APPLIED AI R&D

Agents and tools grounded in working systems

Economic agents, reusable numerical models, and embedded computation. Our research connects explicit plans to specialized tools and keeps the evidence behind each capability visible.

RESEARCH PORTFOLIO

Four connected research programs

Explore the prototypes, their current evidence, and the work still ahead.

ECONOMIC DECISION SYSTEMSPrototype

Agent Factors & Economic Agents

A working research system that turns economic and forecasting questions into typed computational graphs, with reviewable plans, tool calls, and output artifacts.

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COMPUTATIONAL INFRASTRUCTUREPrototype

Mojo Numerical Tools

Reusable numerical packages for statistics, factor models, simulation, and conditional distributions, connected to Rust research workflows through explicit data and library interfaces.

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SIMULATION & EMBEDDED COMPUTATIONPrototype

Drone Systems Research

An early computational workbench for drone-related numerical kernels, starting with Rust reference calculations and an ARM assembly implementation checked under QEMU.

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REAL-WORLD OPERATIONSPrototype

Landscaping Operations Agents

Research into bounded agents that help service businesses plan work, allocate operating resources, and evaluate decisions without replacing accountable operators.

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INSIDE THE PROJECTS

Implementation, evidence, and next steps

Numerical building blocks with explicit model boundaries

The Mojo packages include moments and covariance estimators, principal-component analysis (PCA), ordinary least squares and vector autoregression (OLS/VAR), stochastic simulations, and conditional normalizing flows. Shared model contracts and C-compatible library boundaries let Rust graph tools reuse these numerical routines.

Current capabilities

  • Moments, covariance, PCA, and OLS/VAR models
  • Stochastic simulation and conditional-flow inference
  • Shared model contracts and Rust library bridges

Evidence & limits

PCA has a deterministic CPU reference; its GPU model currently reports a CPU fallback. Conditional spline flows provide CPU reference inference and differentiation, while their graph-facing library interface exposes inference. Training-only fitting and frozen held-out transforms are explicit parts of the factor-model workflow.

Next research steps

Specialized GPU kernels, broader training orchestration, and complete forecasting validation remain development work. The shared kernels package is a scaffold with a planned sparse-matrix multiplication kernel; it is not an implemented accelerator library.

Backend status, training intervals, buffer ownership, and artifact provenance stay visible. GPU execution is described only where implemented.

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OPERATIONS RESEARCH

Landscaping Operations Agents

Research into bounded agents that help service businesses plan work, allocate operating resources, and evaluate decisions without replacing accountable operators.

  • Estimate and job-context preparation
  • Crew, route, equipment, and service planning
  • Scenario-based operating and procurement research

Operator approval remains required for customer commitments, purchases, scheduling changes, and other external actions.

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R&D COLLABORATION

Bring a domain problem or computational bottleneck

We welcome research partners who can define the operating question, relevant evidence, and what a useful result would look like.

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