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Enterprise AI can be limited not only by what a model can do, but by whether it can reach and correctly interpret information inside a company’s existing systems. That was the central argument from Unfold co-founder and chief product officer Idan Shuster in a conversation with Omri Hurwitz at HumanX Amsterdam, as reported by TechBullion on October 2, 2026.
Why enterprise AI can struggle to use company data
Companies may already hold valuable information, but it can be spread across proprietary, legacy, and otherwise difficult-to-access business systems. Some systems expose information inconsistently or have no convenient API. As Shuster and Unfold frame the problem, making that information available to an AI system is a prerequisite to using it in workflows.
Access alone may not be enough. A record’s meaning can depend on the application interface, the workflow that produced it, custom components, and the system’s underlying structure. Shuster told The San Francisco Tribune: “If you let the agents interact directly with the data, sometimes it doesn’t make sense.” In other words, a technically reachable database is not necessarily a complete or understandable representation of how a business uses its information.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchWhat Unfold says its integration layer does
Unfold describes itself as an integration layer for enterprise systems, including those without APIs or exports. Its stated process is to connect to a system, understand it layer by layer, and deliver normalized, governed outputs into existing tools and AI workflows. The company names Splunk, Cortex, Microsoft OneLake, Snowflake, Databricks, and AI agents as parts of the surrounding stack on its official product site.
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This is Unfold’s description of its product, not an independent technical assessment or evidence that every system can be integrated in the same way. The company says initial onboarding for one system typically takes around seven days, and its current site promotes “Any system. Live in 7 days.” Treat that as a company-reported timeline, not a guaranteed service level or independently measured result.
Examples from the interview: healthcare and retail
Shuster’s interview examples illustrate how this access-and-context problem can affect different kinds of operations. The coverage does not name the organizations or provide audited outcome data.
Integrating acquired healthcare clinics
Shuster described a healthcare organization that acquires roughly 50 clinics per year, with integration of each clinic’s existing technology reportedly taking months. The example shows how differing systems can become an operational obstacle during acquisition integration; it does not establish that Unfold shortened the process or delivered a quantified saving.
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He also described a large retailer seeking access to mainframe data for fraud analysis. The example points to a possible use for connecting older systems to newer analytical or AI workflows, but the interview coverage does not report measured fraud reductions or other independently verified results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the conversation does—and does not—establish
The interview’s thesis is that enterprise AI adoption may hinge on connecting models to information companies cannot readily replace, while preserving enough system context for the information to be useful. Shuster’s background, as reported by the interview coverage, includes cybersecurity work such as penetration testing and offensive security, product management at Varonis, and service in Israel’s Unit 8200. The same coverage says Unfold first pursued security- and fraud-related data access, then broadened its focus after a healthcare CISO introduced the team to a CIO looking to use data from proprietary healthcare systems in AI workflows.
Shuster’s longer-term framing, quoted by TechBullion, is that companies with both modern and legacy software may eventually encounter the issue: “I think that every company that has existing for at least five, 10 years and have both modern software and legacy software eventually will have this problem.” That is his assessment, not a quantified forecast. The interview coverage does not provide an independent technical evaluation, customer audit, comparative benchmark, or evidence that one integration approach is best for all enterprises.
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