Score dataset citation practice quality and standards

Assess and score data classification with actionable recommendations

Classify dataset columns and detect format-based PII.

Detect and classify PII, PHI, PCI, and credentials in text — SSN, credit cards, emails, medical codes.

Generate data classification schemes

Score data classification coverage and accuracy

Score data classification for zero trust policy enforcement

Suggest data cleaning steps for datasets

Measure missing values, required-column coverage, and dataset completeness.

Check data completeness across all fields in a record set. Returns per-field completeness and overall grade.

Agent-ready data transformation, validation and sync intelligence

Agent-ready data transformation, validation and sync intelligence

Check schema compatibility, breaking changes, required fields, and migration risk

Monitor data contract freshness from schema age, producer SLA, consumer impact, pipeline lag, and incident history

Live data deduplication data for agents and LLMs.

Generate data dictionaries from schemas

Detect distribution drift between baseline and current datasets.

Detect statistical drift between reference and current data distributions

Detect feature distribution drift between training and production data using PSI-based scoring.

Detect data drift between reference and production datasets using PSI score and mean shift analysis.

Detect statistical drift between reference and production datasets

Score input data distribution drift from monitoring data

Calculate cloud data egress costs from transfer volumes

Encryption rubric for your data categories.

Advise on encryption requirements by data type — PII, financial, credentials, logs.

Enrich records with timestamps, metadata, derived fields and record hash.

Enrich_companys Data Enrichment data instantly — optimized for agents, LLMs, and MCP workflows.

Enrich company and contact data with firmographics, technographics and social profiles

Design data enrichment pipelines with external API integrations

Data Ethics Intel API — intelligence and analytics for AI agents.

Data Ethics Intel API — intelligence and analytics for AI agents.

Score data collection and use ethics compliance

Export data to any format CSV JSON Excel

Live data extraction data for agents and LLMs.

Generate a data extraction plan with selectors and tools based on detected page type.

Score scraped data extraction quality: field completeness, suspicious values, type validation and schema compliance.

Generate realistic fake test data

Map data flows between systems

Score platform data flywheel improvement loop quality

Convert data between formats including JSON, CSV, XML and YAML

Deterministic JSON ⇄ YAML ⇄ TOML conversion + format detection.

Format data — numbers, strings, JSON pretty-print and encoding transformations. Built for AI developer agents.

Live data freshness evaluator data for agents and LLMs.

Evaluate data freshness and recommend update frequency for datasets

Data Gov Intel API — intelligence and analytics for AI agents.

Score customer data hygiene from accuracy and freshness

Parse and validate imported data files

Join two datasets on a common key

Auto-label datasets for ML training with confidence scores and human review flags

Classify data lake PII zones from table names, sample fields, lineage, access role, retention, and sharing scope