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57 Listings in IT Ops AI Available
What is Cleric? Cleric is a SRE AI agent offering an AI site reliability engineer that investigates alerts and finds root causes autonomously. Founded in 2023 and based in San Francisco, California, USA, Cleric helps SRE and platform teams automate SRE work and get results faster. Key capabilities of Cleric Autonomous alert investigation Root cause findings Observability integrations Learning from past incidents Root cause analysis Runbook automation How Cleric works Cleric takes alerts, logs and metrics as input and produces text and insights. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Slack, PagerDuty, ServiceNow and Datadog, so the agent works inside existing workflows. Who uses Cleric? Cleric is built for SRE and platform teams. It suits teams that want autonomous alert investigation and root cause findings without adding headcount, while keeping people in control of review and final decisions. Cleric vs Resolve.ai Cleric is often compared with Resolve.ai. Cleric stands out for autonomous alert investigation and observability integrations. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is New Relic AI? New Relic AI is an observability assistant AI agent offering New Relic AI assistant and agents for querying telemetry and troubleshooting issues. Founded in 2008 and based in San Francisco, California, USA, New Relic AI helps engineering teams using New Relic automate observability assistant work and get results faster. Key capabilities of New Relic AI Natural-language NRQL Error analysis Agentic integrations Observability insights Root cause analysis Runbook automation How New Relic AI works New Relic AI takes text and telemetry as input and produces text and insights. It is powered by Multiple LLMs (managed) models, with the vendor managing prompts, models and updates. It connects to tools such as Slack, PagerDuty, ServiceNow and Datadog, so the agent works inside existing workflows. Who uses New Relic AI? New Relic AI is built for engineering teams using New Relic. It suits teams that want natural-language NRQL and error analysis without adding headcount, while keeping people in control of review and final decisions. New Relic AI vs Datadog Bits AI New Relic AI is often compared with Datadog Bits AI. New Relic AI stands out for natural-language NRQL and agentic integrations. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Aisera? Aisera is an enterprise agentic AI platform that provides AI agents and assistants for IT, HR, finance, procurement, customer service, facilities, sales and legal. It automates multi-step requests across the systems a company already uses. Key capabilities of Aisera Agent Composer: Build custom AI agents using natural language. Aisera Assistant: A personal assistant that completes employee and customer tasks. Agent Assist: Supports human agents with suggestions and summaries. Hyperflows: Orchestrates complex multi-step workflows across systems. Aisera Unify: Integration backbone supporting A2A, MCP and AGNTCY standards. How Aisera works Aisera connects to ticketing, HR, CRM and messaging systems through its connector library of 200+ integrations. Users ask for help in chat, and agents resolve requests or run workflows such as onboarding or password resets, handing off to people when needed. Admins build or adapt agents with Agent Composer. Who uses Aisera? IT service desks, HR teams, finance and customer-support organizations in banking, healthcare, retail, telecom, manufacturing and government use it. It is sold to mid-size and large enterprises through sales. Aisera pricing Aisera does not publish prices. Packages such as Pro and Enterprise are quoted through the vendor's sales team, and pricing depends on use cases and volume. Aisera alternatives Moveworks focuses on employee support across IT and HR, Yellow.ai targets customer and employee conversational automation, and Kustomer is a customer-service CRM with AI. Aisera spans IT, HR, finance and CX in one platform.
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What is Workativ? Workativ is an IT support AI agent offering a conversational AI platform that automates employee IT and HR support in Slack and Teams. Workativ helps IT and HR teams automate IT support work and get results faster. Key capabilities of Workativ AI IT support Password resets and access Knowledge answers Workflow automation Ticket triage and routing Automated resolutions How Workativ works Workativ takes text as input and produces text 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 ConnectWise, Autotask, HaloPSA and ServiceNow, so the agent works inside existing workflows. Who uses Workativ? Workativ is built for IT and HR teams. It suits teams that want AI IT support and password resets and access without adding headcount, while keeping people in control of review and final decisions. Workativ vs Moveworks Workativ is often compared with Moveworks. Workativ stands out for AI IT support and knowledge answers. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Selector AI? Selector AI is an intelligent network operations platform that uses AI agents to detect and resolve infrastructure issues. Its flagship product is Selector Foundry, a suite of agents that investigate incidents, act within safety guardrails and verify fixes. Key capabilities of Selector AI Selector Foundry: Specialized AI agents for incidents Rosetta: Conversational interface for network state Correlation and RCA: Automated root cause analysis Digital Twin: Network simulation Selector MCP: Integration framework Alert correlation: Combines alerts into single incidents How Selector AI works Selector aggregates signals from existing monitoring tools and infrastructure, normalizes them into a unified model, correlates alerts into incidents, identifies probable root causes and recommends or takes fixes within guardrails. Who uses Selector AI? Network and infrastructure teams. Customers named by the vendor include NBC, Bell, Lumen and SingTel. Selector AI pricing Selector does not publish prices. Selector AI alternatives Alternatives include Dropzone AI for security operations, Aisera for IT service and Traversal for root cause analysis. Selector is network-focused.
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What is Transposit? Transposit is an incident management AI agent offering AI-driven incident management with human-in-the-loop automation and runbooks. Founded in 2016 and based in San Francisco, California, USA, Transposit helps DevOps and SRE teams automate incident management work and get results faster. Key capabilities of Transposit Incident workflows Runbook automation AI incident summaries Slack-first response Root cause analysis How Transposit works Transposit takes alerts and text as input and produces actions and text. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Slack, PagerDuty, ServiceNow and Datadog, so the agent works inside existing workflows. Who uses Transposit? Transposit is built for DevOps and SRE teams. It suits teams that want incident workflows and runbook automation without adding headcount, while keeping people in control of review and final decisions. Transposit vs PagerDuty Transposit is often compared with PagerDuty. Transposit stands out for incident workflows and AI incident summaries. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Lasso Security? Lasso Security is an enterprise AI security platform that protects AI agents and applications through a loop of discovery, assessment and runtime protection. Key capabilities of Lasso Security Discovery and inventory: Inventories agents and apps, mapping models, prompts, tools and guardrails. AI security posture: Analyzes exposure, supply chain risk and model vulnerabilities against NIST and OWASP. Automated red teaming: Tests agents against 3,000+ attack patterns, including multi-turn attacks. Runtime enforcement: Enforces policies at proxy, API and gateway layers. Threat detection: Behavioral intent analysis across MITRE and OWASP categories. How Lasso Security works Lasso discovers AI systems across the enterprise, assesses risk through posture analysis and red teaming, enforces policy at runtime and detects anomalies with behavioral intent analysis. The vendor claims 98.6% detection accuracy, decisions under 50ms and three patents pending, figures that should be tested in a pilot. Who uses Lasso Security? Enterprise security teams in finance, healthcare and the public sector. Named customers include the US Department of Homeland Security, Optibus, Fiverr, Delek US and Compugen. Lasso Security pricing No pricing is published on the homepage. Contact the vendor for a quote. Lasso Security alternatives Related security automation vendors include Simbian, Command Zero, Conifers.ai and Serval, which apply AI to SOC workflows rather than securing AI applications.
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What is SentinelOne Purple AI? SentinelOne Purple AI is an agentic AI security analyst within SentinelOne's Singularity platform. It lets analysts search and investigate security telemetry in plain English instead of query languages. Purple AI became generally available in September 2025, per SentinelOne partner coverage. Key capabilities of SentinelOne Purple AI Natural language hunting: ask questions in English across security telemetry Investigation notebooks: store hunts, pivots and findings as reusable artifacts Hunting quickstarts: expert-curated hunting workflows Guided investigations: contextual next-step suggestions Post-investigation summaries: generates summaries and communication templates Singularity integration: works with SentinelOne platform data How SentinelOne Purple AI works An analyst asks a question such as suspicious PowerShell activity in the last 24 hours, and Purple AI queries the data and returns a structured answer with recommended next steps. Findings are saved in notebooks that teams can review, share and audit. Who uses SentinelOne Purple AI? SOC analysts and threat hunters on SentinelOne use Purple AI to cut time to investigate. SentinelOne Purple AI pricing SentinelOne does not publish Purple AI pricing. Contact the vendor or a reseller for a quote. SentinelOne Purple AI alternatives Purple AI is compared with Microsoft Security Copilot and CrowdStrike Charlotte AI. Both are AI assistants tied to their vendors' security platforms.
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What is Command Zero? Command Zero is a security investigation AI agent offering an AI-assisted investigation platform that guides analysts through expert-built cyber investigations. Command Zero helps SOC analysts and incident responders automate security investigation work and get results faster. Key capabilities of Command Zero Guided investigations Identity and cloud queries AI summaries Investigation playbooks Autonomous alert triage Investigation reports How Command Zero works Command Zero takes logs and text 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 Command Zero? Command Zero is built for SOC analysts and incident responders. It suits teams that want guided investigations and identity and cloud queries without adding headcount, while keeping people in control of review and final decisions. Command Zero vs Intezer Command Zero is often compared with Intezer. Command Zero stands out for guided investigations and AI summaries. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Knostic? Knostic is an enterprise security company that discovers and secures AI agents and coding assistants, along with supply chain risks such as MCP servers, skills, IDE extensions and rules. It is based in Herndon, Virginia. Key capabilities of Knostic Kirin AI Coding Safety: Integrated security for agents, coding assistants and MCP servers Shadow AI Spotlight: Visibility into unsanctioned AI tool use OpenAnt: LLM-powered vulnerability discovery for CI/CD with two-stage verification OpenClaw: Protects against secret leaks, PII exposure and destructive commands Supply chain inventory: Tracks extensions and MCP servers LLM oversharing tester: Free tool to test oversharing How Knostic works Knostic discovers AI agents and coding assistants across an environment, inventories their MCP servers, skills and extensions, and applies detection and response and posture monitoring. OpenAnt uses a two-stage LLM process to verify vulnerabilities in pipelines. Who uses Knostic? Security teams, developers, compliance officers and security leadership. Backers include Seedcamp and DNX Venture. Knostic pricing Knostic does not publish prices. Free tools include OpenAnt and an LLM oversharing tester, and enterprise demos are available on request. Knostic alternatives Alternatives include Zenity and Harmonic Security for AI security, and Straiker for agent protection. Knostic emphasizes coding assistants and MCP supply chain.
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What is Console? Console is an IT support automation AI agent offering an AI agent that resolves IT requests like access, onboarding and troubleshooting in Slack. Founded in 2023 and based in San Francisco, California, USA, Console helps IT teams automate IT support automation work and get results faster. Key capabilities of Console Access provisioning Onboarding automation Troubleshooting Policy-based approvals Root cause analysis Approval workflows How Console works Console takes text as input and produces text 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 Slack, Microsoft Teams, Jira and ServiceNow, so the agent works inside existing workflows. Who uses Console? Console is built for IT teams. It suits teams that want access provisioning and onboarding automation without adding headcount, while keeping people in control of review and final decisions. Console vs Serval Console is often compared with Serval. Console stands out for access provisioning and troubleshooting. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Qevlar AI? Qevlar AI is an autonomous Security Operations Center platform that investigates alerts, hunts threats and drives response while analysts stay in control. It connects to 40+ security tools through APIs and is live in production at 1,500+ organizations, including enterprises and MSSPs. It was named MSP Today Product of the Year 2025. Key capabilities of Qevlar AI Alert investigation: investigates across the security stack and builds unified incident narratives Blast radius mapping: shows scope and drives containment actions Continuous threat hunting: autonomous hunts for emerging threats and anomalies Institutional knowledge: adapts to your environment for consistent decisions SOC and vulnerability integration: elevates confirmed exploitation in remediation queues 40+ integrations: CrowdStrike, Microsoft Sentinel, Splunk, Okta and more How Qevlar AI works Qevlar enriches data, pivots across tools, correlates alerts and adapts its approach as it learns, unlike SOAR platforms that run static playbooks. Core logic uses a structured graph orchestrator, and language models handle bounded tasks like summarization to limit hallucinations. Who uses Qevlar AI? In-house SOC teams and MSSPs use Qevlar to scale investigation without adding analysts. Qevlar AI pricing Qevlar AI does not publish pricing. Contact the vendor for a quote. Qevlar AI alternatives Qevlar AI is compared with Intezer, Radiant Security and Resolve.ai. Intezer analyzes malware and alerts, and Radiant Security also automates SOC triage.
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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.