Uncover hidden structure in your data
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.
What sets us apart
Our team combines the mathematical foundations, engineering discipline, and domain experience needed to deliver results that hold up under scrutiny.
- Mathematical Depth — We are mathematicians who bring rigorous theory, not just off-the-shelf models, to every engagement.
- Interpretability by Design — We prioritize methods that can be explained and validated, so your stakeholders and compliance teams understand what the system is doing and why.
- Domain-Adaptive Solutions — We don't apply generic pipelines. Each solution is tailored to the structure of your data, your operational constraints, and your decision environment.
- End-to-End Ownership — From raw data ingestion to deployed models, we cover the full stack so nothing falls through the cracks between teams.
- Trusted in High-Stakes Contexts — Our work has been validated in environments where errors carry real consequences.
Delivering practical solutions
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.
Algorithm Development
Custom algorithm development across machine learning, optimization, and signal processing, delivering tailored solutions to complex analytical challenges.
Topological Data Analysis
Reveal multiscale structure in data that other methods miss and generate robust descriptors that can appear independent of orientation or parameterization.
Safety Engineering for AI
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.
Data Engineering
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.
Agentic Tooling
Custom agentic workflows with user-defined functions and specialized model development, deployed to scale.
Visualization
Visualizations and dashboards ranging from mapping spatial patterns to tracing dynamic relationships over time. Designed to make the structure of data immediately interpretable.
Our work in action
Dimension estimation and stratification finding for point clouds
Dimmer estimates the local dimension of point cloud data and recovers its stratification — a partition into locally consistent, lower-dimensional pieces — revealing structure that single-number dimension estimates miss.
Automating ridgeline identification where labelled data falls short
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.
Distributed Persistent Homology
Dispers provides a simple interface to Distributed Persistent Homology.
Contact us
Have a question or want to work with us? Send us a message and we'll get back to you.