From Proprietary AI to Flexible Enterprise Platforms
Enterprise AI platforms that avoid vendor lock-in are systems designed so organizations can plug in their preferred AI models and tools, swap them as needs change, and maintain control over data and governance without being bound to a single supplier. This shift is now visible across workplace technology, where AI is embedded in AV, unified communications, and digital signage. At large industry events, vendors that once hard-coded proprietary models are moving toward modular designs and interoperable architectures. Instead of selling a closed stack, they expose APIs and integration layers that route AI requests through the customer’s own environment. The result is a new generation of autonomous workplace systems that combine BYOM flexibility with operational AI, promising fewer manual tasks, faster incident resolution, and a smoother digital workplace experience for employees and support teams alike.
Appspace BYOM: AI Flexibility Without Vendor Lock-In
Appspace is pushing vendor lock-in avoidance to the foreground with its new BYOM (Bring Your Own Model) capability for enterprise AI platforms. Rather than forcing customers to use predefined models, BYOM routes AI traffic through the customer’s own AI environment and API keys, reusing existing investments in Microsoft Azure OpenAI, Azure AI Foundry, or Google Gemini. This design extends AI across communications, knowledge discovery, workplace services, space booking, and visitor management, positioning Appspace as a broader workplace intelligence platform instead of a narrow chat or content tool. BYOM flexibility also gives IT teams more control over governance, compliance, and cost, since they can select the best model per use case and align usage with existing enterprise agreements. According to invidis, Appspace joins Poppulo among the few ISVs offering modular AI integration while many others still hard-code their models.
Lena’s Autonomous Operations for AV and Unified Communications
NetSpeek’s Lena platform shows how autonomous workplace systems are maturing beyond basic monitoring into self-directed operations. Lena is an AI-native platform for AV, unified communications, and digital signage environments that can detect operational issues, diagnose root causes, and execute remediation workflows across multi-vendor setups with little to no human intervention. At InfoComm, Lena is set to display how it identifies active problems, troubleshoots across AV devices, UC platforms, and network equipment, then takes corrective actions within defined guardrails. NetSpeek designed Lena with multiple autonomy levels: it can either remediate issues end-to-end or recommend actions that require administrator approval in more controlled environments. A new memory framework adds historical context for devices, rooms, and users so the platform can recognize patterns and improve diagnosis over time, strengthening service reliability as enterprise collaboration environments scale.
Multi-Vendor Ecosystems and the End of Single-Stack AI
Both Appspace and NetSpeek are building around multi-vendor ecosystems rather than closed stacks, signaling a broader move in enterprise AI platforms. Lena’s integrations span collaboration and display vendors such as LG, Microsoft, Neat, Zoom, and network partner NETGEAR AV, and NetSpeek has announced additional partnerships with Avocor, DTEN, Jabra, and Cisco. This breadth allows Lena to coordinate autonomous workflows across diverse AV and UC infrastructures without demanding a single-vendor environment. On the workplace experience side, Appspace’s BYOM model connects to external AI providers instead of locking customers into its own AI. Together, these strategies show how vendor lock-in avoidance and interoperability now shape product roadmaps. Instead of competing on proprietary algorithms alone, platforms compete on how well they orchestrate many tools, models, and hardware ecosystems under one operational AI layer.
Balancing Autonomy, Governance, and Human Control
The emerging pattern at InfoComm points to a blend of autonomy and choice: enterprises want autonomous workplace systems that reduce manual intervention while keeping clear guardrails around AI behavior and vendor selection. Lena addresses this by allowing different autonomy modes, from full automatic remediation to recommendation-only workflows where administrators approve changes. Appspace’s BYOM approach keeps AI governance in the customer’s hands by running models in their own AI environments, under their own API keys and compliance policies. This balance helps organizations gain the efficiency of operational AI without surrendering oversight or becoming dependent on one supplier’s roadmap. As more enterprise AI platforms adopt BYOM flexibility and multi-level autonomy, IT teams can standardize on architectures that remain adaptable, switching models or vendors as business needs shift while maintaining a consistent operational framework.
