Products, business-system integrations, learning platforms and operational tools. Each story explains the problem, our contribution, how it was implemented and what has been checked.
Product engineering, business integrations and working prototypes. Each story identifies our contribution, the implemented workflow and the checks behind its current status.
Product engineering in partnership with Accelerare.
Agents need more than a prompt to do useful work. Ascape brings tools, workflow steps, approvals and run history into one workspace.
VexWorks product engineering.
Crux connects AI sessions and local models across computers, phone and watch, while each device retains its own tools and sign-ins.
Founder-led work under Revenue Optimization Group, LLC, before VexWorks was formed.
A computer-vision demo that detects beach rental units, classifies occupancy and maps their positions as the layout changes.
Founder’s Ascape integration and access-control contributions to the existing StudioLens product.
StudioLens is a venture research and portfolio workspace. The founder’s contribution connects its company context and account permissions to Ascape, where governed agents and workflows can run.
Engineering of the Academy learning frontend, practice labs and progress tools.
A role-based learning platform for using AI agents in everyday work. Guided paths, simulated labs and progress exports help learners and team leads move from an introduction to a scoped pilot in Ascape.
Independent software project for product research and purchasing preparation.
A workspace for project briefs, product research, comparison and purchasing preparation. It keeps selected offers, quantities, retailer rules and the evidence behind a comparison together.
Project notes updated .
Research has its own status. These efforts sit alongside the delivered project work.
Internal engineering work includes a supervised local-model coding router: bounded source tasks, executable acceptance checks, recorded responses and a final review before completion. Archived evidence records a supervised DGX workflow; controller corrections were needed. This supports private-AI evaluation and integration work, while unattended reliability remains a research question.
Discuss local AIAn onboarding process for people new to quantum computing. The work is still in development.
Discuss quantum onboardingTell us what needs to work, what you have today and where the current approach falls short.