Mave
Mave · Mave: Agentic SecOps Platform That Investigates Alerts, Hunts Threats and Runs Governed Response Across Your Existing Security Tools
Mave is an agentic security operations platform whose agents investigate alerts to an evidence-backed verdict, answer plain-language questions across connected tools, hunt for activity that never alerted, tune detections and trigger response actions under approval rules the team sets. It queries data where it already lives through APIs instead of ingesting it, and is aimed at enterprise SOCs, multi-SIEM organizations and MSSPs.
Best for
Enterprise SOCs, MSSPs and organizations running several SIEMs or EDRs that want AI agents to investigate every alert, hunt and tune detections across the tools they already own, with response actions under their own approval rules and no data migration
Not ideal for
Small teams without a security function or existing security tooling to connect, buyers who want self-serve sign-up and published pricing, and organizations that require a fully self-hosted or air-gapped deployment
Who it's for
SOC analysts, detection engineers, threat hunters, security leaders and MSSPs at organizations with an existing, often fragmented, security stack
Capabilities
- Investigates alerts by pulling context from every connected tool and returning a verdict with the evidence that supports it
- Ask Mave: plain-language questions across all connected systems, answered with citations to the underlying evidence and no query syntax required
- Queries each connected system in its native language at task time, without ingesting telemetry into a central store, index or new data lake
- Continuous agentic threat hunting for activity that never raised an alert, starting from a campaign, actor, vulnerability, indicator, technique or analyst hypothesis
- Scores live threat campaigns against the organization's technologies, assets and identities, and watches for dormant indicators reactivating
- Detection engineering across SPL, KQL, YARA-L, Sigma, EQL, Lucene and SQL-based rules: finds coverage gaps, tunes noisy or broken rules, translates and tests rules against historical data, and commits approved changes to GitHub, GitLab, Bitbucket or Azure DevOps
- Generates a response from the live investigation (notify, ticket, document or remediate, such as isolating a host or disabling an identity) instead of relying on a fixed SOAR playbook
- Governance controls: approval gates for workflow actions and detection updates, destructive actions behind approval by default, per-platform least-privilege API permissions that start read-only, and a full audit trail of queries, correlations, conclusions and actions
- Bring-your-own context: a knowledge base of policies, naming, ownership and exceptions that agents use during their work
- Mave Agentic Workflows let teams build their own agentic workflows on the Mave Harness runtime that agents use to act across connected tools
- Multi-tenant operation for MSSPs and multi-SIEM organizations, with tenant-scoped APIs and context, permissions and response policies kept separate per customer or environment
- Mave Broker, an on-premises broker that reaches internal tools without exposing their APIs externally
Limitations
- No public price: both packages and the SMB bundle are quoted through a sales form, and purchase starts with a demo
- No self-serve sign-up or trial: the site routes buyers to a demo, evaluation is a proof of concept, and Mave's terms say any free POC period is set in an order form
- No public product documentation, API reference or full integration catalog is published; the platform page names a sample of integrations only
- Delivered as SaaS (the AWS Marketplace listing is a SaaS contract); no fully self-hosted deployment is documented, only the Mave Broker for reaching on-premises tools
- Because data is not ingested, investigations depend on the retention, API limits and permissions of your existing tools; Mave sells managed retention separately as the Mave Lake add-on
- Alert investigation with verdicts, governed response and reasoning-based detections are in the Advanced package; Essentials covers Ask Mave, threat hunting, threat intelligence and custom agentic workflows
- Mave does not publish which AI models power its agents; its terms say the service may include third-party AI and language-generation models
Use cases
- Letting Mave investigate every Tier 1 and Tier 2 alert to a verdict so analysts only review the cases that need judgment, instead of paying an MDR for first-line triage
- Asking "did anyone else receive this phishing email, and did any of them click?" across email, EDR and identity tools in one plain-language question
- Checking a newly reported attack campaign against your own assets and identities, then hunting across the SIEM, EDR and cloud for related activity
- Translating a Sigma rule into SPL and KQL, testing it against historical data in both SIEMs, and opening a commit in the detection-as-code repository for review
- Running investigations and hunts across several SIEMs after an acquisition without first consolidating them
- Serving many MSSP clients with standard agents that run on each client's own stack under client-specific permissions and response policies
- Moving searches and investigations off the SIEM to measure which data sources could be dropped from premium ingestion before a renewal
Our take
Mave's bet is that SOC agents should go to the data instead of the data coming to them, which matters most if your stack is fragmented: several SIEMs after an acquisition, an MSSP serving many clients, or a team that wants to cut SIEM ingestion. In a single-vendor shop, the platform's own AI analyst may cover most of the same ground with less integration work. The governance model (read-only start, approval gates, destructive actions held back by default, full audit trail) is the right shape for letting agents act, and the proof-of-concept metrics Mave proposes, such as analyst agreement with verdicts and the share of alerts still escalated, are the ones to insist on. Because there is no public documentation, pricing or model disclosure, ask in the evaluation which of your tools are supported with read and write actions, how retention gaps are handled without Mave Lake, which models run the agents and how your data is processed.
Who should use it
Security teams with a mixed or multi-SIEM stack, MSSPs, and organizations looking to reduce MDR reliance or SIEM ingestion that want AI agents to investigate, hunt and tune detections across existing tools, with response kept under their own approval rules.
Who should skip it
Small IT teams without security tooling or a SOC function, teams fully standardized on one vendor's platform with its own built-in AI analyst, buyers who need a self-serve trial or published prices, and organizations that cannot use a SaaS control plane.
Strengths
- Vendor-neutral: works across the SIEMs, EDRs and identity tools you already own rather than requiring one platform
- No telemetry migration or ingestion pipeline before it is useful; integrations connect through APIs and start read-only
- Covers the whole SOC loop (investigation, hunting, threat intelligence, detection engineering and response) in one place
- Response is governed: approval gates, destructive actions behind approval by default, least-privilege permissions and a full audit trail
- Detection engineering works across major rule languages and detection-as-code repositories
- Multi-tenant design suits MSSPs and organizations with several SIEMs or subsidiaries
Weaknesses
- No published pricing, self-serve trial or public documentation, so evaluation requires a sales process and proof of concept
- Investigation depth depends on which tools you connect, their retention and the permissions you grant
- Alert investigation and governed response require the higher Advanced package
- Young company that only left stealth in October 2026, and it does not say which AI models its agents use
Mave pricing
Mave Essentials
Contact sales
- Ask Mave: plain-language questions across connected tools with cited evidence
- Agentic threat hunting and Mave Threat Intelligence scored against your environment
- Mave Agentic Workflows on the Mave Harness runtime
Mave Advanced
Contact sales
- Everything in Essentials
- Mave Agentic SOC: alerts investigated to a verdict, responses run under your guardrails
- Mave Agentic Detection: reasoning-based detections
- Enterprise workflows with ITSM and knowledge-base integrations
Add-ons
Contact sales
- Mave Lake: managed, searchable security data retention with hot and cold tiers per source
- Mave Broker: on-premises broker for internal tools
- Mave SECTEAM: managed context tuning, threat hunting, detection engineering and reporting
Bundle for SMBs
Contact sales
- Alternative package for smaller teams at a fixed price (not published)
Note: Mave prices by the number of endpoints protected and the size of the security team, not by data volume, and quotes are requested through a form on its pricing page. Neither package requires moving data into another store. Mave is also sold as a SaaS contract through AWS Marketplace.
Where Mave excels
Bringing MDR triage in-house
Mave investigates every Tier 1 and Tier 2 alert to an evidence-backed verdict and can run authorized responses, so analysts only handle cases that need judgment or approval.
Post-acquisition SecOps across several SIEMs
Agents run cross-SIEM searches, investigations and hunts through scoped APIs while each business unit keeps its own tools, data and permissions, without waiting for a consolidation project.
MSSP capacity
Standard agents can be deployed across client tenants and customized per client, with tenant-scoped APIs and separate context, permissions and response policies.
SIEM renewal planning
Moving investigations and hunts off the SIEM and measuring which sources and retention can be dropped without losing coverage gives teams evidence before negotiating ingestion volume.
Mave vs. competitors
Mave vs. Purple AI
Purple AI is SentinelOne's agentic SOC analyst and reasons over data in the SentinelOne Singularity Platform, including third-party sources ingested into it, with response running through Singularity Hyperautomation. Mave is a separate, vendor-neutral layer that queries SentinelOne and other vendors' tools in place without ingesting their data, and adds hunting and detection engineering across several SIEM rule languages. Purple AI fits SentinelOne-standardized SOCs; Mave fits mixed and multi-SIEM stacks.
Frequently asked questions
What does Mave do?
Mave is an agentic security operations platform. Its agents investigate alerts across your connected security tools and return a verdict with evidence, answer plain-language questions across those tools (Ask Mave), hunt for threats that never raised an alert, apply threat intelligence to your environment, find and tune gaps in detection rules, and trigger response actions such as notifying, ticketing, isolating a host or disabling an identity, under approval rules your team sets.
Does Mave replace my SIEM?
Not necessarily. Mave queries the SIEM and other tools in place through their APIs rather than storing the data itself, so it works alongside one or several SIEMs. Mave does market it for reducing SIEM ingestion and retention costs: teams can move searches, investigations and hunts off the SIEM first, then use proof-of-concept results to decide what data to stop ingesting at renewal. For retention outside your existing tools, Mave sells a separate Mave Lake add-on.
How much does Mave cost?
Mave does not publish prices. It offers two packages, Essentials (Ask Mave, agentic threat hunting, threat intelligence and agentic workflows) and Advanced (everything in Essentials plus the agentic SOC for alert investigation and response, agentic detection and ITSM and knowledge-base integrations), plus add-ons (Mave Lake, Mave Broker and SECTEAM managed services) and a fixed-price bundle for smaller teams. Mave says pricing is based on the number of endpoints and the size of the security team, not on data volume; you request a custom quote. It is also available as a SaaS contract on AWS Marketplace.
Can Mave take response actions on its own?
Yes, within rules you set. Any verdict, indicator or finding can trigger a response, from notifying or opening a ticket to remediation through connected tools. You decide what runs automatically and what waits for a human; Mave says destructive actions stay behind approval by default, each integration uses least-privilege, per-platform permissions that start read-only, and every query, conclusion and action is logged.
Which tools does Mave integrate with?
Mave's platform page shows integrations including Splunk, Elastic, CrowdStrike, SentinelOne, Okta, Microsoft Azure, Amazon Web Services, Google, ServiceNow, Jira, Slack and Zoom, and its detection engineering page names GitHub, GitLab, Bitbucket and Azure DevOps for detection-as-code repositories. Mave describes itself as platform-agnostic but does not publish a full integration list, so confirm coverage for your specific tools during a demo.
Does Mave have a free trial?
There is no self-serve sign-up or trial. Mave sells through demos, and its solution pages describe evaluation as a proof of concept measured with agreed metrics, such as the share of alerts dispositioned, analyst agreement with verdicts and time to verdict. Mave's terms of service say it may offer a free, no-obligation POC period as specified in an order form.
Can Mave run on-premises?
Mave is delivered as SaaS. To reach on-premises tools without exposing their APIs to the internet, it offers Mave Broker, an on-premises broker, and lightweight scoped bridges that bring on-premises workloads into the same investigations as cloud and SaaS sources. A fully self-hosted deployment is not documented.
Mave vs Purple AI: what is the difference?
Purple AI is SentinelOne's agentic SOC analyst and works on data inside the SentinelOne Singularity Platform. Mave is vendor-neutral: it queries many vendors' SIEMs, EDRs and identity tools in place without ingesting their data, and SentinelOne is one of the integrations it shows. Purple AI suits teams standardized on SentinelOne; Mave targets mixed or multi-SIEM stacks.
Integrations & fit
About Mave
Mave sits on top of the security and IT tools an organization already runs (SIEMs, EDRs, identity, cloud, ticketing and chat) and does SOC work across them rather than inside one of them. Integrations connect through scoped APIs and start read-only, and Mave's agents query each system in its own query language at the moment a task needs the data, so there is no telemetry migration, central index or schema normalization project before it is useful. The work comes in four connected loops. Alert investigation pulls an alert, gathers context from every connected tool and returns a verdict with the supporting evidence. Ask Mave is federated search: an analyst asks a question in plain language and gets an answer that cites the evidence behind it. Threat hunting and threat intelligence start from a campaign, actor, indicator, technique or hypothesis, check whether it is relevant to the organization's assets and identities, and hunt across connected systems. Detection engineering reviews, translates, tests and tunes rules in SPL, KQL, YARA-L, Sigma, EQL, Lucene and SQL, and can commit approved changes to detection-as-code repositories. Any verdict or finding can then trigger a response (notify, open a ticket, document, or contain and remediate through connected tools, such as isolating a host or disabling an identity), with destructive actions held behind approval by default and every query, conclusion and action logged. Mave came out of stealth on October 22, 2026 with $34 million in funding. It says it is already running in more than 200 SOCs and that Fortune 200 companies and global MSSPs use it. It is sold through demos and custom quotes (two packages, Essentials and Advanced, priced by endpoints and security team size rather than data volume) and as a SaaS contract on AWS Marketplace. The tradeoffs: there is no self-serve sign-up or trial (evaluation runs through a demo and a proof of concept), no public price and no public documentation; investigation quality depends on how many tools you connect and what permissions you grant; and the no-ingestion model means Mave works with whatever retention your existing systems keep, unless you add its separate Mave Lake retention add-on.
Updates from Mave
Mave announced its launch with $34 million in funding: a $28 million Series A led by Red Dot Capital Partners with Lumir Growth Partners, and a $6 million seed round led by Dell Technologies Capital and Emerge Ventures. The company said the platform was already running in more than 200 SOCs, that Fortune 200 companies and global MSSPs use it, and that the funding will go to AI research, the enterprise platform and more than doubling its team.
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