Figures vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Figures raised €10M+ for crowdsourced real-time comp benchmarking and pay equity analytics for European tech companies across France, Germany, UK, and Spain; founded 2020, Paris.
About
Figures was founded in 2020 in Paris, France and raised over €10M to build a compensation benchmarking and pay equity platform specifically designed for European technology companies. The company recognized that most compensation data in Europe was either US-centric, outdated, or locked in expensive analyst subscriptions, and built a crowdsourced compensation database with real-time data from tech companies across France, Germany, the UK, Spain, and other European markets.\n\nThe platform allows HR leaders and compensation managers to benchmark salaries, equity grants, and total compensation packages against relevant peer companies using role, seniority, location, company stage, and industry filters. Figures also provides pay equity analysis tools that help companies identify and address gender and demographic pay gaps within their organizations, which is increasingly important as European pay transparency regulations come into force across EU member states.\n\nFigures integrates with HRIS systems to automate the data submission process for contributing companies, reducing the friction of participation in its benchmarking network and improving data freshness. The company competes against Radford, CompensationTool, and global platforms like Pave and Assemble in the compensation benchmarking category, with its European tech focus and pay equity capabilities as its primary differentiators.
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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