OUR PRODUCTS
Data Deliverables Integrated with AI
We integrate Systems Thinking with Machine Learning techniques to provide customized, reusable, and scalable data products with rapid delivery schedules. Check out the Portfolio page for recent projects and case examples.
Data Assets
Instead of one-off reports, we build tools that take raw, messy data and process them through “engines” that process data repeatably and reliably, converting them into audit ready formats.
Decision Support Systems (DSS)
We develop Machine Learning models used for “what-if” analysis and construct visualization tools that make complex data digestible for non-technical users.
Reproducible Analytical Compendiums
We produce a comprehensive package that contains the data, the code, the environment, and the final report. We utilize a security-conscious “Hybrid” archiving strategy, where the user data and final artifacts are vaulted in secure cloud storage, while the source code, environment, and documentation is managed in a private GitHub repository.
Initiation
In this phase, the team lead meets with the client to establish a working relationship. Services and deliverables will be clearly defined as well.
Engagement
Relevant stakeholders are identified and the team convenes to determine project objectives, success criteria, access to data, scope, level of abstraction, timelines, and roles and responsibilities. These are discussed and agreed upon to ensure alignment between the client’s expectations and the project lead’s capabilities.
Specification
The outcome of successful engagement is a specification documented in a Data Analysis Plan (DAP). The DAP outlines the methodology for the research project before any statistical analysis begins. It serves to ensure research integrity, allow for traceability between the problem statement and research findings, and allow for the reproduction of the study by independent parties.
Data Wrangling
This process involves transforming and mapping raw data into a format appropriate for analytics or machine learning. Effective data wrangling ensures that subsequent data models are built on a solid foundation, enabling simplified and intuitive data exploration and analysis, seamless tool integration, enhanced visualization, and improved reproducibility and collaboration.
Data Analysis
Data Analysis uses client data to explore and discover useful information and support decision-making. Organization, logic, technical rigor, and statistical inference is applied to data models to elicit answers to key questions and prove/disprove hypotheses.
Data Visualization
Data Visualization transforms the results of rigorous data analysis into a clear, intuitive narrative that facilitates rapid insight and informed decision-making. This allows stakeholders to grasp difficult concepts or identify new opportunities at a glance without needing to navigate dense datasets.
ABOUT US
TEAM MEMBERS
Meet our experts
Larry Mannings
Owner, Lead Technical Consultant
Larry is an accomplished technical consultant with over 25 years of experience in systems and electrical engineering, specializing primarily in undersea warfare and sonar systems. As a former Naval Officer, he brings a background of strategic leadership, data analysis, and technical consulting, particularly within the defense acquisition enterprise. His core expertise lies in managing complex projects involving classified systems and leveraging data to solve difficult problems. Larry is committed to helping organizations and researchers improve performance and communicate evidence-based results using digital engineering and data science principles.
