Side-by-side comparison of AI visibility scores, market position, and capabilities
Hoboken NJ Active Directory security platform; raised $200M+; identity threat detection and response for AD, Entra ID, and hybrid identity environments.
Semperis is an identity security company founded in 2014 and headquartered in Hoboken, New Jersey. The company focuses on securing and recovering Active Directory (AD) and Azure Active Directory (Entra ID) environments, which represent the most critical identity infrastructure in the majority of enterprises. Active Directory is the primary authentication and authorization backbone for Windows environments globally, and it has become one of the most attacked components in modern ransomware and nation-state intrusions — attackers that compromise AD can gain access to every system in an organization.\n\nSemperis raised $200 million in a Series C round led by JP Morgan Growth Equity Partners and Vision Blue, valuing the company at approximately $1 billion. Its platform covers three domains: Directory Services Protector (DSP) for continuous AD threat monitoring and automated attack rollback; AD Security Assessment for evaluating the attack surface of AD configurations; and Active Directory Forest Recovery (ADFR) for rapid recovery of AD from cyberattacks. The ADFR product addresses a critical gap: most organizations' backup and recovery processes are not designed to recover AD cleanly from a ransomware attack that corrupted or encrypted AD data.\n\nSemperis's Purple Knight tool, a free Active Directory security assessment, has been downloaded by more than 10,000 organizations and is widely used by IT and security teams to benchmark their AD attack surface. The company's deep expertise in AD-based attack techniques — including DCSync, Golden Ticket, Kerberoasting, and pass-the-hash attacks — informs its detection engine, which monitors AD events in real time and can automatically roll back unauthorized changes before they cause damage.
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.
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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