CTO/CPO · 10+ years experience

Product strategy.
Hands-on engineering.
Applied AI.

I’m Will, a product-minded technical founder building AI systems around real data and real workflows. I take problems from customer discovery through architecture, implementation and evaluation.

12+ products from zero to marketScaled products from $0–10M ARRHundreds of thousands of usersExited founderForbes 30 Under 30, 2024

Selected work

From ambiguous problem
to working system.

What I built, the decisions behind it,
and what happened next.

01 / Applied AI · Geospatial intelligence

Vale

Founder & Engineer · 2026

Hundreds of millions of geospatial data points ingested

PlanningTerrainHazards
AWS ingestion worker
PostGIS → SiteReportField-level evidence · coverage · confidence
CLI / MCPGrounded answers
System architecture

Making fragmented land data usable by AI.

Built an AI land-intelligence system spanning hundreds of millions of geospatial data points, with agent-operated ingestion on AWS and cited site reports served through PostGIS and MCP.

MCPGrounded generationEvaluation design
  • 296 English authorities ingested
  • 6 MCP tools exposing 34 site-profile fields
  • 62% → 89% rubric pass rate

Internal evaluation: 100 cases across 25 authorities.

Read the case study
02 / Venture building · Energy infrastructure

Metris Energy

Co-founder & CTO / CPO · 2023–2025

Tens of thousands of devices · millions of telemetry records

OEMs & devices5-min telemetry
Normalized energy dataBilling · performance · fault detection
System architecture

Building an energy startup from zero to market.

Co-founded a venture-backed energy startup, owning product strategy, engineering, hiring and technical sales. Took the platform from MVP to market and early signs of product–market fit, connecting tens of thousands of devices and ingesting millions of telemetry records.

Company buildingProduct strategyTechnical sales

Co-founder & CTO / CPO · secondary share sale

Read the case study
03 / Embedded delivery · Data architecture

Berrien Springs Public Schools

Fractional CTO · 2025

SIS + 2 LMSsCurriculumState data
One source of truthStudent · learning · reporting data
Admin workflowsPerformance benchmarks
System architecture

Turning fragmented student data into useful decisions.

Replaced dozens of linked Google Sheets with a unified data architecture connecting student information, two learning management systems, curriculum and state reporting. As sole engineer and fractional CTO, built bespoke administrative tools and student-performance benchmarks across district schools and state data.

Systems integrationData architectureCustomer delivery
  • SIS, two LMSs, curriculum and state reporting integrated
  • Dozens of linked Google Sheets replaced
  • Student-performance benchmarking across district and state

Delivered for a district with $100M in annual funding.

Read the case study
04 / Embodied AI · Robotics

Spice Terminator

Team project · LeRobot Worldwide Hackathon · 2025

24-hour build · top 30 global winner

Teleoperated demonstrations
GR00T N1.5 / SmolVLAFine-tuned for plate cleaning
SO-101 armDepth + RGB cameras
Web controlSynced 3D view
Training and control workflow

Teaching a robot to clean a plate.

In 24 hours, our team built an autonomous cleaning pipeline using an SO-101 arm, RealSense depth camera and RGB camera. We fine-tuned NVIDIA GR00T N1.5 and Hugging Face SmolVLA, and built a web platform connecting robot control, live camera feeds and a synchronized 3D view.

Vision-language-action modelsRobot control3D visualization
  • Top 30 globally · 3,000+ participants across 44 countries
  • Best Novelty Prize · London hackathon hosted by SoTA
  • Recognized by NVIDIA Robotics

Hugging Face LeRobot Worldwide Hackathon · June 2025.

Read the case study

How I work

Close to the customer.
Deep in the implementation.

01 / Understand

Find the useful problem.

Work with customers and domain experts to understand workflows, test demand and define a scope worth shipping.

02 / Build

Own the system.

Connect models, tools, APIs and data. Build the application and the infrastructure needed to make it useful.

03 / Evaluate

Learn from failures.

Separate retrieval failures from answer failures, inspect evidence, and use evaluations to guide changes.

More experience

A decade of building
and shipping products.

All work ↗

Python · TypeScript · React / Next.js · PostgreSQL / PostGIS · OpenAI & Anthropic APIs · MCP · AWS / GCP

Let’s talk

Building AI that works
in the real world.

I’m exploring Applied AI and Forward Deployed Engineering roles where I can work closely with customers, write code, and own delivery.