SenseOn vs Splunk: A Complete Comparison for 2026

SenseOn is a detection and response platform: one lightweight Universal Sensor captures endpoint, network and identity telemetry, the Data Fabric connects it with the other signals you choose, and the Intelligence Fabric correlates it into cases. Splunk is a log management and SIEM platform that aggregates data from across your environment for search, correlation and analysis. Both serve security teams, but they differ on the question that drives most Splunk reviews: how much of your data you can afford to analyse. This guide compares them on pricing, detection, deployment and operations, with Splunk's capabilities and pricing linked to Splunk's own pages.

How Does Splunk Work?

Splunk is a data platform built around its proprietary Search Processing Language (SPL). Splunk ingests machine data from virtually any source (firewalls, endpoints, servers, cloud services, applications), normalises that data and stores it in a searchable index.

Splunk's architecture consists of several components:

• Forwarders collect data from source systems and send it to the Splunk infrastructure
• Indexers receive, parse and store incoming data, making it searchable
• Search heads provide the interface where analysts write SPL queries, build dashboards and create detection rules
• Splunk Enterprise Security (ES) is the SIEM layer that adds correlation rules, notable events, risk-based alerting and compliance frameworks on top of the core platform. Splunk describes it as a SIEM that "has been a leader in the market for over a decade"

Splunk's strength lies in its flexibility. SPL can query virtually any data format, and Splunkbase offers more than 1,000 apps and add-ons from Splunk, its partners and its community for integrating with third-party tools. For organisations with skilled Splunk analysts, this flexibility is genuinely powerful.

The trade-off is complexity. Operating Splunk at scale requires dedicated expertise in SPL, index management, search optimisation and data pipeline architecture. Many organisations need dedicated Splunk administrators to maintain the platform effectively.

How Does SenseOn Work?

SenseOn takes a different approach. Instead of starting from logs forwarded by other tools, SenseOn deploys a single lightweight Universal Sensor that captures endpoint, network and identity telemetry on the same device. On Windows it uses under 0.6% CPU and about 90 MB of memory for endpoint plus network telemetry. The Data Fabric adds other supported signals through out-of-the-box integrations with Microsoft 365, AWS and identity providers, plus log ingestion for anything else you want to bring in. Supported telemetry that you route to Detection & Response goes through built-in detection and correlation. Detection runs at three speeds: in real time on the endpoint, in near real time across every log source you route to Detection & Response, as it streams through SenseOn's message queue, and with behavioural analytics that run about every five minutes across those same sources.

The Intelligence Fabric correlates that evidence into cases using cross-domain correlation, which cross-validates each potential alert using three independent AI techniques:

1. Supervised learning models trained on labelled threat data identify known attack patterns
2. Unsupervised anomaly detection identifies deviations from normal behaviour without prior knowledge of specific threats
3. Deep-learning sequence analysis examines chains of events over time to detect multi-stage attacks

In the independent AV-Comparatives Business Security Test, March to June 2024, SenseOn recorded 95.9% real-world protection and 98.7% malware protection with zero false alarms. That is an endpoint protection test, in which a false alarm is a clean file or website wrongly blocked, so it measures the sensor rather than SIEM-style detection. Read the protection rate and the false alarm count together.

Because one sensor and one platform cover endpoint, network and identity evidence, SenseOn covers detection work that is usually split across SIEM, EDR, NDR, SOAR and UEBA tools, in one console.

Head-to-Head Comparison

Pricing Comparison

Pricing is often what starts a Splunk review. Splunk's pricing models page states that "ingest volume-based pricing is based on gigabytes of data ingested into Splunk", with workload pricing "based on the amount of compute and storage resources required to run search and analytics workloads" as the alternative. Either way, the more data you ingest and search, the better your security visibility, but the higher your costs. This tension, sometimes called the SIEM tax, forces security teams to trade coverage against budget.

The Splunk bill has five parts, and the licence is only the first:

• Splunk licence: Set by ingest volume or workload, with tier and negotiated discounts applied. Splunk's pricing page does not publish list rates for Splunk Cloud Platform or Enterprise Security; you request a quote
• Infrastructure: On-premises compute and storage for indexers and search heads, or the equivalent cloud spend
• Professional services: Ongoing tuning, content development and architecture support
• Staffing: Dedicated Splunk engineers to keep the platform healthy
• Add-on licences: Splunk Enterprise Security, Splunk SOAR and Splunk UBA are separately licensed products

Model all five, not only the licence line; most of them grow as data volumes increase.

Retention raises a further question: how quickly you can use older data. In Splunk Cloud Platform, how long data stays searchable is your searchable-retention setting, set per index. After that, data can go to a Splunk-managed archive, which cannot be searched where it sits. Splunk's archive documentation says: "The restoration process can take up to 24 hours to complete." Splunk "will block you from restoring large amounts of data" that could hurt performance, and "by default, restored data is searchable for a period of one month". A hunt that reaches past your searchable retention starts with a restore request.

SenseOn changes the model rather than the rate. It is priced as an annual pool of Flex Intelligence Credits, with tiered plans on the pricing page. Detection, observability and compliance draw from one credit pool, and you pay for outcomes: detection and response across your data, analytics included, and the investigations SenseOn's AI completes. Data volume is one meter, not the whole bill. SenseOn's cost compression combines three things: edge processing removes unnecessary data before the pipeline; intelligent routing down three pipelines, configured by Weave, SenseOn's security engineering agent, separates storage from compute; and ClickHouse compression, with storage priced on the compressed volume. Together these cut costs by about 40% against a traditional SIEM. The saving on SIEM costs alone would be larger, because SenseOn's price also includes the work of its Agentic Cybersecurity Team (ACT), the AI agents that investigate and resolve cases. You pay for the investigations the agents complete, not for an MDR service. Data rolls to object-storage economics automatically. There is no restore step: SenseOn's AI agents query every tier where the data sits, and can run queries and threat hunts across all retained data for the whole retention period. Because they run in the background, a slower query over older data does not keep an analyst waiting.

Detection Philosophy: Rules vs AI

The most fundamental difference between SenseOn and Splunk is how they approach detection.

Splunk relies on correlation rules: logical statements written in SPL that define the conditions under which an alert should fire. For example: "If a user authenticates from two countries within one hour, generate an alert." These rules are powerful when well crafted, but they require someone to anticipate the attack pattern in advance, write the rule correctly and tune the thresholds to minimise false positives without missing genuine threats. Hard thresholds are a known source of false alarms in intrusion detection (Khraisat et al., Cybersecurity, 2019).

Real-world attacks rarely match neat rule definitions. Adversaries adapt their techniques to stay below detection thresholds, and novel attack patterns have no corresponding rules. Mature Splunk deployments typically maintain hundreds of correlation rules, each needing tuning as the environment changes. That tuning decides outcomes: Bryant and Saiedian found that re-engineering SIEM correlation rules improved detection rates, gave more descriptive alerts and lowered false positives, and attributed much of SIEM's shortfall to insufficient configuration (Bryant and Saiedian, Computers & Security, 2020). The CardinalOps 2025 State of SIEM Detection Risk report, based on analysis of production SIEM deployments, found that enterprise SIEMs on average have detections for only 22% of MITRE ATT&CK techniques, and that 10% of their rules are broken.

SenseOn's cross-domain correlation starts from built-in detection instead. The three AI methods analyse telemetry independently and cross-validate findings. The supervised model recognises known patterns, the unsupervised model flags anomalies without prior knowledge (an approach shown to detect insider threats from unlabelled data with low false positive rates, and to hold up better when several models vote (Le and Zincir-Heywood, IEEE Transactions on Network and Service Management, 2021)) and the deep-learning model detects sequences that unfold over hours or days. Detection engineering still has a place: Forge drafts and tests detection changes, and a detection engineer reviews, tunes and approves them.

The operational effect shows in the published numbers. Across customer environments, about 97% of alert noise is removed before an analyst sees a queue. In one Fortune 500 services environment, 33.4 billion events a month produced 36,000 alerts, 173 cases needing human judgement in 30 days and about six human escalations a day. Across all customer environments, 92.5% of incidents are resolved by AI under human governance over a rolling 30-day window.

When Should You Choose Splunk?

Splunk remains a strong choice in specific circumstances. Where SenseOn still has a role, we say so.

• Large enterprise with deep SPL investment: If your organisation has invested heavily in Splunk talent, custom SPL content and integrated workflows, the switching cost may outweigh the benefits of migration. Splunk's flexibility is hard to match for organisations that can afford to exploit it. SenseOn's answer: run SenseOn alongside Splunk and move high-volume, low-value sources off the per-GB licence where the evidence supports it.
• General-purpose log analytics beyond security: Splunk serves IT operations, application performance monitoring and business analytics well beyond security. SenseOn's answer: SenseOn searches and visualises any log, not only security data, so log search and dashboards for IT and application logs can move too.
• Existing Splunk investment with long-term contracts: Organisations mid-way through multi-year Splunk licences may find it more practical to plan migration for the next renewal.
• Regulatory requirements for raw log retention: Some frameworks require long-term retention of raw logs in their original format. SenseOn's answer: retention is set per pipeline in compressed cold storage and stays queryable through standard APIs; confirm the format your auditor needs.

When Should You Choose SenseOn?

• Splunk cost pressure: If your Splunk renewal is driving budget conversations, SenseOn prices on outcomes, and data volume is one meter, not the whole bill. Detection runs on endpoint telemetry and the log sources you route to Detection & Response.
• Lean SOC teams: If your security team is small, you cannot spend most of it on SIEM administration. With about 97% of alert noise removed before a queue, and mean time to detect and respond under 20 minutes across managed-service customer environments, a small team works from cases, not raw alerts.
• Consolidation goals: If you run separate SIEM, EDR, NDR and SOAR tools, one sensor covers endpoint, network and identity, and response runs from the same agent that collected the evidence. Consolidate licences only when the parallel run shows the overlap.
• Compliance and AI accountability: Organisations subject to DORA, NIS2 or FCA requirements need continuous monitoring and evidence. Regulation (EU) 2022/2554 (DORA) and Directive (EU) 2022/2555 (NIS2) both make detection and incident handling mandatory. SenseOn's Decision Trace writes every AI and analyst action to an append-only record, giving chain-of-custody evidence for NIS2, DORA, the EU AI Act and ISO 27001.
• Consolidated visibility: The Universal Sensor records network connections, DNS and TLS metadata on the host, tied to the process and user that made them, so network evidence does not depend on building a pipeline from another tool. On Linux, network telemetry needs kernel 5.2 or later with eBPF; older kernels give process telemetry only, and a network probe covers segments where no agent can run.

Customers describe the change in their own words. At ED&F Man, Cyber Security Analyst John Jordan said: "We managed to cut down from 40 cases a day down to about 40 a month… it massively reduces how much time we spend following false leads." That is a measured change in cases handled, not a universal false-positive rate.

Migration Considerations

Moving from Splunk to SenseOn is augment-first: deploy, prove, redirect, then consolidate. Here is what to expect.

Phase 1: Assessment

Map your current Splunk environment with the SenseOn team: data sources by daily volume, detection rules that actually fire, compliance requirements and integration points. This shows which Splunk functions SenseOn covers and which, such as non-security analytics, stay on a log tool.

Phase 2: Sensor Deployment

Deploy the Universal Sensor across your estate. New endpoints enrol with a secure token, and the same command runs in PowerShell on one machine or across an estate through Intune, SCCM, Group Policy or NinjaOne. The sensor needs no inbound ports; all communication is initiated from the endpoint over mutually authenticated TLS. If you keep another EDR, set SenseOn's antimalware to dual-running mode.

Phase 3: Parallel Operation

Run SenseOn alongside Splunk for a 14 to 28 day proof window. Your team sees what SenseOn catches, what the incumbent misses and where response time improves, and gets familiar with the console before anything is switched off.

Phase 4: Redirect and Consolidate

Move high-volume, low-value sources off the Splunk licence first, then retire overlapping tools only where the evidence supports it. Archive Splunk data you must keep for audit before you decommission, or keep a reduced licence until your retention obligations are met.

What Data to Bring

You do not need to migrate raw log data from Splunk into SenseOn; the sensor starts collecting its own telemetry when it is installed. You may want to:

• Archive Splunk data for compliance retention requirements
• Export key correlation rules for reference, to check coverage during the parallel run
• Document current Splunk dashboards and reports so equivalent SenseOn views can be configured

Frequently Asked Questions

Is SenseOn a direct replacement for Splunk?

Yes. SenseOn covers detection, correlation, investigation and response across endpoint, network and identity, and it searches and visualises any log you send it, security or not. The recommended route is augment-first: run SenseOn alongside Splunk for a 14 to 28 day proof window.

How does SenseOn's pricing compare to Splunk's?

Splunk prices by data volume or compute, which means costs grow as your environment generates more logs. SenseOn is priced as an annual pool of Flex Intelligence Credits. Detection, observability and compliance draw from one pool, and you pay for outcomes: detection and response across your data, analytics included, and the investigations SenseOn's AI completes. Data volume is one meter, not the whole bill. Three levers bring the cost down: edge processing removes unnecessary data before the pipeline, Weave (SenseOn's security engineering agent) routes data down three pipelines with storage separated from compute, and ClickHouse compression means storage is priced on the compressed volume. Together they cut costs by about 40% against a traditional SIEM, and the price also covers the AI agents that investigate and resolve cases.

Can I migrate from Splunk to SenseOn without losing historical data?

Yes. Keep historical data in your existing Splunk instance during the transition, or export it for archival before you decommission. SenseOn does not need your Splunk history to start: the Universal Sensor collects its own telemetry from installation, and you run both platforms in parallel during the proof window.

Does SenseOn require SPL expertise to operate?

No. SenseOn starts from built-in detection and correlated cases rather than a library of searches you write. Hunter prepares hunt queries and evidence for a person to review, and Forge drafts detection changes for an engineer to approve. Teams without dedicated Splunk engineers can work from cases instead of queries.

How does SenseOn handle compliance reporting compared to Splunk?

SenseOn's Decision Trace writes every AI and analyst action to an append-only, immutable record, giving 100% audit coverage and chain-of-custody evidence for NIS2, DORA, the EU AI Act and ISO 27001. SenseOn itself is ISO/IEC 27001:2022 certified by British Assessment Bureau (UKAS-accredited) and holds Cyber Essentials Plus. Splunk Enterprise Security includes compliance content; tailoring reports to a specific regulation takes configuration effort and SPL expertise.

Sources

• Ansam Khraisat, Iqbal Gondal, Peter Vamplew, Joarder Kamruzzaman, "Survey of intrusion detection systems: techniques, datasets and challenges", Cybersecurity (Springer), 2019, https://doi.org/10.1186/s42400-019-0038-7 (open access)
• Blake D. Bryant, Hossein Saiedian, "Improving SIEM alert metadata aggregation with a novel kill-chain based classification model", Computers & Security, 2020, https://doi.org/10.1016/j.cose.2020.101817
• Duc C. Le, Nur Zincir-Heywood, "Anomaly Detection for Insider Threats Using Unsupervised Ensembles", IEEE Transactions on Network and Service Management, 2021, https://doi.org/10.1109/TNSM.2021.3071928
• Splunk, Splunk pricing models, accessed 20 September 2026
• Splunk, Splunk pricing, accessed 20 September 2026
• Splunk, Store expired Splunk Cloud Platform data in a Splunk-managed archive, Splunk Cloud Platform Admin Manual 10.5.2605, accessed 23 September 2026
• Splunk, Splunk Enterprise Security, accessed 20 September 2026
• Splunk, Splunk SOAR, accessed 20 September 2026
• Splunk, Splunkbase, accessed 20 September 2026
• AV-Comparatives, Business Security Test 2024 (March - June), accessed 20 September 2026
• CardinalOps, State of SIEM Detection Risk, 2025 edition, June 2025, accessed 20 September 2026
• EUR-Lex, Regulation (EU) 2022/2554 (DORA), 14 December 2022, accessed 20 September 2026
• EUR-Lex, Directive (EU) 2022/2555 (NIS2), 14 December 2022, accessed 20 September 2026

Related: Splunk Alternatives for Security Teams: 7 SIEMs Compared

How SenseOn writes, checks and corrects its content: editorial standards.