FloQast vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Accounting transformation platform. $200M+ ARR (Jan 2026). $1.6B valuation. 2,600+ teams (Twilio, Zoom, Snowflake). AI Agents via FloQast Transform. Founded 2013, LA. Private.
About
FloQast was founded in 2013 in Los Angeles, California, by former accountants who experienced firsthand the chaos of month-end close processes at fast-growing companies. The company's mission is to transform how accounting teams operate by replacing fragmented, spreadsheet-driven workflows with a purpose-built platform that brings structure, automation, and AI-driven intelligence to the accounting function. FloQast was designed from day one for accountants by accountants, giving it deep domain credibility and workflow alignment that generic finance automation tools lack.\n\nFloQast's platform covers the full spectrum of accounting operations, from close management and reconciliation to reporting, compliance, and AI-powered agentic workflows through its FloQast Transform product line. Over 2,600 accounting teams at companies including Twilio, Zoom, and Snowflake use FloQast to manage their close process, maintain audit trails, and ensure accuracy across financial reporting cycles. The platform integrates with major ERP systems and financial data sources, serving as the operational layer that sits on top of the general ledger to coordinate the human and automated tasks required to close books accurately and on time. FloQast Transform extends this foundation with AI agents that can autonomously handle reconciliation, variance analysis, and other high-volume accounting tasks.\n\nFloQast surpassed $200 million in annual recurring revenue in January 2026, a milestone that cements its position as one of the most successful vertical SaaS companies in the accounting technology space. The company carries a $1.6 billion valuation and remains privately held, continuing to invest in product expansion and enterprise market penetration. With AI agents increasingly capable of handling core accounting workflows, FloQast is positioned to lead the broader transformation of the CFO technology stack.
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).
AI Visibility Head-to-Head
Capabilities & Ecosystem
Capabilities
Also Compare
Track AI Visibility in Real Time
Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.