DataScava is an advanced unstructured text mining solution that pinpoints high-quality data with user-controlled business and domain language. It evolved from TalentBrowser, where we patented deterministic methods to structure, measure, filter, and curate nonlinear content — without requiring training data or manual labeling. By enabling you to harness your expertise — working standalone or alongside other solutions — DataScava helps you:
* Structure, measure, filter, match, route, sort, and rank raw text automatically
* Feed explainable, auditable outputs into AI, LLMs, ML, RPA, BI, Research, TA, and BAU applications
* Create domain-specific data pipelines upstream, audit and measure results downstream
* Get structured, high-quality datasets and outputs you can act on
* Stay in control with results you can see, refine, and trust
How It Works:
DataScava applies three complementary methodologies that focus on your business language and expertise, not generic language models:
DSLP | Domain-Specific Language Processing – Structures and measures user-defined key terms exactly, with no disambiguation
TTT | Tailored Topics Taxonomies – Import, build, or select vocabularies and data types that reflect your expertise
WTS | Weighted Topic Scoring – Prioritize outcomes with transparent, explainable scoring that reflects your rules and thresholds
Together, they form a patented approach we call “Profile Matching of Unstructured Documents” — modeled after a contour profile gauge carpentry tool, because DataScava measures language based on your priorities. The DataScava Difference:
Less time, more accuracy – Filters and categorizes automatically
Precision at scale – Numeric results you can trust across industries
Transparency over black-box AI – See and audit exactly why a file matched
Scalable and domain-specific – Refine vocabularies, taxonomies, and scoring
Human in Command – Automation works alongside your expertise
