Pinpoint high-value unstructured data
Keep the human in command of AI
Our unstructured data miner’s patented matching technology gets the precise textual data needed for AI, ML, RPA, BI, Research, or Talent applications using your business language, domain expertise, and industry jargon. It can curate quality training data from large data sets to unleash AI and optimize ML models, extract Business Intelligence and Research data, filter and route emails in RPA, quantify skills and experience for People Analytics, and more. Use the value-added metadata DataScava generates about raw text in your other systems and charting.
For Data Scientists, Data Analysts, Researchers, BI Specialists, SMEs, Business Analysts, and IT
“DataScava perfectly complements existing approaches to unlocking the value of unstructured text data – by helping companies to model higher-level intents and purposes behind the labeling and classification of data – by capturing the abstract topics and themes that represent their own business and subject matter expertise – and by applying both to big data sets real-time.”
-Scott Spangler, Chief Data Scientist, IBM Distinguished Engineer, Author “Mining the Talk: Unlocking the Business Value in Unstructured Information”
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Our Patented Approach
Weighted Topic Scoring
We use three proprietary methodologies to get the relevant data you care about
Weighted Topic Scoring, Tailored Topics Taxonomies, and Domain-Specific Language Processing work together as an alternative or adjunct to traditional Natural Language Processing. They measure, curate, classify, label, filter, and route messy unstructured text data automatically in real time.
DataScava enables a more data-centric approach to business applications, with topic models which reflect the primary areas of focus, flexible topic scoring to encode your organization’s priorities, and customized text processing that mirrors the way people actually communicate in the industry.
How It Works
Faster and more efficient analysis
Our sophisticated algorithm assigns weights to topics based on their importance and relevance within the domain. This advanced scoring function you control based on your interests, priorities, and intents enables you to focus on the most critical topics and discard noise, leading to better insights.
Tailored Topics Taxonomies
(TTT)
Models features and topics within heterogeneous text using specialized taxonomies you can select, create, edit, or import to capture business language and domain expertise, allowing for the highly customized vocabulary and logic necessary for complex document processing.
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Domain-Specific Language Processing
(DSLP)
DSLP incorporates domain-specific knowledge into the language processing pipeline. It indexes the contents of each file using your TTT. It works at the file level to generate weighted topic scores and other metadata, surfacing relevant documents from large datasets.
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Weighted Topic Scoring
(WTS)
Accurately measures and matches topics according to user-defined score thresholds and labels documents into appropriate cohesive categories using heuristic techniques tailored to a specific business purpose, enabling a true human-machine partnership in an ever-changing environment.
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Why DataScava is Different
It’s a new paradigm
- It uses TTT, DSLP, WTS (not NLP, NLU, or Semantics) to find what you’re looking for, not what it infers.
- It ensures cross-collaboration between technical and non-technical people.
- Works top-down through your corpus at the file level, not the sentence level.
- Provides auditable corpus-level statistics that are explainable, transparent, and provable.
- Generates sortable metadata to summarize textual content in a numerical format.
- Measures color-coded topics, highlights key terms in on-topic files, and filters out irrelevant ones.
- Encapsulates your business language and domain expertise in your software on an ongoing basis.
