SOC Platform Security Tools

Exaforce is building an AI first SOC platform that can serve as an augment to your existing SOC via agentic capabilities, a SIEM replacement or augment via its data lake, as well as offering MDR capabilities via a managed offering.

Mate provides a comprehensive AI SOC enablement platform by integrating into a company's entire data stack, building a comprehensive knowledge base, and then giving users a copilot like experience to accelerate their investigation and response capabilities

Scanner provides a simpler SIEM data architecture to provide maximum flexibility for AI. They enable rapid querying of new and historical data in S3 through inventive compression and indexing techniques. They also enable flexible compute usage via a serverless architecture, allowing you to only pay for the exact compute you use.

AI-driven SIEM and security analytics built on the open Elastic (Elasticsearch) stack, unifying detection, investigation, and response across endpoints and clouds.

Brava uses an attack simulation engine to maximize the value of every log - providing data pipeline, storage, search, and AI response capabilities. First, their agents identify blind spots across your ecosystem by simulating various attacks and testing your detection logic. They then utilize the findings to optimize your log ingestion by reducing unnecessary logs. Finally, they provide an optimized data storage and searching layer to empower agentic incident response.

Monad is an extremely flexible data pipeline solution for normalizing, enriching, and routing data. They provide a straightforward user interface with some of the most robust flexibility in the category.

Panther is the SIEM tool truly doing things differently. Their unique approach to detection rules makes things much easier to manage in that they can be written in Python. This makes it easier to write and maintain rules, and also makes it easier to integrate with other tools. They allow some awesome flexibility via Python based rules.

AI Strike is combining LLMs with traditional SIEM and CSPM to provide a holistic LLM based approach to security incident response. They're combining robust asset data with log sources to give the LLM enough context to make accurate alerting decisions.

Artemis provides numerous services under a single platform - from MDR to AI SOC to Detection Engineering. Their key differentiator is intelligently storing and searching data within their own platform or other platforms depending on the context. This enables AI incident response, detection engineering management, or SIEM replacement use cases.

Daylight offers end-to-end MDR services powered by an AI data platform, but with a commitment to the human aspects of being a service provider. Daylight’s primary differentiation goes beyond AI or data lookup capabilities to focus on the quality of the human analysts and threat hunters behind the product. Teams get the speed benefits of an AI first pass, with the confidence of human expertise backing them up.

Vega rolls up a wide scope of workflows into what they call a Security Analytics Mesh - a unified data system for humans and agents to query data wherever it lives. These capabilities enable several core outcomes for the SOC: analytics, detection engineering, autonomous triage, and threat hunting. The platform sits across existing SIEMs, data lakes, and cloud storage and can operate as either a full SIEM replacement or an augmentation layer, with the data staying in place either way.

Query is not strictly speaking a SIEM, but an excellent way to gather all of your relevant data in a single search. They've created truly on demand, cross integration searches - a great way to save money and time for organizations deep the struggle of log management.

Splunk is still one of the best siems for security teams willing to invest the time to learning their query language. They have robust features and integration options, but have a steep learning curve and can be expensive. If you're an organization looking to make a substantial investment in dedicated security teams, Splunk is a great option.

SentinelOne was one of the first major security providers to normalize their data into a data lake architecture, and the benefits are more clear than ever: giving customers a single place to manage all of their security programs, from EDR to CNAPP to AI Security. Consolidating this data enables teams to run cross-domain investigations without stitching integrations between separate products, and gives Purple AI (their agentic analyst) a unified data plane to reason across instead of guessing at relationships between siloed tools.

AI-native modern SIEM and security data platform for ingesting, detecting on, and investigating security logs at scale.

Cortex Cloud is a security operations platform that integrates cloud and application security capabilities into their larger security operations offerings. This provides a single hub for managing first and third party findings across vulnerabilities and runtime events.

Datadog offers a complete suite a security offerings that are a great fit for developer focused teams not looking for the most mature details in each area. They offer most scanning types, runtime detections, and a full SIEM, and you're probably already sending them your logs. It's a great runtime choice to meet developers where they work, but the UX is built primarily for developers.

SumoLogic's being cloud native has given them a lead in fast cloud queries and development. They're a great middle of the road between QRadar and Splunk, and similarly get the job done with both a query language and understandable dash-boarding. They provide a great cloud native offering.

Azure Sentinel will get the job done for organizations looking specifically for a SIEM for their Azure environment. They're less robust in their support for other cloud providers, but are a great option for organizations looking to keep things simple and consolidated.

7AI started as an AI incident response tool but has quickly expanded to provide detection engineering, data storage, MDR services, and more. Their architecture supports advanced incident response automation especially for phishing and email security use cases, with specialized agents doing investigations within the context of your environment.

Fig provides teams visibility into their detection and log source health across their existing tools. It gives teams insights into what detections would never fire, what log enrichments can be done, and helps consolidate and manage the overall health of your program.

CrowdStrike's container runtime technically works, but deployment, maintenance, and usefulness do not compare to other tools at the time of testing. CrowdStrike's Windows offerings remain dominant in the space, but their CNAPP and container security solutions are difficult to recommend.

API-first SecOps cloud platform giving MSSPs and security teams pay-as-you-go EDR, telemetry pipelines, and agentic AI automation across their existing tools.

Streaming-first composable SIEM combining security data pipelines, tiered storage, in-stream detection, and AI-assisted SecOps workflows.

Beacon provides a data storage, data pipelines and an agent runtime that normalizes and enriches telemetry from 150+ sources so AI agents and analysts can detect, hunt, and respond at machine speed.

Vendor-agnostic telemetry pipeline that collects, reduces, enriches, and routes security and observability data from any source to any destination.

Acquired by Palo Alto Networks. QRadar offers robust protection and logging features, but without the steep learning curve of Splunk. Their methodology for filtering is simple and gets the job done, but your team will work more slowly over time without the query language.

Devo is a robust cloud SIEM with a lot of solutions. However, their lack of clear focus has made them less effective as they've tried to expand half-heartedly into numerous areas. They're a great option for organizations looking for a single pane of glass, but not the best option for any one area.

Google SecOps' SIEM offering is a good option for organizations looking for robust SIEM capabilities hosted on top of Google Cloud's infrastructure. They're a straightforward choice for a modern SIEM, with especially robust threat intelligence capabilities

Greymatter is an AI SOC platform that's composed of agentic investigations, detection management, data pipelines, and threat hunting capabilities.

Anvillogic provides a unified detection engineering plane for writing federated searches and detections across multiple SIEMs and data stores.

Defender for Cloud has a lot of comparative features to dedicated CNAPPs, but it's a beast to setup and maintain. It's a good starting point for larger companies who don't have an appetite for a more focused solution, and are addicted to collecting the highest E license as possible.

Unified data and AI lakehouse that security teams use as a petabyte-scale security data lake for detection engineering, threat hunting, and SIEM cost offload.