Sturdy Statistics
Sturdy Statistics combines data analysis with practical software to help organizations extract reliable insights from unstructured text, including customer conversations, support tickets, and research documents. The platform structures text into verifiable, topic-based insights grounded in exact quotes and sources, avoiding the unpredictability of LLMs. Its topic-modeling technology helped insurance intelligence platform DealSurface cut LLM processing costs by 99% while increasing actionable signals by 34%.
- Data & Analytics
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Most valuable business and research insights are trapped in unstructured text—buried in customer conversations, support tickets, product reviews, patient notes, or research papers. Traditional tools force organizations to choose between expensive AI that hallucinates, brittle keyword matching, or manual tagging that doesn't scale, making it difficult to extract reliable, actionable insights from large volumes of text.
Solution
Sturdy Statistics provides a platform that automatically organizes, classifies, and structures unstructured text, enabling users to extract insights instantly. Unlike black-box AI systems, every result is grounded in verifiable facts, with exact quotes and sources surfaced automatically to ensure transparency, accuracy, and trust. The platform handles various text types including customer conversations, support tickets, news articles, financial documents, product reviews, and research publications. Analysts can automatically categorize support cases, track escalating issues, identify emerging themes, monitor news trends, detect feature requests, and organize academic literature—all without manual tagging.
Target Audience
Primary customers are data teams, data leads, and design engineers at companies handling large-scale customer interaction data (such as contact centers, e-commerce, and telecom providers), as well as research assistants and academics in fields like genomics and literature review.
Features
- Text Analysis API that automatically turns raw unstructured text into structured, machine-readable insights
- Results grounded in verifiable facts with exact quotes and sources surfaced automatically
- Capability to crawl citation networks in academic literature and map out research themes across thousands of papers
- Handles any volume of text while avoiding the unpredictability of LLMs
- Incorporates prior biological knowledge and tolerates errors in messy data, as demonstrated in single-cell RNA sequencing applications
- Automatically categorizes support cases, tracks escalating issues, identifies emerging themes, and surfaces answers from call transcripts in minutes
- Topic-modeling technology that indexes documents into granular, measurable topics that can be filtered and analyzed before LLM processing