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SPECIFICTION
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Giskard vs RAMPART

Giskard

giskard.ai

RAMPART

microsoft.github.io

Side by side

FigureGiskardRAMPART
Price fromFree—
Free planYes—
Free trial——
Open sourceYes—
WebYes—
Windows—Yes
macOS—Yes
LinuxYesYes
APIYesYes
Self-hostedYes—
Plans published40
Spec score · AI Security Testing Tools8.6 (#5)7.3 (#21)
LicenseThe public giskard-oss repository is marked Apache-2.0 licensed.The GitHub repository identifies RAMPART as MIT-licensed.
PurposeGiskard describes its platform as a way to find vulnerabilities in AI agents before they reach production.RAMPART is a pytest-native safety testing framework for agentic AI applications.

Plans

Giskard

  • FreeFree
  • Open-sourceFree
  • EnterprisePriced on request
  • ProfessionalPriced on request

Giskard pricing →

RAMPART

No plans published.

RAMPART pricing →

In their own words

Giskard

Giskard provides tools for assessing AI agents before production, with coverage for prompt injection, data disclosure, inappropriate content, hallucinations, contradictions, and omissions. Its Hub performs black-box testing of conversational text-to-text agents available through an API endpoint. An assessment produces a structured report with a deploy-or-fix verdict, ranked vulnerabilities, and functional scenarios; passing agents receive a Giskard Label. Giskard describes a remediation process in which its team qualifies findings, discusses severity, prioritizes issues, opens workflow tickets, and reruns tests to check fixes. Enterprise evaluation options include adversarial probes, domain-specific datasets, RAG quality metrics, customizable metrics, and human review interfaces. Deployment choices include on-premise, private cloud, and SaaS. Giskard lists EU or US data residency, access controls, audit trails, identity-provider integration, encryption, and a zero-training policy, alongside GDPR, SOC 2 Type II, and HIPAA compliance. The free plan includes a local open-source library, basic vulnerability scanning and RAG evaluation, community support, and best-effort maintenance.

Visit giskard.ai

RAMPART

RAMPART has no write-up on Specifiction yet; its figures are above.

Visit microsoft.github.io