Side-by-side comparison of AI visibility scores, market position, and capabilities
VR remote work platform enabling virtual multi-monitor workspaces. Most-used AR/VR productivity app with 2,000+ cumulative user-years; building Visor headset.
Immersed was founded with the conviction that the physical limitations of a single monitor should not constrain knowledge workers, and that virtual reality could deliver a superior multi-monitor experience from anywhere in the world. The company built its core platform around spatial computing, enabling users to work inside virtually unlimited screen real estate in a persistent, distraction-free virtual environment. Immersed has consistently ranked as the most-used AR and VR productivity application across major headset platforms.\n\nImmersed's software runs on Meta Quest, Apple Vision Pro, and other leading headsets, providing virtual workspaces that can render multiple large displays simultaneously. The platform supports remote collaboration, allowing distributed teams to work together in shared virtual offices. In parallel with its software business, Immersed developed the Visor headset — a high-resolution mixed reality device designed specifically for professional productivity use cases where display fidelity and ergonomics are paramount.\n\nImmersed has accumulated over 2,000 cumulative user-years of usage on its platform, reflecting deep engagement from a core base of power users who have adopted VR as their primary work environment. The company occupies a unique position at the intersection of spatial computing hardware and productivity software, giving it platform-level leverage as enterprise adoption of mixed reality headsets accelerates. Its hardware-software combination and early-mover advantage in VR-native work tools make it well positioned for the shift toward ambient computing.
Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.
Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).
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