Best AI Security Software - Page 6
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Compare the Top AI Security Software as of September 2026 - Page 6
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Reclaim Security
Reclaim Security
Reclaim Security is an AI-driven cybersecurity platform designed to automatically identify and fix security exposures across an organization’s existing security tools and infrastructure. Instead of simply detecting vulnerabilities or generating alerts, it focuses on automated remediation, helping security teams resolve misconfigurations, enforce security policies, and reduce risk without requiring extensive manual intervention. It scans the organization’s security stack, including cloud environments, identity platforms, endpoint protection tools, and other defenses, to identify gaps, weak configurations, or ineffective controls that could be exploited by attackers. Once risks are detected, it analyzes them in the context of real-world attack techniques and prioritizes the issues that pose the greatest threat. It then proposes remediation actions and can automatically deploy those changes once approved, ensuring security configurations remain optimized. -
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Raven
Raven
Raven is a runtime application security platform designed to protect cloud-native applications by operating directly inside the application during execution, rather than relying on external defenses. It provides real-time visibility into how code actually runs, allowing it to understand execution flows, libraries, and function-level behavior in order to detect and stop malicious activity before it occurs. Unlike traditional tools such as WAF or EDR that monitor from the outside, Raven embeds itself within the application, enabling it to prevent exploits, supply chain attacks, and zero-day threats even when no known vulnerability or CVE exists. It continuously monitors runtime behavior, identifies abnormal patterns or misuse of legitimate logic, and responds immediately to block harmful execution. It also helps teams prioritize security efforts by filtering out the majority of irrelevant vulnerabilities and focusing only on those that are truly exploitable. -
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depthfirst
depthfirst
depthfirst is an AI-native application security platform designed to help organizations detect, prioritize, and fix software vulnerabilities by deeply understanding their code, infrastructure, and business logic as a unified system. depthfirst, built around its core “General Security Intelligence,” analyzes entire repositories and environments to map how systems actually function, enabling it to uncover complex, real-world vulnerabilities that traditional scanners often miss. It evaluates full attack paths, permissions, and data flows to determine whether an issue is truly exploitable, significantly reducing false positives and allowing teams to focus only on meaningful risks. depthfirst operates across multiple layers of the stack, including source code, dependencies, secrets, containers, and running applications, providing continuous security coverage from development through production. -
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Nebulock
Nebulock
Nebulock is an AI-powered autonomous threat hunting platform designed to proactively identify hidden security threats across an organization’s entire technology stack. It continuously analyzes telemetry data from endpoints, identity systems, cloud environments, networks, and SaaS tools, correlating signals across these layers to uncover attacks that traditional tools miss. It uses agentic AI to automate the full threat hunting lifecycle, forming hypotheses, testing them against real-time data, and translating findings into validated behavioral detection rules without manual intervention. Its core architecture includes a contextual “behavior graph” that builds a baseline of normal activity and detects anomalies by comparing events across a unified timeline, enabling more accurate identification of insider threats, credential misuse, and lateral movement. Nebulock emphasizes behavior-based detection rather than relying on static indicators. -
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UPX
UPX Cybersecurity
UPX (Ultimate Packer for eXecutables) is a high-performance executable compression tool designed to reduce the size of programs and libraries without affecting their functionality or performance. It works by compressing executable files such as EXE, DLL, and other formats across multiple operating systems, including Windows, Linux, and macOS, typically reducing file sizes by 50% to 70%, which helps decrease disk usage, download times, and network load. The compressed executables remain fully self-contained and run exactly as before, as it automatically decompress at runtime without requiring additional dependencies or noticeable memory overhead. UPX uses efficient lossless compression algorithms and supports in-place decompression, allowing programs to execute directly from memory while preserving speed and behavior. It is designed to be secure and transparent, as its open-source nature allows antivirus and security tools to inspect compressed files without obstruction. -
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Snapper
Snapper
Snapper is an AI agent security platform designed to provide end-to-end governance and protection for organizations deploying AI agents across applications, networks, and systems. It delivers runtime enforcement by evaluating every agent action, including tool calls, API requests, and data access, before execution through a policy-driven rule engine with multiple enforcement layers. It offers unified visibility into AI usage by monitoring network traffic, browser activity, DNS, and processes to detect unauthorized tools and “shadow AI,” while also intercepting outbound LLM requests through SDK wrappers and a network proxy to evaluate, redact, and log sensitive data in real time. Snapper includes advanced threat detection capabilities that identify prompt injection, exploit chains, anomalous behavior, and multi-step attack patterns using behavioral baselines, kill chain tracking, and composite trust scoring. -
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Simaril
Simaril
Silmaril is a self-healing prompt injection defense designed to protect AI systems from increasingly complex, multi-step attacks that traditional guardrails fail to stop. It operates by wrapping inference calls and evaluating whether an execution sequence is leading toward a harmful outcome, rather than simply filtering inputs. It uses a multihead classifier that analyzes user intent, application context, and execution states together, enabling it to detect indirect injection, multi-turn attack chains, context poisoning, and tool abuse before damage occurs. Silmaril continuously strengthens its defenses through autonomous threat hunting agents that probe systems, discover vulnerabilities, and generate synthetic training data from real attack scenarios. These insights are used to retrain the model automatically, deploying updated protections in under an hour and propagating anonymized defenses across all deployments. -
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Proofpoint AI Security
Proofpoint
Proofpoint AI Security is a unified platform designed to help enterprises govern, monitor, and protect the use of AI systems, large language models, and autonomous agents across the organization. It provides visibility into both sanctioned and unsanctioned AI usage, enabling security teams to discover shadow AI tools, observe prompts and responses, and understand how AI interacts with sensitive data in real time. It applies intent-based detection and behavioral analysis to identify anomalies, prompt injection attempts, and risky interactions, while enforcing policies directly during runtime to prevent data leakage and misuse. It reconstructs full AI transactions, from user input to agent actions and outcomes, giving organizations complete traceability and audit readiness. With controls that extend across endpoints, browsers, and AI agent connections, it enables granular access governance and ensures that AI systems only access and share appropriate information. -
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Straiker
Straiker
Straiker is an AI-native security platform built specifically to protect enterprise AI applications and autonomous agents, focusing on the emerging risks of “agentic AI” systems that interact with tools, APIs, and sensitive data. It provides full visibility and control across the entire AI stack by analyzing behavioral signals from models, prompts, tools, identities, and infrastructure, enabling real-time detection and prevention of AI-specific threats such as prompt injection, privilege escalation, data exfiltration, and malicious tool usage. It combines continuous discovery, adversarial testing, and runtime protection through core components like Discover AI, Ascend AI, and Defend AI, which together identify all active agents, simulate attacks to uncover vulnerabilities, and enforce real-time safeguards during execution. Its multi-layered architecture captures deep contextual signals across user interactions, networks, and agent workflows. -
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Matters.AI
Matters.AI
Matters.AI is the first AI Security Engineer for Data, built for the AI and data layer to autonomously see, understand, and resolve data misuse before the SOC opens a ticket. It protects what truly matters wherever data lives or travels, functioning like an AI security engineer that understands context, monitors behavior, and protects sensitive data autonomously across cloud, SaaS, endpoints, microservices, and AI pipelines. Matters is built on semantic intelligence, nearest neighbor search, data lineage modeling, and predictive behavior analysis, so it does not just detect threats; it understands context, anticipates risk, and takes action proactively. Instead of relying on static rules, regexes, dashboards, and noisy alerts, Matters reads between the lines, traces risk in motion, and never sleeps. It identifies sensitive data not just by how it looks, but by what it represents, tracking data across cloud, SaaS, endpoints, and beyond using fingerprinting and eBPF. -
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OpenAI Daybreak
OpenAI
OpenAI Daybreak is frontier AI for cyber defenders and OpenAI’s vision for changing the way software is built and defended. Daybreak means seeing risk earlier, acting sooner, and helping make software resilient by design, starting from the premise that the next era of cyber defense should be built into software from the beginning. It is not only about finding and patching vulnerabilities, but about helping systems become resilient to them by design. Daybreak brings AI into modern cyber defense by helping defenders reason across codebases, identify subtle vulnerabilities, validate fixes, analyze unfamiliar systems, and move from discovery to remediation faster. Because those same capabilities can be misused, Daybreak pairs expanded defensive capability with trust, verification, proportional safeguards, and accountability. It combines the intelligence of OpenAI models, the extensibility of Codex as an agentic harness, and security partners across the security flywheel. -
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Ocean
Ocean
Ocean is an agentic email security platform that prevents AI-powered targeted attacks, automates triage, and gives employees real-time guidance. Traditional defenses scan the surface for anomalies and patterns that AI is now trained to avoid, while Ocean goes deeper by investigating every email before it reaches the inbox, not after the damage is done. Its central intelligence engine, Ray, coordinates a swarm of purpose-built agents that understand intent, enrich context, and follow the evidence across infrastructure, files, abuse mailboxes, links, identity, financial signals, quarantine, and contacts. Ocean builds a living memory of how an organization operates and communicates, adapts from day one, and constantly learns. Every verdict comes with the full reasoning behind it, every signal checked, and every step taken, backed by evidence instead of a score or black box. -
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Google AI Threat Defense
Google
Google AI Threat Defense is an AI-powered cybersecurity platform designed to help organizations proactively predict, prioritize, and remediate threats at machine speed. Combining the reasoning capabilities of Gemini, contextual risk analysis from Wiz, automated code remediation through Gemini and CodeMender, and frontline threat intelligence from Mandiant, the platform enables security teams to continuously identify exposures, validate risks, accelerate remediation, and monitor environments for emerging threats. Built around a four-step framework of Prepare, Scan, Remediate, and Monitor, Google AI Threat Defense helps organizations strengthen security across multicloud, AI, SaaS, code, and hybrid environments while reducing response times and improving operational resilience against modern AI-driven attacks. -
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Gray Swan
Gray Swan
Gray Swan is an enterprise AI security and evaluation platform that helps organizations deploy AI with confidence by protecting LLM applications, agents, and model deployments from emerging threats, policy violations, and harmful content. It integrates with any LLM provider to add security without disrupting existing workflows, combining automated adversarial testing, continuous red teaming, runtime monitoring, and adaptive protections. Gray Swan tests beyond known attacks by using threat intelligence from 15,000+ adversarial researchers and more than three million attack attempts generated through its Arena, helping teams discover vulnerabilities before they appear in public databases. Its core products include Shade, an advanced AI vulnerability assessment platform that continuously probes LLMs like a security researcher working 24/7, and Cygnal, a runtime monitoring and protection layer for AI interactions. -
15
GuardionAI
GuardionAI
GuardionAI is an Agent and MCP Security Gateway that provides unified security for AI agents and Model Context Protocol tools operating on enterprise data. It sits in the execution path to discover, redact sensitive data, enforce protection, and give teams visibility into actions that traditional SIEM, DLP, and identity layers cannot see. Every agent action is inspected, enforced, and logged at the protocol level across AI agents, LLM apps, RAG systems, chatbots, coding agents, MCP servers, internal tools, databases, operating systems, and cloud environments. GuardionAI protects against critical AI threats such as prompt injection, system override, web attacks, MCP tool poisoning, malicious code execution, NSFW content, PII and credential exposure, confidential data leakage, off-topic drift, and unauthorized access, mapped to OWASP LLM Top 10 and agentic AI threat frameworks. Its gateway provides four layers of protection. -
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General Analysis
General Analysis
General Analysis is an AI security platform that helps security teams adversarially test, monitor, and protect AI agents and systems in production. It is built to help organizations understand AI risk, prevent incidents, and secure real AI deployments across employee copilots, coding agents, customer support agents, healthcare assistants, legal assistants, financial copilots, creative pipelines, and other agentic workflows. It maps AI applications and agents across prompts, retrieval, tools, MCP servers, browser actions, permissions, repositories, cloud accounts, SaaS workflows, and business processes, then generates context-aware attacks that expose system-level risks. Its automated red teaming uses attacker models that adapt to target responses and produce multi-step exploit chains, helping teams uncover vulnerabilities that static prompt sets or endpoint-only tests may miss. -
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Constellation Gate AI
Constellation Gate AI
Constellation Gate AI is a drop-in defense layer for AI agents, built to sit between the agent and the model while screening every request for attacks and leaks. Gate acts as an inline gateway for coding agents and model APIs, protecting workflows without requiring major code changes. Users can point existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode at Gate and inherit prompt-injection defense, secret scanning, PII redaction, token optimization, and a verifiable audit trail. The platform is designed around three real risks: prompt injection, credential and PII leakage, and hijacked tool calls. Instead of relying on the model to defend itself, Gate blocks attacks before they reach the model, redacts secrets before responses return, and stops attacker-controlled tool outputs before an agent acts on them. Gate accepts the same calls an agent already makes, forwards them to the model, scans every call and response in both directions. -
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Antares
Cisco
Antares is a family of open-weight security small language models purpose-built to localize known vulnerabilities inside large codebases. Antares-350M and Antares-1B are compact enough to run locally or on premises, helping teams keep proprietary source code inside their environment while reducing inference cost and runtime. Starting from a vulnerability description, advisory, or CWE category, the model follows an iterative investigation process similar to a human analyst, it searches for relevant code patterns, reads candidate files, incorporates new evidence, changes direction when a path is unproductive, and narrows the search to the files most likely to contain the weakness. Antares returns a ranked list of potentially vulnerable source files together with the terminal exploration trace that produced the result, making findings easier to review and prioritize. -
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MAI-Cyber-1-Flash
Microsoft
MAI-Cyber-1-Flash is Microsoft AI’s compact, code-heavy security model for finding vulnerabilities in complex codebases. Derived from the MAI-Thinking-1 lineage and built from scratch on high-quality data, it is deeply integrated into MDASH, Microsoft’s multi-agent vulnerability identification and remediation harness. MDASH uses more than 100 expert-tuned agents and multiple leading models to find, validate, and remediate software vulnerabilities, while MAI-Cyber-1-Flash efficiently handles up to 90% of tasks. Exceptionally difficult cases can be routed to larger models such as GPT-5.4, creating a well-tuned multi-model system that selects the right model for each task. Together, MDASH and MAI-Cyber-1-Flash achieved 96% on CyberGym, outperforming Mythos, Gemini, and GPT-based alternatives in reasoning over large codebases to identify vulnerabilities. -
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Codename MDASH
Microsoft
Codename MDASH is an agentic code scanner in Microsoft Defender that uses a multi-model AI system to detect, validate, and remediate vulnerabilities with greater depth than traditional static analysis. It extends Defender CLI with a multistage pipeline in which specialized agents collaborate across four stages. Prepare ranks files by risk using call-graph analysis and code-complexity metrics, prioritizing functions most likely to contain vulnerabilities. Scan sends ranked code to more than 100 expert agents, including injection, memory-safety, and auth-bypass auditors, with each agent focused on a specific vulnerability class. Validate combines taint analysis, type resolution through Language Server Protocol servers, and multi-model agentic debate to refine confidence and reduce false positives. Dedup consolidates overlapping results into a final set of unique actionable findings. -
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Formal
Formal
Formal is a protocol-aware reverse proxy that secures access to databases, APIs, infrastructure, and AI tools by enforcing least privilege at the wire-protocol level. Deployed as a single stateless binary in a VPC through Terraform, Kubernetes, or Docker, it sits between identities and resources without application changes, SDKs, or agents. Formal parses more than 15 protocols, including PostgreSQL, MySQL, MongoDB, Snowflake, SSH, Kubernetes, HTTP, MCP, S3, Redis, RDP, BigQuery, ClickHouse, and DynamoDB, allowing query-level decisions instead of generic network filtering. Policies can authenticate and authorize users, mask or filter fields, rewrite requests, block actions, require MFA, quarantine sessions, suspend access, or support impersonation across session, request, and response stages. Teams can secure AI agents and MCP servers by stripping PII before it reaches a model, blocking unauthorized tool calls, and auditing every action. -
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Darktrace / SECURE AI
Darktrace
Darktrace / SECURE AI is an AI security solution that brings every AI interaction across an organization into a single view, helping teams understand intent, assess risk, protect sensitive data, and support policy alignment. It monitors prompts, sessions, and responses in real time across enterprise GenAI tools such as Microsoft Copilot and ChatGPT Enterprise, low-code environments including Microsoft Copilot Studio, high-code platforms such as Amazon Bedrock and SageMaker, SaaS applications, and SASE. Behavioral analytics distinguish normal, business-aligned activity from significant or risky deviations, detecting conversational prompt attacks, malicious chaining, and unsafe actions without relying only on historical attack patterns. Darktrace learns directly from the environment it protects, allowing it to identify novel and AI-related threats on first encounter. -
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Arms Cyber
Arms Cyber
Arms Cyber is a stealth-driven endpoint security platform for the AI era, built to protect critical data from human and AI-driven attacks through one lightweight sensor. Instead of relying only on detection after exposure, Raven conceals sensitive data, blocks threats as they execute, and keeps recovery options available directly at the endpoint without reboots, downtime, or replacing existing security tools. It combines three core modules. AI Ransomware Protection stops AI-accelerated and conventional ransomware at execution time, limiting the files an attack can reach. It integrates with backup infrastructure to hide restoration points, plant decoys, and stop attempts to disable, delete, or unhook backups so clean recovery remains possible. It closes the AI-at-the-endpoint visibility gap by monitoring every AI tool, model, and service running on endpoints and enforcing organizational policy before sensitive data reaches unapproved systems. -
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GPT‑5.6‑Cyber
OpenAI
GPT-5.6-Cyber is OpenAI’s most advanced purpose-trained cybersecurity model for approved defenders conducting authorized vulnerability research, exploit validation, and security testing. Built on GPT-5.6 Sol, it is trained to improve performance on specialized cybersecurity tasks such as finding zero-day vulnerabilities, developing exploit chains, testing authentication bypasses, privilege escalation, and advanced security research. The model is designed to reduce unnecessary refusals on legitimate higher-risk, dual-use cybersecurity work while helping trusted defenders conduct real-world security activities. GPT-5.6-Cyber improves performance on exploit development workflows and can generate proof-of-concept exploits alongside technical findings, assess the severity and impact of novel vulnerabilities, and support vulnerability discovery and report writing. It is particularly suited to sustained reasoning across large and unfamiliar codebases. -
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Onyx Security
Onyx Security
Onyx is a secure AI control plane for discovering, protecting, governing, optimizing, and measuring AI agents and models across the enterprise. It gives security, governance, and AI teams visibility into sanctioned and shadow AI across SaaS, cloud, endpoints, and code, including prompts, responses, and agent actions. AI Security helps strengthen posture, identify vulnerabilities, and enforce real-time safeguards against threats and misuse, while AI Governance supports security standards and regulatory requirements with opt-in coverage and policy controls defined in natural language. AI Orchestration reduces friction when setting up agents and MCPs and helps optimize for cost, accuracy, and latency. AI ROI measures adoption, sets goals, and tracks outcomes across departments. The Onyx Guardian Agent acts as a supervisory AI that continuously identifies risks and remediates issues across the platform, helping organizations manage large numbers of agents at scale. -
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Rilevera
Rilevera
Rilevera is an AI Detection Engineer that continuously validates, improves, and manages detections across SIEM, EDR, and data platforms so security teams can focus on stopping real threats instead of chasing broken rules. It validates detection logic, telemetry dependencies, and schema integrity across platforms, immediately identifying when a rule breaks or required data disappears. AI-driven detection optimization analyzes performance data, false-positive trends, overlap, and logic quality to recommend improvements and push validated updates back into execution platforms. Coverage and Gap Analysis maps detections and telemetry to MITRE techniques and threat actors, helping teams identify blind spots and prioritize new rule development. Structured workflows for design, validation, peer review, and controlled deployment bring discipline and speed to the detection lifecycle. Rilevera continuously analyzes detection performance to improve signal quality, reduce alert fatigue, etc. -
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Pi
Pi Security
Pi is an agentic product security platform that builds institutional security memory so organizations can find, fix, and prevent recurring vulnerabilities without slowing development. It continuously ingests codebases, past incidents, pentest reports, tickets, and other security history into a living inventory, giving the system context about how the organization builds and secures software. When a vulnerability is found, Pi traces it to its architectural root cause, searches for variants across the codebase, and helps close the entire class of issue rather than treating each finding independently. Remediation is generated in the context of the organization’s languages, architecture, and conventions, then delivered directly into developer workflows. What the system learns becomes prevention guardrails that can be applied in IDEs and pull requests during design and coding, blocking known insecure patterns before they reach production. -
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Exabeam
Exabeam
Exabeam helps security teams outsmart the odds by adding intelligence to their existing security tools – including SIEMs, XDRs, cloud data lakes, and hundreds of other business and security products. Out-of-the-box use case coverage repeatedly delivers successful outcomes. Behavioral analytics allows security teams to detect compromised and malicious users that were previously difficult, or impossible, to find. New-Scale Fusion combines New-Scale SIEM and New-Scale Analytics to form the cloud-native New-Scale Security Operations Platform. Fusion applies AI and automation to security operations workflows to deliver the industry’s premier platform for threat detection, investigation and response (TDIR). -
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Deep Instinct
Deep Instinct
Deep Instinct is the first and only company to apply end-to-end deep learning to cybersecurity. Unlike detection and response-based solutions, which wait for the attack before reacting, Deep Instinct’s solution works preemptively. By taking a preventative approach, files and vectors are automatically analyzed prior to execution, keeping customers protected in zero time. This is critical in a threat landscape, where real time is too late. With the aim of eradicating cyber threats from the enterprise, Deep Instinct protects against the most evasive known and unknown cyberattacks with unmatched accuracy, achieving highest detection rates and minimal false positives in tests regularly performed by third parties. Providing protection across endpoints, networks, servers, and mobile devices, the lightweight solution can be applied to most OSs and protects against both file-based and fileless attacks. -
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CUJO AI
CUJO AI
CUJO AI is the global leader in the development and application of artificial intelligence to improve the security, control and privacy of connected devices in homes and businesses. CUJO AI brings to fixed network, mobile and public Wi-Fi operators around the world a complete portfolio of products to provide end users with a seamlessly integrated suite of Digital Life Protection services while improving their own network monitoring, intelligence and protection capabilities. Leveraging artificial intelligence and advanced data access technologies, unprecedented visibility and actionable insight are provided for end-user networks by inventorying connected devices, analyzing applications and services in use, and detecting security and privacy threats. Artificial intelligence and real-time network data combine, working together to create smarter and safer environments for people and all their connected devices.
