Best Artificial Intelligence Software for Splunk Cloud Platform - Page 2

Compare the Top Artificial Intelligence Software that integrates with Splunk Cloud Platform as of December 2025 - Page 2

This a list of Artificial Intelligence software that integrates with Splunk Cloud Platform. Use the filters on the left to add additional filters for products that have integrations with Splunk Cloud Platform. View the products that work with Splunk Cloud Platform in the table below.

  • 1
    NVIDIA DGX Cloud Serverless Inference
    NVIDIA DGX Cloud Serverless Inference is a high-performance, serverless AI inference solution that accelerates AI innovation with auto-scaling, cost-efficient GPU utilization, multi-cloud flexibility, and seamless scalability. With NVIDIA DGX Cloud Serverless Inference, you can scale down to zero instances during periods of inactivity to optimize resource utilization and reduce costs. There's no extra cost for cold-boot start times, and the system is optimized to minimize them. NVIDIA DGX Cloud Serverless Inference is powered by NVIDIA Cloud Functions (NVCF), which offers robust observability features. It allows you to integrate your preferred monitoring tools, such as Splunk, for comprehensive insights into your AI workloads. NVCF offers flexible deployment options for NIM microservices while allowing you to bring your own containers, models, and Helm charts.
  • 2
    100x

    100x

    100x

    100X is an AI-powered platform designed to troubleshoot complex software systems by autonomously analyzing tickets, alerts, logs, metrics, traces, code, and knowledge to pinpoint problems and remediate issues. It operates through a multi-step process: connecting to your environment to build a comprehensive knowledge graph, automatically investigating every incoming alert or support ticket, dynamically querying telemetry and connecting signals across systems, isolating specific system issues with supporting evidence, suggesting proven fixes with relevant context, and learning from every resolution by capturing commands, fixes, and failure patterns discovered by your team. 100X integrates with tools like Datadog, Grafana, LaunchDarkly, Jenkins, Kafka, Redis, and Salesforce, and can be deployed within your cloud environment, ensuring data is accessed, processed, and stored entirely within your cloud boundary.
  • 3
    Deductive AI

    Deductive AI

    Deductive AI

    Deductive AI is a cutting-edge platform that redefines how organizations handle complex system failures. By connecting your entire codebase with telemetry data, encompassing metrics, events, logs, and traces, Deductive AI empowers teams to pinpoint the root cause of issues with unprecedented precision and speed. It streamlines the process of debugging, significantly reducing downtime and improving overall system reliability. Deductive AI integrates with your codebase and observability tools, creating a unified knowledge graph powered by a code-aware reasoning engine to diagnose root causes like an expert engineer. It builds a knowledge graph with millions of nodes in seconds, uncovering deep relationships between codebase and telemetry data. It orchestrates hundreds of specialized AI agents to search, discover, and analyze breadcrumbs of root cause spread across all connected sources.
  • 4
    Synergy

    Synergy

    Unframe

    Synergy is an AI-native command center for enterprise IT operations that unifies siloed monitoring, ticketing, logging, and documentation into a single pane of glass. It continuously correlates signals across tools like Splunk, New Relic, Jira, ServiceNow, and Confluence to turn alert storms into clear, prioritized insights. Synergy’s Smart Incident Workflows automate routine tasks, suggest next steps, flag ownership gaps, and accelerate resolution to cut mean time to detection and repair. Its proactive monitoring detects risks before traditional alerts trigger, flags error spikes and missed escalations, recognizes emerging patterns, and answers investigative queries in natural language. Built-in root cause analysis traces incidents end-to-end across time, logs, metrics, tickets, and post-mortems, links to similar events for instant context, and generates concise summaries.
  • 5
    Cisco AgenticOps
    AgenticOps is a groundbreaking paradigm redefining enterprise IT operations for the AI-driven era, leveraging AI agents to transform real-time telemetry, automation, and deep domain knowledge into intelligent, end-to-end actions, executing cross-domain workflows in networking, security, and applications directly within a unified platform. At its core is Cisco’s Deep Network Model, a large language model purpose-trained on over 40 years of Cisco expertise, spanning CCIE-level reasoning, CiscoU content, and real-world operational scenarios, further refined via reinforcement learning, chain-of-thought reasoning, and test-time scaling for precision and speed. This engine powers AI Canvas, the industry’s first generative UI for cross-domain IT operations, which aggregates live telemetry data into an intelligent workspace. Through the embedded Cisco AI Assistant, users interact via natural language to diagnose issues, explore options, drill into root causes, and execute remedial actions.
  • 6
    CardinalOps

    CardinalOps

    CardinalOps

    The CardinalOps platform is an AI-powered threat exposure management solution designed to provide organizations with an integrated view of prevention and detection controls across endpoint, cloud, identity, network, and more. It aggregates findings from misconfigurations, unsecured internet-facing workloads, missing hardening controls, and gaps in detection or prevention to give full visibility of exposures and prioritize actions based on business context and adversary tactics. The system continuously maps detections and controls to the MITRE ATT&CK framework to assess coverage depth and identify broken, noisy, or missing detection rules, while also generating deployment-ready detection content customized to each environment via native API integration with major SIEM/XDR tools such as Splunk, Microsoft Sentinel, IBM QRadar, and others. Through its automation and threat intelligence operationalization features, it helps security teams remediate exposure faster.
  • 7
    Daylight

    Daylight

    Daylight

    Daylight merges lightning-fast agentic AI with elite human expertise to deliver a next-gen managed detection and response service that goes beyond alerts, aiming to “take command” of your cyber-frontier. It promises full coverage of your environment with no blind spots, context-aware protection that continuously learns from your systems and past cases (including Slack chats), near-zero false positives, the industry’s lowest mean time to detection and mean time to response, and deep integration with your IT and security stack so it supports unlimited platforms, unlimited integrations, and delivers actionable, noise-free insights via AI dashboards. With Daylight, you get true end-to-end threat detection and response (no escalation games), 24/7 expert support, custom response workflows, environment-wide visibility, and measurable improvements in analyst utilization and response speed, all built to shift your security operations from reactive to commanding.
  • 8
    7AI

    7AI

    7AI

    7AI is an agentic security platform built to automate and accelerate the entire security operations lifecycle using specialized AI agents that investigate security alerts, form conclusions, and take action, turning processes that once took hours into minutes. Unlike traditional automation tools or AI copilots, 7AI deploys purpose-built, context-aware agents that are architecturally bounded to avoid hallucinations, and operate autonomously; they ingest alerts from existing security tools, enrich and correlate data across endpoints, cloud, identity, email, network, and more, and then produce full investigations with evidence, narrative summaries, cross-alert correlation, and audit trails. It offers a complete security stack: detection to triage alerts (filtering out noise and up to 95–99% of false positives), investigations (multi-system data-gathering and expert-level reasoning), and unified incident-case management (auto-populated cases, team collaboration, and handoffs).
  • 9
    Apica

    Apica

    Apica

    Apica is the observability cost optimization leader helping IT teams gain complete control over their telemetry data economics. Apica Ascent processes all observability data types including metrics, logs, traces, and events while optimizing observability costs by 40% compared to traditional approaches. Unlike solutions that lock users into proprietary formats, Ascent offers true flexibility with support for any data lake of choice, on-premises or cloud deployment options, and elimination of expensive tool sprawl through modular solutions. Built to handle high-cardinality data that overwhelms competitive solutions, Ascent includes the patented InstaStore™ optimized storage technology for maximum efficiency and advanced root cause analysis capabilities. Organizations choose us to make observability investments that reduce costs instead of spiraling them out of control.
  • 10
    CognitiveScale Cortex AI
    Developing AI solutions requires an engineering approach that is resilient, open and repeatable to ensure necessary quality and agility is achieved. Until today these efforts are missing the foundation to address these challenges amid a sea of point tools and fast changing models and data. Collaborative developer platform for automating development and control of AI applications across multiple personas. Derive hyper-detailed customer profiles from enterprise data to predict behaviors in real-time and at scale. Generate AI-powered models designed to continuously learn and achieve clearly defined business outcomes. Enables organizations to explain and prove compliance with applicable rules and regulations. CognitiveScale's Cortex AI Platform addresses enterprise AI use cases through modular platform offerings. Our customers consume and leverage its capabilities as microservices within their enterprise AI initiatives.
  • 11
    Cyclops

    Cyclops

    Cyclops Security

    Prioritizing risk is one of the biggest challenges in cyber security, our innovative solution creates a business context for your security operations, allowing you to validate the effectiveness of your security controls in the context of your unique business requirements. Cyclops integrates with your existing security tools using the CSMA approach to gather metadata on threats, vulnerabilities, cloud instances, SaaS apps, and more. It then enriches this data with context and insights by looking at the same entities in different products that are integrated. By providing this contextualized approach to risk validation, our cybersecurity mesh product helps you make intelligent decisions and focus on what really matters.
  • 12
    Conifers CognitiveSOC
    Conifers.ai's CognitiveSOC platform integrates with existing security operations center teams, tools, and portals to solve complex problems at scale with maximum accuracy and environmental awareness, acting as a force multiplier for your SOC. The platform uses adaptive learning, a deep understanding of institutional knowledge, and a telemetry pipeline to help SOC teams solve hard problems at scale. It seamlessly integrates with the ticketing systems and portals your SOC team already uses, so there's no need to alter workflows. The platform continuously ingests your institutional knowledge and shadows your analysts to fine-tune use cases. Using multi-tier coverage, complex incidents are analyzed, triaged, investigated, and resolved at scale, providing verdicts and contextual analysis based on your organization's policies and procedures, while keeping humans in the loop.
  • 13
    AWS DevOps Agent
    AWS DevOps Agent is a software from Amazon Web Services (AWS) designed to act as an autonomous, always-on operations engineer that resolves and proactively prevents incidents across your infrastructure, applications, and deployments. It automatically learns your application resources and their relationships, including infrastructure, code repositories, deployment pipelines, observability tools, and telemetry, then uses that knowledge to correlate logs, metrics, traces, deployment data, and recent code changes. When an alert, error spike, or support ticket arises, DevOps Agent immediately begins automated investigation; it triages incidents 24/7, runs root-cause analysis, and proposes detailed mitigation plans which can be automatically routed through team workflows (e.g., via Slack, ServiceNow, PagerDuty) or directly create support cases with AWS.
  • 14
    Swish.ai

    Swish.ai

    Swish.ai

    The first hyperautomation platform that works with any existing ITSM tool to uncover and act on insights in real time, accelerating ticket resolution time and reducing costs. Swish.ai hyperautomation platform mines, automates, and predicts the best course of action, and then routes to the best-matched agent. The Swish.ai platform evaluates your historical ITSM ticket data to create and inform dynamic AI models that capture insights about your unique environment, even as it evolves. Swish.ai’s patented solution goes beyond NLP to understand your company lingo. It improves the understanding of each underlying ticket issue and identifies the next best action accurately on the spot. Once tickets have been accurately classified, the platform evaluates additional real-time variables before assigning them to the best-matched agents. We also provide reference resources to ensure they have everything needed to resolve the ticket without re-routing or pausing it.