Transform unstructured documents into knowledge graphs. Extract entities, relationships, and insights from millions of documents with precision.
Turn your document chaos into structured, searchable intelligence — at any scale.
Extract clauses, obligations, dates, and parties from thousands of contracts. Flag risks, compare terms, and build compliance dashboards automatically.
Named-entity recognition across millions of documents — people, organizations, amounts, dates — with configurable confidence thresholds.
Automatically build knowledge graphs from unstructured text. Connect entities, discover relationships, and power semantic search.
Process documents in 50+ languages with the same pipeline. OCR, layout analysis, and NER tuned for each language family.
Sample your corpus, classify document types, and define the extraction schema. We map every field you need before writing a line of code.
OCR, layout detection, chunking, NER, and relation extraction — assembled into a Spark or cloud-native pipeline that scales horizontally.
Fine-tune SparkNLP, LayoutLM, or transformer models on your labeled data. Active learning loops minimize annotation effort.
Plug extracted data into your systems — search indices, data lakes, or knowledge graphs — with quality dashboards and human-in-the-loop review.
Document intelligence is in our DNA. We built DocsTAI, our flagship product, processing millions of pages for enterprise clients across three continents.
Our pipelines handle terabytes of unstructured data daily on Spark and Databricks. Not a prototype — production infrastructure.
Financial documents, legal contracts, medical records, government filings — we've built extraction models for all of them.
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or email directly: fernandrez@iseeci.com