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57 Listings in IT Ops AI Available
What is Ethiack? Ethiack is a cybersecurity company offering continuous, AI-driven penetration testing through its Hackian agentic AI engine. It maps attack surfaces, finds and tests vulnerabilities and validates proof of exploit. Key capabilities of Ethiack Attack surface mapping: External, internal and third-party assets. Autonomous testing: Triggered by code or infrastructure changes. Exploit validation: Proof of exploit for confirmed risks. Prioritized findings: With remediation guidance. Compliance reporting: NIS2, DORA, SOC2, ISO27001 and PCI. How Ethiack works The platform follows See, Test and Act. It maps assets, runs continuous autonomous tests when code or infrastructure changes and delivers prioritized findings. The vendor claims over 80% accuracy and 30x faster than manual pentesting. Who uses Ethiack? Security teams replacing annual pentests. Customers named include ANA Aeroportos (650% ROI), Bluepharma and Universidade do Porto. Ethiack pricing Ethiack offers a 30-day free trial and on-demand demos. Paid pricing is not published. Ethiack alternatives XBOW is an autonomous offensive security company, Traversal automates incident investigation, and Lasso Security focuses on LLM security. Ethiack focuses on continuous pentesting.
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What is Microsoft Security Copilot? Microsoft Security Copilot is a generative AI service that helps security and IT teams protect, detect and respond to threats using agentic AI. It works across Microsoft security products and partner solutions. Key capabilities of Microsoft Security Copilot Embedded agents: Ready-to-use agents in Microsoft Defender, Entra, Intune and Purview Phishing Triage Agent: Microsoft says analysts identified malicious emails up to 550% faster Conditional Access Optimization Agent: Found 204% more missing zero trust policies per Microsoft Custom and partner agents: Supports third-party and custom-built agents Multi-product integration: Microsoft Sentinel, Defender XDR and Defender for Cloud SCU capacity model: Security Compute Units meter workload execution How Microsoft Security Copilot works Teams use Security Copilot inside Microsoft security tools or standalone. Agents run tasks such as phishing triage and policy optimization, drawing on connected products like Sentinel and Defender XDR. Capacity is measured in Security Compute Units. Who uses Microsoft Security Copilot? Security operations, identity and IT administrators in organizations on the Microsoft security stack. Microsoft Security Copilot pricing Security Copilot is included in Microsoft 365 E5 and E7 at 400 SCUs per month per 1,000 user licenses, with a phased rollout. A standalone per-SCU option exists, and third-party sources report about $4 per SCU per hour. Microsoft Security Copilot alternatives Alternatives include CrowdStrike Charlotte AI for endpoint security, SentinelOne Purple AI for threat hunting and Moveworks for IT support.
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What is Terra Security? Terra Security is an agentic offensive security platform that automates continuous penetration testing. AI agents test web applications, external and internal networks and AI systems while human operators oversee critical decisions. Key capabilities of Terra Security Web application testing: Handles adaptive authentication and business logic. External network assessment: Tests exposed infrastructure. Internal network pentesting: Covers internal attack surface. AI red teaming: Targets LLMs, copilots and AI agents. TORCH: Terra Offensive Research Collaboration Hub for agent-human work. Ambient and Copilot agents: Automate testing steps. Signed reports: Audit-ready reports signed by certified pentesters. How Terra Security works Agents test continuously and align validation with code changes instead of a single yearly test. A Human-on-the-Loop workflow keeps people in control at critical decision points. Terra says it moves 4 to 6 week testing to 2 to 4 hours. Who uses Terra Security? Security teams that need frequent pentesting evidence for compliance and engineering teams shipping often. Terra Security pricing Terra Security does not publish pricing or a free trial. Terra Security alternatives Lasso Security focuses on LLM security and Traversal on AI site reliability. Terra Security is built for offensive testing and pentest reporting.
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What is Conifers.ai? Conifers.ai is an AI SOC AI agent offering an AI SOC platform that investigates and resolves complex security incidents with institutional knowledge. Conifers.ai helps SOC teams and MSSPs automate AI SOC work and get results faster. Key capabilities of Conifers.ai Incident investigation Alert enrichment Case summaries MSSP support Autonomous alert triage Investigation reports How Conifers.ai works Conifers.ai takes logs and alerts as input and produces investigations and reports. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Splunk, Microsoft Sentinel, CrowdStrike and Okta, so the agent works inside existing workflows. Who uses Conifers.ai? Conifers.ai is built for SOC teams and MSSPs. It suits teams that want incident investigation and alert enrichment without adding headcount, while keeping people in control of review and final decisions. Conifers.ai vs Prophet Security Conifers.ai is often compared with Prophet Security. Conifers.ai stands out for incident investigation and case summaries. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Moveworks? Moveworks is an employee support AI agent offering an agentic AI assistant for employee support across IT, HR and business systems (part of ServiceNow). Founded in 2016 and based in Mountain View, California, USA, Moveworks helps large enterprises automate employee support work and get results faster. Key capabilities of Moveworks Employee AI assistant Enterprise search Agent builder IT and HR automation Human handoff Resolution analytics How Moveworks works Moveworks takes text as input and produces text and actions. It is powered by Multiple LLMs (managed) models, with the vendor managing prompts, models and updates. It connects to tools such as Zendesk, Salesforce Service Cloud, Slack and Shopify, so the agent works inside existing workflows. Who uses Moveworks? Moveworks is built for large enterprises. It suits teams that want employee AI assistant and enterprise search without adding headcount, while keeping people in control of review and final decisions. Moveworks vs Aisera Moveworks is often compared with Aisera. Moveworks stands out for employee AI assistant and agent builder. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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ServiceNow Now Assist is the generative AI capability embedded across the ServiceNow platform, adding summarization, conversational assistance, and content generation directly into IT, customer, HR, and developer workflows. What Now Assist does Summarize: auto-summarize incidents, cases, and chats to speed resolution. Assist: Virtual Agent chat and in-flow guidance for agents and employees. Generate: create knowledge articles and code (App Engine) from prompts. Automate: agentic AI and text-to-workflow across ITSM, CSM, and HR. Who it's for Enterprises using ServiceNow that want to embed generative and agentic AI into their existing workflows.
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What is Keycard? Keycard is an agent identity AI agent offering an identity and access platform that issues and governs scoped credentials for AI agents and MCP tools. Keycard helps developers and security teams automate agent identity work and get results faster. Key capabilities of Keycard Agent identity Dynamic credentials Access policies Audit trails Scoped agent credentials Access auditing How Keycard works Keycard takes text as input and produces credentials and policies. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Okta, MCP servers, OAuth providers and Claude, so the agent works inside existing workflows. Who uses Keycard? Keycard is built for developers and security teams. It suits teams that want agent identity and dynamic credentials without adding headcount, while keeping people in control of review and final decisions. Keycard vs Descope Keycard is often compared with Descope. Keycard stands out for agent identity and access policies. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Doppel? Doppel is an AI-native social engineering defense platform. It finds cloned domains, fake profiles and fraudulent marketplace listings that impersonate a brand or its executives, then dismantles the attacker infrastructure through takedowns, training and simulation. Key capabilities of Doppel Impersonation detection: Finds cloned domains, fake profiles and fake listings within minutes of creation. Automated takedowns: Direct integrations with hosts and platforms speed removal. Cross-channel monitoring: Covers web, social, app and dark web. Brand protection: Dedicated product for brand abuse. Training and simulation: Builds employee resilience to social engineering. Audit evidence: Documentation for SOC 2, TPN, MPA, GDPR and CCPA audits. How Doppel works The engine correlates and prioritizes threats across channels, then triggers takedown requests through direct integrations with hosting providers and platforms. Doppel reports a median takedown time under 10 hours. Security and brand teams use the platform to review cases and evidence. Who uses Doppel? Security, fraud and brand protection teams, with industry pages for financial services, media, technology and sports organizations. ARK Invest is a named customer example. Doppel pricing Doppel does not publish pricing on its website. Plans are scoped through the vendor. Doppel alternatives ZeroFox covers external threat and digital risk protection, Netcraft offers takedown and brand protection services, and Proofpoint covers email and brand impersonation. Doppel focuses on AI-driven detection and takedown across channels.
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What is Noma Security? Noma Security is an AI and agent security AI agent offering a security platform for AI and agents covering inventory, posture, red teaming and runtime protection. Founded in 2023 and based in Tel Aviv, Israel, Noma Security helps enterprise security teams automate AI and agent security work and get results faster. Key capabilities of Noma Security AI inventory and AIBOM Agent security posture AI red teaming Runtime protection Policy enforcement AI usage visibility How Noma Security works Noma Security takes AI assets and code as input and produces insights and alerts. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Microsoft 365 Copilot, Salesforce, Okta and Slack, so the agent works inside existing workflows. Who uses Noma Security? Noma Security is built for enterprise security teams. It suits teams that want AI inventory and AIBOM and agent security posture without adding headcount, while keeping people in control of review and final decisions. Noma Security vs Protect AI Noma Security is often compared with Protect AI. Noma Security stands out for AI inventory and AIBOM and AI red teaming. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is B-Yond? B-Yond is a telecom network AI AI agent offering AI-driven automation for telecom network testing, troubleshooting and operations. B-Yond helps mobile network operators automate telecom network AI work and get results faster. Key capabilities of B-Yond Automated network troubleshooting 5G testing Root cause analysis Network automation Predictive risk models Operational dashboards How B-Yond works B-Yond takes network data as input and produces insights and actions. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as SCADA, GIS (Esri), SAP and Snowflake, so the agent works inside existing workflows. Who uses B-Yond? B-Yond is built for mobile network operators. It suits teams that want automated network troubleshooting and 5G testing without adding headcount, while keeping people in control of review and final decisions. B-Yond vs Subex B-Yond is often compared with Subex. B-Yond stands out for automated network troubleshooting and root cause analysis. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Straiker? Straiker is an enterprise security platform for AI agents that helps organizations discover, test and defend autonomous AI systems. It positions itself as The Agentic AI Security Company. Key capabilities of Straiker Discover AI: Maps AI agents, MCP servers and workflows with misconfiguration detection Ascend AI: Adversarial testing for prompt injection, goal hijacking and tool misuse Defend AI: Runtime blocking of data exfiltration, memory poisoning and identity abuse STAR Labs research: Threat research on agent attacks Policy enforcement: Controls on agent behavior Continuous monitoring: Ongoing inventory How Straiker works Discover inventories agents and MCP servers, Ascend attacks them to find weaknesses before attackers do, and Defend watches runtime activity to detect and block threats. Who uses Straiker? Enterprises; the vendor names DirectTV, Comcast, Deloitte and Automation Anywhere as customers. Straiker pricing Straiker does not publish prices. Straiker alternatives Alternatives include Knostic, Harmonic Security and WitnessAI. Straiker emphasizes agent red teaming and runtime defense.
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What is Intezer? Intezer is an AI-powered security operations center (SOC) platform that automates alert triage, investigation and response. The vendor says it investigates 100% of alerts at forensic depth, including low-severity signals that human teams often skip. Key capabilities of Intezer Alert triage: Multiple AI models give consistent verdicts on incoming alerts Forensic investigation: Endpoint analysis, memory scanning and reverse engineering False positive resolution: The vendor says 98% are resolved in under one minute Automated response: Disable users or isolate devices, or route plans for manual review Detection engineering: Investigation results tune rules and track MITRE ATT&CK coverage Analyst feedback: Users can challenge verdicts, which tunes triage logic How Intezer works Alerts arrive from connected security tools. Intezer applies forensic techniques such as memory scanning and reverse engineering together with built-in threat intelligence and several AI models, then returns a verdict and a remediation plan. Actions can run automatically or wait for approval, and feedback from analysts tunes both triage and detection rules to the environment. Who uses Intezer? Intezer is aimed at enterprise security teams that want to close MDR gaps and reduce alert fatigue, and at managed security service providers. Its site cites 150+ customers including Salesforce, MGM Resorts, NVIDIA and Equifax. Intezer pricing Intezer uses endpoint-based pricing with no volume fees, so cost scales with the number of endpoints rather than alert counts. It does not publish a rate card, so you need to contact the vendor for a quote. Intezer alternatives Alternatives include 7AI and Radiant Security, which also automate SOC investigation with AI, and Qevlar AI, which focuses on alert investigation. Intezer emphasizes forensic depth and endpoint-based rather than volume-based pricing.
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IT Ops AI (AIOps) applies machine learning to IT operations, detecting and diagnosing incidents, reducing alert noise, automating remediation, and predicting issues, to keep systems reliable and teams focused. This guide explains what AIOps is, how it works, what matters, and how to choose one.
IT Ops AI (AIOps) applies machine learning to IT operations, detecting and diagnosing incidents, reducing alert noise, automating remediation, and predicting issues, to keep systems reliable and teams focused. This guide explains what AIOps is, how it works, what matters, and how to choose one.
AIOps (AI for IT operations) uses machine learning and analytics on IT telemetry, metrics, logs, traces, and events, to detect anomalies, correlate and reduce alerts, diagnose root causes, and automate or recommend remediation.
It spans AIOps platforms, observability tools with AI/ML features, and AI assistants for IT service management (ITSM) and incident response.
The category exists because modern systems generate overwhelming telemetry and alerts. Buyers weigh signal quality (noise reduction and accurate root cause), integration with their observability and ITSM stack, automation safety, and how much it actually reduces incidents and toil.
AIOps ingests telemetry from across the stack, learns normal behavior, detects anomalies, correlates related alerts into incidents, surfaces probable root causes, and triggers or recommends remediation, reducing noise and speeding resolution.
Platforms combine data ingestion from monitoring/observability and ITSM tools, anomaly detection and correlation models, root-cause analysis, and automation/runbooks.
IT and SRE teams connect data sources, tune detection and automation, and use AIOps to triage and resolve incidents faster, with humans approving or overseeing automated actions.
Learn normal behavior and detect issues across metrics, logs, and traces early.
Group related alerts into incidents to cut noise and alert fatigue.
Surface probable root causes to speed diagnosis and resolution.
Trigger runbooks and automated fixes, with approvals and guardrails.
Forecast capacity issues and potential failures before they occur.
Integrate with monitoring, observability, and ITSM tools for end-to-end workflow.
Correlation and noise reduction cut alert fatigue so teams focus on real issues.
Root-cause analysis and automation speed incident resolution.
Early anomaly detection and prediction prevent incidents before they escalate.
Automating routine remediation frees engineers from repetitive work.
Manage complex, high-telemetry systems that overwhelm manual ops.
| Type | Best for | Ideal size | Pros | Limitations |
|---|---|---|---|---|
| AIOps platforms | Correlation, RCA, automation | Mid-market to enterprise | End-to-end ops intelligence | Integration and tuning |
| Observability + AI | AI features in monitoring tools | Any | Unified with telemetry | Scope tied to that tool |
| Incident response AI | Triage and on-call assistance | Any | Faster incident handling | Needs good data |
| ITSM AI | Service desk and ticket automation | Any | Automates IT service work | Different focus than ops |
Technology: Technology IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Healthcare: Healthcare IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Financial Services: Financial Services IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Retail & E-commerce: Retail & E-commerce IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Education: Education IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Professional Services: Professional Services IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Manufacturing: Manufacturing IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Media: Media IT and SRE teams use AIOps to reduce alert noise, detect and diagnose incidents faster, automate remediation, and predict issues, keeping systems reliable as complexity grows.
Test noise reduction and root-cause accuracy on your environment, this is the core value.
Confirm integration with your monitoring, observability, and ITSM tools.
Review guardrails, approvals, and rollback for automated remediation.
Verify it handles your telemetry volume and complexity.
Assess how much tuning and learning time before it delivers real noise reduction.
Understand data-volume, node, or seat pricing and how it scales.
Generative AI is adding conversational incident investigation and on-call copilots.
Autonomous remediation is expanding, with humans overseeing rather than executing.
Predictive and preventive ops are reducing incidents before they happen.
Buyers should prioritize signal quality, stack integration, automation safety, and measurable MTTR and noise reduction.
AIOps (AI for IT operations) applies machine learning and analytics to IT telemetry, metrics, logs, traces, and events, to detect anomalies, correlate and reduce alerts, diagnose root causes, and automate or recommend remediation. It spans AIOps platforms, observability tools with AI features, and AI assistants for incident response and IT service management, helping teams keep complex systems reliable.
It correlates related alerts from across the stack into single incidents and filters out noise, so instead of hundreds of disconnected alerts, teams see a few meaningful incidents. This cuts alert fatigue and helps engineers focus on real problems. Noise reduction and accurate correlation are among the most valuable AIOps capabilities, test them on your data.
Yes, AIOps can trigger automated runbooks and remediation for known issues, though safe deployment uses guardrails, approvals, and rollback so automation doesn't cause incidents. Many teams start with recommended actions and human approval, then expand autonomous remediation as confidence grows. Review automation safety controls carefully.
It can, by detecting anomalies early, speeding root-cause analysis to lower mean time to resolution (MTTR), and predicting issues before they escalate. Impact depends on signal quality and integration. Measure noise reduction, MTTR, and incident volume against a baseline to verify real improvement rather than relying on claims.
AIOps ingests data from your monitoring, observability, logging, and ITSM tools and pushes incidents and actions back into them. Integration breadth and depth vary and are essential to value, since AIOps sits on top of your telemetry. Confirm support for your specific observability and ITSM stack before adopting.
AIOps needs time to learn your environment's normal behavior before anomaly detection and correlation become accurate, and integration and tuning take effort. Time to value varies by tool and complexity. Ask vendors about typical ramp time and what tuning is required, and pilot to confirm it delivers noise reduction in your environment.
Telemetry can contain sensitive operational and sometimes personal data, and volumes are large. Confirm encryption, access controls, data residency, retention, and whether your data trains shared models. Review security and cost (often tied to data volume) carefully given the scale of telemetry involved.
Prioritize signal quality (noise reduction and root-cause accuracy) on your environment, integration with your monitoring and ITSM stack, automation safety controls, scalability to your telemetry, time to value, and pricing. Pilot in a real environment and measure noise reduction and MTTR before rolling out broadly.
