OpenSearch playing in enabling that?
Bianca Lewis: I do believe that that’s very closely linked to the AI discussion that we just had from different perspectives on an AI scale. A lot of companies today are not really sure how much AI workloads are going to cost them. We all heard the token economy and the buzz around that. But the fact is, how much do my applications really cost me at AI scale? And if we find ourselves losing money on an application, what does that mean for the business? How do we secure things at scale as well? What happens with all of these increasing workloads that we might expect or might not expect, and a vendor suddenly raises their prices or gives a pricing model? Then I have to re architect my whole data infrastructure. What about all the compliance like CRA and data sovereignty that are coming up here? And the challenges are very numerous if you put in your eggs into a proprietary vendor or a single cloud. And that trend has become very clear, that the safest progress in this present time of uncertainty is to develop on an open infrastructure where you own your own data infrastructure in a sovereign way. When you figure out all of these questions and what they mean to your business, your choices will become clearer in one year, two years, three years. But the priority at the moment is not to lock into any one approach. And there’s no better system for that than the open platform of OpenSearch.
