Collibra Unstructured Data for AI

Collibra is an enterprise data-governance and AI-governance platform described by its maker as an Enterprise AI Control Plane. It governs context and control across data, models, and AI agents, including structured data and governance workflows for AI systems. In the described unstructured-data workflow, Collibra supports AI-assisted taxonomies and metadata tagging with evidence and confidence scores, sensitive-data detection, duplicate and conflict checks, freshness monitoring, scheduled data-slice refreshes, and generation of context files for coding agents.

Deasy Labs is an enterprise platform for curating unstructured organizational data for AI applications. It connects to sources such as SharePoint and S3, OCRs, parses, and chunks files, then builds taxonomies, applies metadata, detects sensitive information, and evaluates file quality and relevance for a stated use case. Users can create data slices by topic, time, quality, relevance, or sensitivity and deliver them to RAG pipelines, search systems, and AI agents, while writing metadata back to source systems. Deasy continuously monitors connected sources, enriches new content, and refreshes datasets to reduce the effects of stale, duplicated, conflicting, irrelevant, or sensitive files. The platform provides APIs and a Python SDK, supports deployment in a customer's own environment, and allows use of customer-provided models and LLM endpoints. The company was acquired by Collibra, according to the video description.

Deasy Labs is an AI data-curation platform with APIs and a Python SDK for preparing unstructured organizational data for RAG systems, search, and AI agents. It connects to sources such as SharePoint and S3, OCRs, parses, chunks, and normalizes files, then builds taxonomies, applies metadata, detects sensitive data, and evaluates file quality and relevance against a use case. Users can slice the enriched corpus by relevance, topic, time, quality, or sensitivity, write metadata back to source systems, or deliver datasets to downstream retrieval pipelines. Data slices are continuously monitored and refreshed as source content changes. The SDK can also generate context files and folder indexes for coding agents, as demonstrated in the video.

DatologyAI is a data curation service for AI model builders. It processes proprietary enterprise data, public web data, and licensed data for pre-training and mid-training on open models or privately deployed foundation models. Its four-stage pipeline cleans poorly formatted, empty, short, or evaluation-contaminated data; curates it by quality, task, and taxonomy; creates synthetic data for task relevance and diversity; and composes sources into staged training datasets. The company also describes seeded rephrasing methods for generating synthetic data at trillion-token scale.

Databricks is a unified platform for data, analytics, and AI. It supports ETL, data warehousing, governance, and AI workflows through a data-centric platform. The videos describe its use for security detection, organizational ontologies, agents, and internal enterprise AI workflows.