pipeline.clean
Clean and standardize data formats — dates to ISO 8601, phones to digits, emails to lowercase, currencies to floats.
Auto-detects field types from names and values when rules are not provided.
Fills nulls with sensible defaults. Returns cleaned data with transformation stats.
Costs 2 credits.
pipeline.deduplicate
Remove duplicate records based on specified key fields or full record hash.
When keys are provided, two records are considered duplicates if they have
identical values for all specified key fields. Returns deduplicated data with stats.
Costs 1 credit.
pipeline.redact_pii
Detect and redact personally identifiable information (PII) from records.
Auto-detects emails, phone numbers, SSNs, credit cards, IP addresses, names,
and addresses using field name heuristics and regex patterns. Returns redacted
data with stats on what was found and removed.
Costs 1 credit.
context.build
Build an AI-ready context package from one or more data sources.
Fetches schemas, sample data, and relevant records from each source, then
assembles them into structured chunks optimized for LLM consumption.
Perfect for RAG pipelines. Also indexes data for semantic search.
Costs 3 credits.
context.summarize
Generate an AI-powered summary of a dataset with key insights.
Uses Claude Haiku to analyze the data and produce a narrative summary,
key insights as bullet points, and data quality observations.
Costs 2 credits.
credits.check_balance
Check your current credit balance and subscription plan.
Returns remaining credits and active plan (free, basic, or pro).
Call this before expensive operations to verify you have enough credits.
Free — no credits consumed.