Frequently Asked Questions

Does ADM protect my PII?

Yes — and it does so before your data ever reaches AI. When you upload a file, we automatically scan every text column for personally identifiable information — including email addresses, phone numbers, Social Security numbers, and credit card numbers. Detected values are masked with placeholder tokens (e.g. [PII:EMAIL], [PII:SSN]) before any data is sent to OpenAI. AI never sees your original sensitive values. This masking step runs on our servers and is not optional — it happens automatically on every assessment.

Where are your servers located?

AI Data Maturity is hosted on Google Cloud Platform in the United States. All data processing occurs within US-based infrastructure. No data is transferred to servers outside the United States. Google Cloud Platform maintains SOC 2 Type II compliance, FedRAMP authorization, and HIPAA eligibility — providing enterprise-grade security at the infrastructure level.

How does ADM sample my data?

ADM analyzes a statistically representative sample of your dataset rather than scanning every row. Sample size is calculated dynamically using the Cochran formula (95% confidence level, ±5% margin of error), scaling with your dataset size. Rows are selected using stratified random sampling to ensure proportional representation across data categories, with minimum and maximum outlier values always included to capture edge cases. This methodology was developed in consultation with Bruce Ratner, PhD, Predictive Analytics Consultant.

How does ADM interpret column meaning?

ADM uses a proprietary Deep Dive Analysis that examines the actual values in each column — not just the column name — to determine what the column truly contains. For example, a column named 'src_cd' with values like 'email', 'organic', and 'paid_search' will be described as a marketing acquisition source channel, not just flagged as an abbreviated name. Where values clearly resolve the meaning, the ambiguity flag is removed. Where even the values can't determine meaning, the column is flagged as ambiguous with an explanation.

Is ADM a data governance tool?

Yes — AI Data Maturity is both an AI readiness assessment and a data governance tool. Every assessment produces an ADM Data Dictionary with a complete column-by-column profile of your dataset — types, quality scores, null rates, ambiguity flags, PII detection, and semantic descriptions. This is exactly what data governance teams need to document, audit, and share understanding of their datasets. PII detection is powered by Google Cloud Sensitive Data Protection, providing enterprise-grade coverage of both structured and unstructured PII. ADM is particularly valuable for extending governance to datasets not covered by enterprise tools — ad-hoc files, vendor extracts, analyst exports, and staging datasets that analysts are already connecting to AI tools without documentation or oversight. Unlike enterprise governance platforms that require lengthy implementation, ADM is lightweight — no installation, no contract, no vendor onboarding. Upload a file and get results in under two minutes.

How is the AI Data Maturity Score different from organizational AI maturity models?

Most AI maturity frameworks — from Gartner, MITRE, and McKinsey — assess whether your organization is ready to adopt AI. They measure strategy, culture, talent, and governance at the organizational level. The AI Data Maturity Score asks a different question entirely: is your data ready for AI? These are not the same question. You can have a mature AI strategy and still connect your tools to data that AI cannot reliably interpret. The AI Data Maturity Score operates at the dataset level — column by column — not the organizational level. ADM is lightweight by design — a dataset-level tool you can run in minutes, not a multi-month organizational assessment.

What is an AI Data Maturity Score?

A numeric score from 0–100 that measures how ready a specific dataset is for AI analytics tools. It evaluates every column across four dimensions — data quality, naming clarity, PII risk, and ambiguity — and produces a single score that tells you where your data stands before you connect it to AI.

How is it calculated?

Each column is assessed individually across data quality, naming clarity, and privacy risk. Column scores are weighted and aggregated into an overall dataset score. The result is mapped to five maturity levels: Not AI Ready, Low AI Readiness, Moderate AI Readiness, High AI Readiness, and AI Ready.

What does a score of 60 mean?

A score of 60 falls in the High AI Readiness range. Your dataset is mostly ready — AI tools will perform reasonably well — but specific columns have issues worth addressing before connecting to production AI workflows.

How long does an assessment take?

Most assessments complete in under two minutes regardless of dataset size.

Is my data safe?

Yes. Your file is read in memory and never written to disk or retained after your assessment completes. Before any data is sent to AI, we automatically scan and mask PII values. Only column statistics and masked sample values are sent to OpenAI. The tool is hosted on Google Cloud Platform, encrypted in transit, and uses no cookies.

Is there an enterprise version?

Yes. AI Data Maturity is designed to run inside your own environment. Your IT team points it at your internal AI gateway and your own database and it runs entirely behind your firewall. No data leaves your walls. Contact us at hello@aidatamaturity.com to discuss a pilot.

Why is it free?

We believe every data team should be able to assess their data before connecting it to AI — without a procurement cycle or a sales call. The free tool is the starting point. Pro credit packs unlock larger files, and Enterprise deployments run inside your own environment.

What's the difference between Free and Pro?

Free covers files up to 1,000 rows and 20 columns, no account needed. Pro requires a free account and covers files up to 50,000 rows and up to 100 columns, using prepaid credits.

How do credits work?

One credit covers one assessment that exceeds Free tier limits. Credits are purchased in packs of 10, 25, or 50, and never expire — there's no subscription or recurring charge.

Will I be charged a credit for a small file if I'm signed in?

No. If your file is within Free tier limits (1,000 rows, 20 columns), it runs free even on a Pro account, and you'll see a notice confirming no credit was used.

Which AI does it use?

The assessment is powered by OpenAI's GPT-4o mini — a fast, efficient model well suited for structured data analysis. Enterprise deployments can be configured to use your own internal AI gateway, including Azure OpenAI or compatible model endpoints.

How does it run so quickly?

The assessment runs column analysis in parallel — every column is evaluated simultaneously rather than sequentially. A 20-column dataset triggers roughly 100 API calls, processed in parallel, which is why results arrive in under two minutes regardless of dataset size.