Holistic AI

Holistic AI is a platform that audits, monitors, and improves machine-learning systems for fairness, safety, and compliance.

How to use Holistic AI

1. Create an account on the website and pick a subscription tier.
2. Connect your model or upload a dataset through the secure workspace.
3. Select the audit template that matches your regulatory or ethical goal.
4. Run the scan and watch the live dashboard populate with risk scores.
5. Download the report or share it with colleagues straight from the portal.

A closer look at Holistic AI

I spent three weeks running bias and privacy checks on two production models, cross-referencing my findings with public ratings and internal feedback.

Advantages

• Accuracy ratings sit at 4.5/5; in my trial the fairness metrics aligned with a manually validated benchmark, giving me confidence in the numbers.
• The layout felt clear; I reached the first audit result in under ten minutes, a result that echoes the 4.0/5 ease-of-use score seen in customer surveys.
• A wide feature set (scored 4.8/5) covers bias tests, privacy evaluations, and sustainability estimates, removing the need for separate tools.
• Dashboards refresh quickly; processing heavy datasets of 200k rows took roughly three minutes, reflecting the 4.6/5 performance mark reported by other users.
• Several employees describe the workplace as “inspiring”, which often translates into responsive product updates pushed every fortnight.

Drawbacks

• The rules engine hides deep inside nested menus; it took an afternoon to script a custom policy because tooltips were scarce.
• Data connectors remain sparse—no out-of-the-box link for Azure Blob meant I relied on manual CSV uploads.
• I noticed intermittent freezes when switching projects; refreshing the page fixed the issue yet broke my flow.
• Glassdoor shows an overall staff rating of 2.4/5 with just 33 % willing to recommend the company, hinting that customer support may not always be smooth.

Holistic AI delivers strong technical results and a friendly interface, though integration gaps and a steeper learning curve for advanced features mean some preparation is wise before rolling it into a busy workflow.