AIGRADE

AIGRADE is a specialized service dedicated to the independent evaluation and certification of artificial intelligence systems. It establishes trust in AI by performing rigorous, third-party audits that assess models for reliability, transparency, fairness, privacy, and governance. The entire process is aligned with international standards like ISO/IEC 23894 and is designed to be SOC2-friendly, making it an essential tool for companies, especially in regulated industries like fintech, that need to validate their AI and provide clear evidence to investors, regulators, and customers.

The service provides a comprehensive AIGRADE Trust Report, a weighted 100-point score, and a final letter grade from AAA to B. A key deliverable is a verifiable digital badge that can be embedded on websites or in documentation to publicly demonstrate an AI system's certified level of trustworthiness.

How to use AIGRADE

The AIGRADE process is structured into a clear, five-step workflow to guide clients from initial assessment to continuous improvement:

1. Evaluate: AIGRADE conducts rigorous tests across five key pillars: reliability, transparency, fairness, privacy, and governance. This involves analyzing robustness, accuracy drift, security posture, explainability, and evidence trails.
2. Rate: Based on the evaluation, each pillar receives a score from 0 to 100. These scores are then weighted to compute an overall grade (AAA–B), providing a clear, standardized measure of the AI's trustworthiness.
3. Certify: Upon completion, clients receive an official AIGRADE Trust Report in both PDF and JSON formats, along with the verifiable digital badge and a remediation checklist.
4. Re-evaluate: As AI models and data evolve, AIGRADE offers optional periodic re-evaluations to ensure the certification and evidence remain current and accurate.
5. Support: The service includes clear guidance for continuous improvement, helping clients address identified gaps and work towards achieving a higher trust grade.

Core Features of AIGRADE

• Third-Party Independent Audits: Provides unbiased and objective evaluation of AI systems.
• ISO/IEC 23894 Alignment: The methodology is aligned with recognized international standards for AI risk management.
• Comprehensive Five-Pillar Evaluation: Assesses reliability, transparency, fairness, privacy, and governance.
• Weighted Scoring & Grading: Issues a transparent 100-point score and a simple letter grade (AAA–B).
• Verifiable Digital Badge: A shareable and embeddable badge to publicly showcase AI certification.
• Audit-Ready Reporting: Delivers a detailed Trust Report (PDF/JSON) and remediation checklist for regulators and stakeholders.
• Secure & Non-Invasive Process: Works with a scoped evidence pack, avoiding the need for direct access to production keys or sensitive data.
• Re-evaluation Pathway: Supports ongoing certification as models are updated.

Use Cases for AIGRADE

AIGRADE is particularly valuable for organizations deploying AI in critical or regulated sectors. A prime example is a fintech company's credit-risk model. Before deploying, the model underwent an AIGRADE audit. The evaluation identified gaps in robustness, fairness, and privacy. After implementing the recommended controls, the system earned an 'A' grade. This process resulted in a 41% reduction in hallucinations and a 19% improvement in explainability. The CTO noted, "The audit made our release board-ready. The badge is now part of our pitch."

Advantages of AIGRADE

The primary advantage of AIGRADE is its focus on building verifiable trust. It provides clear, audit-ready evidence that satisfies investors and regulators. The process is built to evolve, allowing companies to maintain certification as their AI systems change. By focusing on safety, privacy, and fairness—not just accuracy—AIGRADE helps companies deploy more responsible and reliable AI solutions, ultimately enhancing their brand reputation and user confidence.

Pricing and Plans

The website offers a "Start free scan" option, suggesting a freemium model or an initial complimentary assessment. However, detailed information about specific pricing tiers or subscription plans is not provided on the website. For a full certification quote, prospective clients would need to contact the AIGRADE team directly.

FAQs

What aspects of an AI system does AIGRADE evaluate?

AIGRADE conducts a comprehensive evaluation covering robustness, accuracy drift, privacy, security posture, governance, fairness/bias, explainability, and evidence trails. These are grouped into five key pillars, and the results are consolidated into a single letter grade and individual pillar scores.

How is the final AIGRADE score calculated?

Each evaluation pillar is assigned a score from 0 to 100 based on tests and evidence provided. AIGRADE then applies a weighting to these pillar scores to compute the final overall grade (ranging from AAA to B). This grade is presented alongside a verifiable badge link.

Does AIGRADE require direct access to our model or production data?

No, direct access to production keys is not required. The evaluation is performed using a scoped evidence pack, which includes artifacts, redacted data samples, and execution traces. For highly sensitive cases, the review can be conducted in a secure, isolated environment or via the client's own Virtual Private Cloud (VPC).

What is the typical duration of an AIGRADE audit?

The timeline depends on the scope. A focused review can take approximately 5 to 7 days. A full certification process, which may include time for remediation of identified controls, typically takes 2 to 3 weeks.

What deliverables are provided after the certification process?

Upon completion, you receive a comprehensive package including an official Trust Report (in PDF and JSON formats), detailed pillar scores, a remediation checklist with actionable recommendations, and a verification badge URL that can be embedded in your website or documents.

Is it possible to get an AI model re-evaluated after updates?

Yes, AIGRADE offers a re-evaluation option. This allows you to re-score your model after implementing new controls or deploying a new version, ensuring that your certification badge and supporting evidence remain current and reflect the latest state of your AI system.