Touchplan vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Bootstrapped; $550-1,250/month pricing; 23% annual revenue growth 2021; 210% activity increase; founded 1999; cloud-based construction planning leader
About
Touchplan is a lean construction planning and scheduling platform founded in 1999 that digitizes the Last Planner System methodology — a collaborative, commitment-based scheduling framework developed by construction management researchers Glenn Ballard and Greg Howell. The company was built on the premise that traditional Gantt-chart-based scheduling produces plans that diverge from reality almost immediately on active construction sites, and that reliable workflow requires frontline foremen and trade partners to make and track explicit weekly work commitments. Touchplan translates these analog planning practices — which relied on sticky notes on whiteboards — into a cloud-based collaborative environment accessible from any device on or off the jobsite.\n\nTouchplan's platform enables general contractors and owners to run pull planning sessions, manage lookahead schedules, track percent plan complete (PPC) metrics, and analyze constraint removal across all trades on a project. The software integrates with project management platforms including Procore and supports multi-stakeholder collaboration without requiring all participants to maintain separate licensed accounts. Pricing ranges from $550 to $1,250 per month per project, positioning Touchplan as accessible for mid-size commercial contractors without the enterprise overhead of full project controls software.\n\nTouchplan has grown steadily on a bootstrapped basis, reporting 23% annual revenue growth and a 210% increase in platform activity year over year — metrics that reflect organic expansion within the lean construction community rather than venture-backed growth marketing. The company has built a loyal user base among contractors who have adopted Last Planner as a standard operating methodology, and it benefits from the growing recognition that collaborative planning reduces rework and schedule overruns on complex commercial and industrial projects. Touchplan competes in a niche where its methodology-first positioning differentiates it from broader construction management platforms.
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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