How Vigilens compares to the rest.

Two axes, not a feature list.

Every platform here can be placed on two axes. The first is what it governs: the company as a whole, or each AI system individually. The second is when it checks: once, at audit time, or continuously, as the system changes.

Company-level, point-in-time tools (Vanta, Drata, OneTrust) certify that an organisation met a control set on the day it was assessed. That is the right model for SOC 2 and ISO 27001, where the thing being certified, your security posture, changes slowly. It is the wrong model for an AI system, which can retrain, drift, and change behaviour between one audit and the next. A certificate issued in January says nothing about the model you shipped in March.

AI-aware tools (Credo AI, Fairly AI, Saidot) do treat AI systems as first-class, which is a real step forward. But their assessments are still workflow-driven and periodic: you run an evaluation, you get a report, the report ages. The gap between "assessed" and "actual" opens again the moment the assessment ends.

Vigilens is the only platform here that governs at the AI-system level and verifies continuously. Regulations are encoded as machine-executable rules that run as checks in your CI/CD pipeline. Every commit produces a fresh verdict against the evidence that exists right now. Compliance stops being a document you assemble for an audit and becomes a property of the pipeline that is either true or false at any moment you care to look.

This is the inward-out difference.

Vanta protects your systems from the world. Vigilens protects the world from your AI systems, by watching what they actually do in production, commit after commit.

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Feature comparison

Scoring: 1 = limited or not present, 5 = native and complete. Competitor scores reflect publicly available product documentation as of August 2026. Vigilens covers eight frameworks as views over one continuous evidence record, so a team is never buying a single-framework tool.

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Vigilens vs Vanta

Vanta automates SOC 2, ISO 27001, and HIPAA for cloud-native companies, and it does that well. Its evidence collection is strong and its self-serve experience is polished. For a seed-stage company that needs SOC 2 as a gate to close its first enterprise deal, Vanta is a reasonable default.

The difference is the unit of governance. Vanta certifies the company: it answers whether your organisation, as a whole, met a security control set at the time of assessment. Vigilens governs the AI system: it answers whether a specific model, at a specific commit, is behaving within the bounds its documentation claims. These are not competing answers to the same question, they are answers to different questions. A Vanta SOC 2 report tells a buyer your company handles data responsibly. It tells them nothing about whether your model drifted last week.

Vigilens also covers SOC 2 itself, as one of eight frameworks over a single evidence record, so the framing is not "Vanta does SOC 2, we do something else." It is "Vanta checks your company once a year, we verify each AI system every time it changes." For teams shipping AI under regulatory exposure, that continuity is the point.

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Vigilens vs Drata

Drata is a leader in continuous SOC 2 and ISO 27001 automation, and its evidence collection across engineering tools is genuinely excellent. For a team whose primary need is SOC 2 or ISO 27001 readiness, Drata is hard to beat, and Vigilens does not try to.

Two differences matter. First, unit of governance: Drata continuously monitors your company's security controls, but the object it governs is the organisation, not the individual AI system and its behaviour. Vigilens treats each AI system as the unit, with its own classification, its own controls, and its own live verdict. Second, Vigilens encodes regulations as machine-executable rules that run as checks in the pipeline and produce deterministic verdicts. Drata applies rules internally but does not expose them as code you can see run against a specific model at a specific commit.

Drata is the right choice for security-compliance-first teams. Vigilens is the right choice when the thing you must keep honest is the AI system itself, continuously, and when medical device frameworks like ISO 13485 and EU MDR are in scope, which Drata does not cover.

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Vigilens vs Credo AI

Credo AI is purpose-built for AI governance and, unlike the SOC 2 platforms, it treats AI systems as first-class objects. Its policy and framework mapping is strong, and it supports a broad range of AI governance frameworks. Of everyone here, it is closest to Vigilens on the unit-of-governance axis.

The difference is the other axis: time. Credo AI's governance is workflow and assessment-driven. You run a policy review, you get a result, and that result reflects the system as it was assessed. Vigilens runs continuously as code in CI/CD, so the verdict reflects the system as it is right now, at the latest commit, against evidence collected automatically from GitHub, Jira, MLflow, and Datadog. Vigilens verdicts are also deterministic: no language model decides pass or fail, the rule does, and the result traces back to the exact clause and the exact evidence.

Credo AI suits large enterprises that want broad AI governance policy management. Vigilens suits teams that need that governance to be live and executable rather than periodic, and that need deep coverage of a specific regulated domain such as medical devices.

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Vigilens vs OneTrust

OneTrust is a comprehensive GRC and privacy platform used by large enterprises, with broad framework coverage and strong record-keeping. For privacy programmes and traditional GRC, it is market-proven.

It sits at the far company-level, point-in-time corner of the map. OneTrust was not built for AI systems, its rules are managed manually rather than executed as code, and its engineering integrations are shallow. It records that policies exist; it does not continuously verify that a running AI system behaves as those policies require. Vigilens is the inverse: narrow by design, deep on AI systems, and continuous.

OneTrust remains a strong choice for privacy and enterprise GRC running alongside AI work. Vigilens is the choice when the obligation is to prove, continuously, that specific AI systems behave within spec.

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Vigilens vs Saidot

Saidot is an EU-native AI governance platform from Finland with genuine AI governance depth, and being EU-native is a real advantage over US tools for European buyers. On jurisdiction, Vigilens and Saidot agree.

The difference is architecture and cadence. Saidot's evidence collection is largely manual and its assessments are workflow-driven rather than continuous. Vigilens integrates directly with GitHub, GitLab, Jira, Confluence, Datadog, and MLflow to collect evidence automatically at every release, encodes rules as executable checks, and produces a fresh deterministic verdict each time the system changes. Both take the EU seriously. Vigilens is the choice for engineering teams that want compliance to run continuously in the pipeline rather than as a periodic governance exercise.

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Vigilens vs Fairly AI

Fairly AI focuses on AI model governance, fairness evaluation, and responsible-AI assessment, and its model-level capabilities are real, particularly around fairness metrics.

The difference is scope and continuity. Fairly AI evaluates models at assessment time; Vigilens verifies AI systems continuously against a full regulatory obligation set, with evidence drawn from the whole engineering stack rather than model-evaluation tooling alone. Vigilens verdicts are deterministic and traceable to the clause, and the framework coverage spans eight regulations and standards, including the medical device depth (ISO 13485, EU MDR) that a fairness-focused tool does not address.

Fairly AI is useful for model-level fairness and responsible-AI work. Vigilens is the choice when you need continuous, system-level regulatory verification across frameworks.

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Vigilens vs Trail

Trail focuses on AI lifecycle governance with structured control libraries and partial automation, and it is one of the more technically mature options here, with some rules-as-code capability and EU-native positioning.

Vigilens differs on continuity and depth. Trail automates parts of the compliance workflow; Vigilens runs the full obligation set as executable checks continuously in CI/CD, producing a deterministic verdict at every commit rather than at lifecycle checkpoints. Evidence collection is fully automated across the engineering stack, BYO-LLM is available for teams that cannot send data to third-party models, and the medical device frameworks are covered in depth. Trail is a credible AI lifecycle governance tool. Vigilens is the choice when the requirement is continuous, machine-executable verification of each AI system.

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From verification to foresight.

Everything above is about the present tense: is this system compliant right now. The layer Vigilens is building next is the future tense. Every verdict, every artifact, and every drift event becomes part of a living record of how a system behaves over time, and that record is being taught to look forward, to flag the incident before it happens. No tool in this comparison does this, because none of them hold a continuous, system-level record to learn from in the first place. Continuous verification is the foundation; prediction is what it makes possible. This layer is in development.

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Frequently asked questions

What is the difference between Vigilens and Vanta?

Vanta certifies your company against a security control set at a point in time, mainly for SOC 2 and ISO 27001. Vigilens verifies each AI system continuously, at every commit, against whatever frameworks apply. Vanta governs the organisation once a year; Vigilens governs the AI system every time it changes. Vigilens also covers SOC 2, so the two are not limited to different frameworks, they operate at different units and different cadences.

Is company-level compliance not enough for AI?

It is necessary but not sufficient. A company-level certificate says your organisation met a control set on the assessment date. It cannot capture the fact that an AI system retrains, drifts, and changes behaviour between audits. System-level continuous verification exists to close exactly that gap.

How is Vigilens different from AI-native tools like Credo AI or Fairly AI?

Those tools do treat AI systems as first-class, which matters. The difference is cadence: their assessments are periodic and workflow-driven, so the result ages the moment the assessment ends. Vigilens runs as executable rules in CI/CD and produces a fresh deterministic verdict at every commit, with evidence collected automatically from your engineering tools.

Which platforms are EU-native?

Vigilens (Norway), Saidot (Finland), and Trail are EU-native. Drata, Vanta, Credo AI, Fairly AI, and OneTrust are US-headquartered. EU-native platforms are built for EU jurisdiction from the outset, which matters for data sovereignty and regulatory alignment.

Does Vigilens cover medical device AI?

Yes, in depth. ISO 13485 and EU MDR are covered natively, alongside EU AI Act, GDPR, ISO 42001, ISO 27001, NIST AI RMF, and SOC 2. This medical device depth is a differentiator none of the general-purpose GRC or AI-governance tools in this comparison match.

Can I bring my own LLM?

Yes, on the Govern and Enterprise tiers, so customer data and model outputs stay in your environment. No other platform in this comparison offers Bring Your Own LLM.

How does Vigilens decide pass or fail?

Deterministically. A rule is evaluated against evidence, and the verdict is one of four: PASS, CONTRADICTS, PARTIAL, or INSUFFICIENT. No language model decides the outcome, and every verdict traces back to the specific clause and the specific evidence.

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