Make the next technical decision with evidence.
Work with Nicholas Harris on a scoped evaluation of a scientific dataset, an agent workflow, an inference isolation design or a computational model. Remote consulting, licensing and acquisition conversations are welcome.
Choose a question we can test
- Scientific-data audit. Trace sources, units, uncertainty and conflicting records before deciding what the dataset can support.
- Verification and evaluation. Define an invariant, exercise adverse cases and preserve failures alongside successful runs.
- Integration study. Test a bounded interface or model against an agreed reference and document where the comparison stops applying.
Agree on the deliverable first
Start with a short written problem statement. Together we define the inputs, access boundaries, test method, acceptance criteria and exclusions before agreeing on scope and pricing.
The proposed deliverable is a reproducible evaluation package: the agreed method, source references, runnable checks where sharing rights permit, results and limitations, and a recommendation tied to the evidence. A failed hypothesis remains a useful result.
Inspect the public work
The result pages explain what the lab demonstrated and what remains untested. The evidence and disclosure page distinguishes public artifacts from private implementation. These are examples for evaluation; they do not establish performance in your environment.
For an asset rather than a service, see the licensing and acquisition options. Ownership, dependencies, available rights and evaluation access must be confirmed in diligence before a transaction.
Bring a concrete problem
Send the technical decision you need to make, the available evidence, the intended use and any access restrictions. Please send a public summary first rather than confidential data.
Discuss an evaluationExplore an asset
nick@latticegraph.com · Nicholas Harris · Scottsdale, Arizona · Remote engagements