Jobber vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
$167.5M revenue 2024 (up from $143.2M 2023); 100K customers; 250K+ home service pros; 27M properties in 60+ countries; 671 employees; $83.8M funding; positive 2025 outlook; home services leader
About
Jobber was founded in 2011 in Edmonton, Canada, with a mission to help small home service businesses — landscapers, cleaners, plumbers, electricians, HVAC technicians — run more professionally and grow faster by giving them business management software purpose-built for their workflows. The company's founders identified that the home services sector was dramatically underserved by enterprise software vendors and that most small operators were managing their businesses through paper, spreadsheets, and consumer apps not designed for field work. Jobber's core technology integrates quoting, scheduling, dispatching, invoicing, payment collection, and client communication in a single mobile-first platform.\n\nJobber's platform covers the full customer lifecycle for home service businesses: online booking and quote requests, job scheduling and crew dispatch, GPS route optimization, time tracking, automated follow-up messages, online payment processing, and client history. The platform is designed for non-technical small business owners and their crews, with a mobile app that field workers use on-site and a web dashboard for office management. Jobber also offers a customer-facing portal where homeowners can approve quotes, make payments, and request repeat service — creating a professional experience that helps small operators compete with larger franchise services.\n\nJobber generated $167.5 million in revenue in 2024, up from $143.2 million in 2023, serving more than 100,000 customers and 250,000-plus home service professionals across more than 27 million properties in 60-plus countries. The company has raised $83.8 million in funding and employs 671 people. Jobber competes with ServiceTitan and Housecall Pro in the home services software market, differentiating through its SMB focus, ease of onboarding, and breadth of workflow coverage at a price point accessible to sole operators and small crews.
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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