Accelerate your R&D process and transform messy, unstructured data into clean, validated data with our hybrid approach of AI tooling and mathematically grounded analysis.
Our team combines the mathematical foundations, engineering discipline, and domain experience needed to deliver results that hold up under scrutiny.
Our team of mathematicians and computer scientists solve complex data challenges at the intersection of advanced mathematics and AI. We use mathematical techniques to bridge technical gaps in scientific fields, always prioritizing transparency, scalability, and interpretability.
Custom algorithm development across machine learning, optimization, and signal processing, delivering tailored solutions to complex analytical challenges.
Reveal multiscale structure in data that other methods miss and generate robust descriptors that can appear independent of orientation or parameterization.
Get rigorous model assessment, validation, and verification services to ensure AI systems meet the highest standards of reliability and trustworthiness—essential for managing risk and maintaining accountability.
Robust data pipelines that process real-time data, transforming raw streams into clean, analysis-ready inputs. Time-sensitive signals are captured, structured, and delivered with the reliability and low latency that modern analytical systems demand.
Custom agentic workflows with user-defined functions and specialized model development, deployed to scale.
Visualizations and dashboards ranging from mapping spatial patterns to tracing dynamic relationships over time. Designed to make the structure of data immediately interpretable.
Geomprompt is a geometry-driven approach to prompt enhancement that detects ridge-like features and guides SAM without task-specific training data, capturing the majority of relevant segments at a fraction of the prompt density of standard approaches.
Dispers provides a simple interface to Distributed Persistent Homology.
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