Uptycs
بواسطة Uptycs, Inc.
Uptycs is a comprehensive, unified Cloud-Native Application Protection Platform (CNAPP) and Extended Detection and Response (XDR) solution designed to secure the modern hybrid attack surface. By consolidating security functions that traditionally reside in siloed tools—such as Cloud Security Posture Management (CSPM), Cloud Workload Protection (CWPP), and Endpoint Detection and Response (EDR)—Uptycs provides a single source of truth for security telemetry. The platform is built on a foundational 'security analytics' approach, normalizing telemetry from cloud providers, Kubernetes clusters, containers, and traditional endpoints into a unified data model. This allows security teams to observe, analyze, and contextualize threats across development and runtime environments without the friction of multiple agents or complex data pipelines. At its core, Uptycs leverages a high-performance lambda architecture and a SQL-powered backend to process streaming telemetry in real-time. This unique architecture enables a 'Google-like' search experience across an organization's entire digital estate, allowing analysts to perform historical forensic investigations or real-time queries using standard SQL. By providing deep visibility into system activity—including process execution, network connections, and file integrity—Uptycs helps organizations detect sophisticated threats, prioritize risks based on business context, and accelerate incident response. The platform is particularly well-suited for high-growth enterprises and security-conscious organizations that require scalable, multi-cloud protection with a focus on deep observability and verifiable evidence.
Uptycs distinguishes itself through its unique 'First Principles' architecture, which treats security as a data analytics problem rather than a collection of disparate rules. Unlike competitors that rely on pre-defined signatures or black-box AI models, Uptycs normalizes all telemetry at the source into a structured, SQL-queryable format. This enables 'No-ETL' security analytics, where data from macOS, Windows, Linux, AWS, Azure, and GCP are all stored in a unified data model. One of its most significant advantages is the use of eBPF-based syscall observability, which provides deep runtime visibility without the kernel stability risks associated with traditional agents. Furthermore, Uptycs is the only platform that truly unifies CNAPP and XDR, allowing analysts to trace a threat from a developer's laptop to a compromised container in the cloud using a single UI. The recent launch of Juno AI reinforces this advantage by offering 'verifiable' AI—where every conclusion is backed by actual SQL queries and log data, eliminating the 'hallucination' risks common in other AI security tools. Additionally, its ability to scale to millions of endpoints while maintaining low-latency response times makes it the preferred choice for massive, heterogeneous environments that require both breadth of coverage and depth of analysis.
البائع
Uptycs, Inc.
موقع المقر الرئيسي
Waltham, Massachusetts, USA
الموقع الإلكتروني للشركة
https://www.uptycs.com/
سنة التأسيس
2016
البريد الإلكتروني
Unified Risk Scoring
eBPF Runtime Protection
Juno AI Assistant
Attack Path Mapping
Cloud Security Posture Management (CSPM)
Vulnerability Management
Kubernetes Security (KSPM)
Endpoint Detection & Response (EDR)
$3
لكل Workload لكل Month
$6
لكل Workload لكل Month
Custom
لكل Workload لكل Month
English
Where does Uptycs have offices in GCC?
Not available.
Who are Uptycs customers in the Middle East?
Not available.
What is Uptycs local address?
Not available.
Is Uptycs available in Arabic?
Not available.
Does Uptycs use AI? And where?
Uptycs uses AI extensively, in both classic machine‑learning detections and newer LLM‑based “AI analyst” capabilities.
At its core, Uptycs applies machine learning to anomaly-detect telemetry from endpoints, containers, Kubernetes, and cloud workloads. The platform continuously analyzes eBPF-powered runtime data (processes, syscalls, network, CPU/disk patterns) to establish baselines and score deviations, automatically flagging outliers such as unusual CPU usage, unexpected network connections, or abnormal process behavior that map to MITRE ATT&CK techniques. Security teams can use out‑of‑the‑box ML models or define their own model scopes and learning windows (for example 24‑hour baselining per Kubernetes label or workload group), which then drive contextual anomaly alerts.
On top of that, Uptycs now embeds a verifiable AI security analyst called Juno AI. Juno is an LLM‑powered assistant that runs inside the Uptycs platform, interpreting detections, correlating multi‑source signals, summarizing investigations, explaining attack paths, and suggesting next steps, all while exposing its reasoning steps and underlying evidence (“glass box” AI). It operates over Uptycs’ unified ontology and structured telemetry—using an LLM (currently Claude) to issue SQL queries against normalized security data rather than raw logs—which reduces hallucinations and makes every AI conclusion auditable.
Is Uptycs Web3 company?
No.
Are there any Web3 components in Uptycs?
No.
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