Data Cleaning & Validation for AI Agents

Enables AI agents to deterministically profile, clean, normalize, and validate tabular data, including locale-aware numbers, dates, text encoding, IDs, and CSV/XLSX/JSON inputs, while flagging ambiguous values instead of guessing.

Enables agents to run zero-config entity resolution on messy records from CSVs, tables or databases, automatically choosing match rules and clustering duplicates into stable entities with per-field provenance. Exposes the resulting identity layer through dozens of tools for deduping, merging/splitting records, auditing changes, and answering Customer 360 questions.

Enables AI clients to inspect and safely modify Salesforce and HubSpot data through read-only and permission-gated tools for deduplication, normalization, enrichment, assignment, job-change detection, record creation, mass updates, and segmentation, with auditable and reversible writes.

Enables agents to query imported dated CSV/JSON exports to cross-check values across sources, trace observations to raw files, and surface anomalies such as missing fields, disappeared records, and collection gaps before concluding.