Your data
Does ADM protect my PII?
Yes. Every column is scanned for PII — emails, phone numbers, SSNs, credit card numbers — before anything reaches AI. Detected values are replaced with placeholder tokens. This runs automatically on every assessment.
Where are your servers located?
Google Cloud Platform, US-based only. GCP maintains SOC 2 Type II, FedRAMP authorization, and HIPAA eligibility.
Is my data safe?
Yes. Files are read in memory, never written to disk, and not retained after the assessment. Only masked column statistics and sample values reach OpenAI. Encrypted in transit, no cookies.
How the score works
What is an AI Data Maturity Score?
A 0–100 score measuring how ready a dataset is for AI — based on data quality, risk, privacy risk, and column name ambiguity, evaluated column by column.
How is it calculated?
Each column is scored on data quality, risk, privacy risk, and column name ambiguity, then aggregated into one score mapped to five readiness levels.
What does a score of 60 mean?
High AI Readiness — mostly ready, but specific columns need attention before production use. The full scale: 0–19 Not AI Ready, where fundamental quality and governance issues must be resolved first; 20–39 Low AI Readiness, significant remediation needed before results are reliable; 40–59 Moderate AI Readiness, a foundation exists but specific columns need attention; 60–79 High AI Readiness, mostly ready — address flagged columns and you’re set; and 80–100 AI Ready, well-structured for AI analytics with minor cleanup at most.
How does ADM sample my data?
A statistically representative sample, sized with the Cochran formula (95% confidence, ±5% margin of error) and stratified to keep categories proportional, with outliers always included. Methodology developed with Bruce Ratner, PhD.
How does ADM interpret column meaning?
It reads actual values, not just column names — a column named src_cd with values like “email” or “organic” gets identified as a marketing source channel, not just flagged as cryptic.
Why can’t I just send my data to AI directly?
You can — the question is whether the answers come back right. Dashboards work because an analyst supplies the missing layer: what each column means, which numbers to trust. AI doesn’t get that layer. Send data without it and results get unpredictable. ADM is that layer.
How is this 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 it's for
Is ADM a data governance tool?
Yes. Every assessment produces a full data dictionary — types, quality, null rates, ambiguity, PII — useful for documentation and audit, especially for files outside your governance tools’ reach. No installation or contract required.
Which industries is this for?
Any industry that connects a dataset to an AI tool — healthcare, lending and credit, insurance, accounting and finance, legal and compliance, government, HR, sales and CRM, marketing, retail and e-commerce, supply chain, and real estate. The problems ADM catches aren’t industry-specific: sensitive data nobody flagged, null-heavy fields read as zero rather than unknown, and columns whose names don’t match their contents turn up everywhere. It is also run as a standing data governance check, and as a pre-export check before data leaves the organization.
What do I do once I have the score?
Every assessment comes with five Starter Prompts — ready-to-paste questions with the dataset’s context already built in, so you don’t have to explain your data before you can ask it something. They carry the same understanding as the Dataset Briefing, in the form you use rather than the form the AI reads.
Does ADM fix my data?
No. ADM is the pre-flight check; you’re still the pilot. It doesn’t change your data or make the call for you — it tells you what to check before you connect a dataset to AI: where sensitive data lives, where a column is likely to be misread, and where missing data will get silently filled in with a guess. The decisions stay yours.
What it costs
Why is it free?
Every data team should be able to check their data before connecting it to AI, without a sales call. Pro credit packs unlock larger files; Enterprise runs inside your own environment.
What’s the difference between Free and Pro?
Free: up to 500 rows / 20 columns, no account needed. Pro: up to 50,000 rows / 100 columns, using prepaid credits.
How do credits work?
One credit per file assessment that exceeds Free limits — a file within Free limits always runs free, even on a Pro account. Database connections always use one credit per connection, whatever the size of the table. Credits never expire and there is no subscription.
Will I be charged a credit for a small file if I’m signed in?
No. Files within Free tier limits always run free, even on a Pro account.
Is there an enterprise version?
Yes — it runs entirely inside your environment, behind your firewall, pointed at your own AI gateway and database. Contact hello@aidatamaturity.com to discuss a pilot.
What runs it
How long does an assessment take?
Under a minute. A measured run on an 18-column file takes about 15 seconds from selecting the file to the score on screen.
Which AI does it use?
OpenAI’s GPT-4o mini. Enterprise deployments can be configured to use your own AI gateway, including Azure OpenAI.
How does it run so quickly?
Columns are analyzed in parallel — a 20-column file triggers roughly 100 simultaneous calls, which is why results arrive in under a minute.