Confident AI vs Mindgard
Confident AI
confident-ai.com
Mindgard
mindgard.aiSide by side
| Figure | Confident AI | Mindgard |
|---|---|---|
| Price from | $200/mo | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 4 | 0 |
| Spec score · AI Red Teaming Tools | 8.4 (#5) | 7.5 (#15) |
| Data protection | Confident AI states that data is encrypted at rest, protected by TLS in transit, and covered by SOC II and HIPAA compliance. | Mindgard says customer data is encrypted in transit using at least TLS 1.2 and encrypted at rest in Microsoft Azure using AES. |
| Integrations | Confident AI offers Python and TypeScript SDKs, OpenTelemetry, and more than 20 framework and gateway integrations. | Mindgard says it supports APIs, CI/CD, and Burp Suite, including a Burp Suite extension. |
| Red teaming | Confident AI provides red-team testing for safety vulnerabilities and adversarial attacks. | Automated red teaming emulates attacker workflows to find exploitable vulnerabilities across models, tools, data, and workflows. |
| Security | The documentation states that Confident AI is HIPAA compliant, offers SSO and customizable roles and permissions, and supports self-hosted deployment. | Mindgard’s security overview states that it holds SOC 2 Type 1 for all services and hosts all services on Microsoft Azure. |
Plans
Confident AI
- FreeFree
- Starter$200 a month
- Team$2,000 a month
- EnterprisePriced on request
In their own words
Confident AI
Confident AI is an AI quality platform for evaluating applications during development and monitoring them in production. Teams can experiment with prompts, models, and parameters, run automated regression evaluations in CI/CD, and assess results with more than 50 metrics. Production tracing records inputs, outputs, latency, tokens, and execution spans, while live alerts indicate declining quality. Red-team testing addresses safety vulnerabilities and adversarial attacks. The platform supports Python and TypeScript SDKs, OpenTelemetry, and more than 20 framework and gateway integrations. APIs cover prompt versioning, dataset creation, trace ingestion, project provisioning, and governance policies. It is available through web and API access, or can be self-hosted in AWS, Azure, or GCP using Docker; setup typically takes 1–2 weeks. The free plan includes two seats, one project, five weekly test runs, and 1 GB-month of trace spans. Paid plans start at $200 a month.