WITHSTAND

One complete record of
the whole environment.

One complete record of everything that happens across your environment, with a mature, accredited body of detection and compliance content on top and machine learning and constrained generative AI that never leave your boundary. Software on certified hardware or in your accredited private cloud.

Accredited content on top, a new platform beneath.

The order is deliberate. The data plane comes first, so every layer above it reads the same complete record: the detection, correlation and compliance content, then machine learning, then generative AI. All of it runs inside your boundary; nothing is sent out to be analysed.

Inside your boundarySourcesITOTIoTAIData1Sovereign data planeOne complete record2Detection, correlation, compliance3Machine learning4Generative AINo route out for analysis

What the platform is built to do.

Every capability reads the same complete data on infrastructure you control.

  • Sovereign data plane

    Everything lands once, complete, in open formats.

    Logs, endpoint, network, identity, file activity, OT protocol events, IoT device events and AI traces land in one store on hardware you control, queryable in seconds from hot storage. A streaming backbone, a columnar analytical store and an open-table lake for retention. You set retention; the vendor does not meter it.

  • Detection and correlation

    A mature body of content, running on complete data.

    Real-time rule evaluation on the stream, with detection content expressed in the open Sigma standard alongside native rules. Correlation runs on entities, not on log lines, so the same actor touching an identity, a model and a data store is seen as one story.

  • Compliance engine

    Whether a control fired, not whether it is documented.

    Control-level measurement of regulatory obligations from the same telemetry: government control baselines, operational-resilience rules and critical-infrastructure regimes. Continuous, evidenced, and mapped to the obligations a board is accountable for.

  • Investigation and response

    Ask any question of any data, then act inside your boundary.

    Sub-second investigation over billions of events from one query surface. Response workflows run as data through an embedded orchestration engine: an action runs automatically where your environment profile allows it and waits for a human where it does not, and every action is recorded against the evidence that justified it.

  • Autonomous triage and investigation

    Every alert taken to a verdict, with the reasoning attached.

    Each alert, from Withstand's own detection or from the tools you already run, is ingested, enriched, correlated against the complete record and reasoned to a verdict: closed, escalated, or contained where the gating policy allows. The first two tiers of the SOC run without a human queue; a person steps in where judgement belongs, with the timeline and the evidence already assembled. Every step of the reasoning is written to the evidence tier and exportable, so an analyst, an assessor or a board can read why.

  • Machine learning

    Behavioural detection at millions of events per second.

    Baselining, anomaly scoring and classification per entity and per protocol, against the analytical store. CPU-class work, trained in Withstand's build environment and shipped as signed artefacts through the same offline channel as software.

  • Generative AI, constrained

    Explains, drafts and ranks, and is never the lead detection claim.

    An open-weight model served on your own GPU tier, restricted to natural-language query, obligation-mapped incident narrative for boards, and response-playbook drafting. Nothing model-related leaves your environment, and your data never trains anyone's models.

From alert to verdict.

What happens to one alert, and what is left behind for the person who looks later.

Alerts from

  • Withstand detection
  • The tools you already run

Ingest

Normalised and deduplicated against the record.

Enrich

Resolved to assets, users, data and models.

Correlate

Joined to what the same actor touched.

Reason

Explanations weighed, benign ones included.

Verdict

  • Closed. With the reasoning attached.
  • Escalated. To a person, with the timeline assembled.
  • Contained. Where the gating policy allows it.
Every step is written to the evidence tier and exportable. The verdict proposes; the core decides what runs.

Decision trail

  1. 1Ingest

    Alert from the identity source: a third-party application granted mailbox read and offline access for a finance user. Deduplicated against two near-identical events in the same minute.

  2. 2Enrich

    User resolved in the entity model: finance, no prior consent grants. Application first seen today; publisher unverified.

  3. 3Correlate

    The same user authenticated from a new location shortly before, with no matching change request. Two signals from one actor inside the hour.

  4. 4Reason

    Consistent with consent phishing followed by mailbox access. Benign explanation considered: a sanctioned rollout. No record of one.

  5. 5Verdict

    Escalated, high confidence. Proposed actions: revoke the grant, expire the session. Environment profile: enterprise IT. Revoking the grant runs automatically; expiring the session waits for a person.

  6. 6Recorded

    Trail written to the evidence tier and exportable. A responder receives the timeline, the entities and the proposed actions.

A representative trail, not a customer incident. Stages and wording are illustrative.

Five source classes, because an adversary moves between them.

Collection is where most platforms quietly narrow their claims. A sovereign environment contains all five, and the platforms you already run are sources too.

  • IT

    Endpoint process, file, registry and network events; server and application logs; identity, privileged access and MFA; network flow and DNS; firewall, proxy and email gateway; hypervisor and storage events. Collected by agent, event forwarding, syslog, agentless pulls and network sensor.

  • OT

    Asset inventory and protocol-level events from PLCs, RTUs, SCADA servers, HMIs and historians; control commands, set-point changes, firmware and logic changes. Observed passively on SPAN or TAP, crossing into the enterprise side through a data diode. Active scanning of OT assets is never performed.

  • IoT

    Device discovery and fingerprinting; camera, sensor, building-management, access-control and medical-device traffic; broker and gateway events. Most devices cannot host an agent, so the value is behavioural baselining against each device's own normal.

  • AI

    Prompts, responses and tool calls through AI gateways; agent actions and privilege use; model registry and deployment events; vector store and retrieval access; guardrail outcomes. Captured as OpenTelemetry-compatible traces and joined to the identity that initiated them and the data they touched.

  • Data

    File and share access audit; database audit logs; classification and sensitivity labels; DLP and rights-management events; removable-media and cross-boundary transfer events. Lineage from source to model to output.

  • The platforms you already run

    Cloud security platforms and specialist OT monitoring tools are consumed as sources, not replaced, and their alerts are taken to a verdict here. Withstand is the sovereign layer beside what you already run, for the networks those platforms cannot serve.

Every vendor now claims sovereign. It is a threshold with four tests.

TestWhat it requiresWhy it matters
OperationalThe platform runs inside your boundary; nothing phones home; updates arrive by controlled media.Any external dependency is an unassessed path into the most sensitive system on the network.
JurisdictionalThe vendor is owned, controlled and answerable inside your jurisdiction.Foreign ownership, foreign capital and foreign legal obligations survive on-premises deployment. Running the software yourself does not change who the vendor answers to.
Supply chainDocumented provenance of every component; imaging and hardening performed in-country; no excluded-vendor parts.Accreditation attaches to specific bills of materials. Supply chain is now a primary attack surface.
AI data governanceYour data never leaves your environment and never trains anyone's models, the vendor's or a third party's.Digital sovereignty has moved past privacy to control over national-interest data and AI training material.

Operational sovereignty means you run the software. Jurisdictional sovereignty means the vendor answers to your law. Only the second is a matter of law rather than trust. Withstand is independently owned, carries no intelligence-community capital, is delivered and hardened in your jurisdiction, and is designed so that inference happens inside your accreditation boundary. It is built to clear all four tests.

Machine learning detects. Language models investigate, explain, draft and rank.

Classical machine learning: detection

  • Enterprise environments generate millions of events per second. Token cost and context limits make generative models the wrong tool for real-time detection.
  • Behavioural baselining, anomaly scoring and gradient-boosted classification run against complete raw data, per entity and per protocol.
  • Models are trained in Withstand's build environment and shipped as signed artefacts. Adaptation on your telemetry runs on your own hardware and never leaves it.
  • Machine learning augments a mature body of detection content. It is never the lead claim.

Generative AI: four constrained jobs

  • Triage and investigation of every alert to a verdict, with each step of the reasoning recorded and exportable. The verdict proposes; the core decides what runs.
  • Natural-language query of the lake in place of complex interfaces.
  • Incident and posture narratives mapped to your regulatory obligations, in language a board can act on.
  • Response playbooks drafted dynamically rather than from rigid templates. Execution follows the gating policy: automatic where the environment profile allows it, human approval where it does not, and a learned policy never chooses containment actions on a control network.

Withstand will never lead with an 'AI-powered detection' claim. Its detection credibility comes from proven content augmented by classical machine learning; generative capability is applied only where it is the right tool. Models are open-weight with published provenance and a model bill of materials, signed alongside each release.

Software on hardware you control, in your jurisdiction.

A signed image on certified hardware or in your accredited private cloud. Single site, clustered, hub and spoke, or one instance per classification domain. Nothing leaves the boundary.

  • Certified hardware

    Your own servers from Withstand's hardware compatibility list, imaged and enrolled with a signed operating-system image, measured boot and drive binding. For agencies bound to hardware panels and estates that already own the metal.

  • Virtual

    The same signed image as a virtual machine in your already-accredited private cloud. The trust posture is reduced and stated as such: the hypervisor is in the trust base.

  • Hub and spoke

    A core instance plus edge collectors and passive sensors at remote sites and OT zones, joined by diodes or constrained links. Collectors hold local evidence if the link is lost and reconcile on reconnection.

  • Classification-separated

    One instance per classification domain, with one-way flows through cross-domain guards where policy permits. Updates, content and models arrive on signed media and are verified against the trust root before use.

A security platform that cannot withstand attack is a liability.

Withstand is engineered on the assumption that it will be targeted. An attacker who reaches the monitoring layer can blind the organisation, alter evidence and hide.

  • Trust root and measured boot

    A signed, immutable operating-system image on certified hardware, with measured boot from firmware to container images. The system refuses to run altered software and can prove what it is running.

  • Immutable evidence

    Retained telemetry and audit logs are written to write-once storage tiers with cryptographic chaining, so an intruder who reaches the platform cannot silently alter history.

  • Least privilege inside the box

    Services run isolated with per-service identities. Administrative access is role-based, multi-factor and fully audited. No shared credentials, no vendor back door.

  • Keys and encryption

    FIPS-validated encryption at rest with keys bound to the TPM or an external HSM where mandated. Crypto-erase supports classified decommissioning.

  • Self-monitoring

    The platform monitors itself with the same detection engine and raises alerts on its own integrity, configuration and access events to a separate, minimal channel.

  • Recovery

    Offline, signed backups of configuration, detection content and models, and documented bare-metal recovery to a known-good state without any external service.

Build the next generation with us.

The next-generation Withstand platform is being built with design partners whose constraints are the specification. If your networks cannot leave, you are who this is for.

Become a design partner