Dataset-building
agent platform.
Zero-code schema, multi-element extraction, evidence alignment, and dual QA—define fields in natural language, batch at scale, then review and export production datasets.
Efficiency, quality &
scale.
Storage, processing, intelligent services, and applications—built to lift throughput, close the quality loop, and automate dataset construction end to end.
Zero-code schema
Describe fields and constraints in natural language, then generate a governed schema your team can iterate without a labeling factory.
Multi-element extraction
Pull entities, tables, relationships, and long-form claims in one pass—aligned to your schema and source evidence.
Evidence alignment & dual QA
Every value traces to spans; automated checks plus human review gates keep datasets auditable before they land in BI, ML, or ERP.
Where teams use ThinkExtract
Materials science, chemicals, policy analysis, and curated research datasets—when the deliverable is a governed dataset, not a one-off parse.
See architecture open_in_newDefine · extract ·
review.
Define fields
Start from natural-language field definitions and schema intent—then lock versions for reproducible dataset builds.
Batch extraction & export
Run at volume with evidence alignment and dual QA, then export clean tables for analytics, training data, and operations.
Ship datasets, not dilemmas.
Automation with a quality bar—so your models and dashboards inherit structured data you can defend.