Align Technology vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
San Jose clear aligner orthodontics inventor (NASDAQ: ALGN) at $3.23B 2024 revenue; 20 million Invisalign patient milestone Q1 2025 across 280,000+ doctors with iTero Lumina scanner competing with 3M Clarity for orthodontic clear aligner prescriptions.
About
Align Technology, Inc. is a San Jose, California-based global medical device company — publicly traded on NASDAQ (NASDAQ: ALGN) as an S&P 500 component — operating as the inventor of the Invisalign System and the world leader in clear aligner orthodontics, reaching 20 million Invisalign patients treated worldwide in Q1 2025 through a network of 280,000+ Invisalign-trained doctors across 100+ countries. In fiscal year 2024, Align reported $3.23 billion in total revenue with Q4 2024 revenue of $995.2 million (+4.0% year-over-year). Align's product portfolio comprises the Invisalign System of clear aligners, iTero intraoral digital scanners (including the iTero Lumina with 3X wider field of capture in a 50% smaller wand), and exocad CAD/CAM software for digital dental workflows. Manufacturing is based in Mexico with treatment planning performed in Costa Rica. CEO Joseph Hogan joined from GE Healthcare in 2015. Founded 1997 by Zia Chishti and Kelsey Wirth in San Jose.
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.
About
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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