Fieldborne Intelligence
Human-governed AI workflows for technical work that needs explicit provenance, bounded execution, review gates, and auditable outputs.
Designed to keep evidence, limitations, human authorization, and workflow state visible instead of hiding them behind model output.
Evidence in. Governed work. Reviewable output.
Fieldborne organizes consequential AI-assisted work as a bounded workflow rather than an open-ended generation step.
Start from explicit source material and defined inputs.
Break the task into reviewable claims, steps, or artifacts.
Check provenance, support, contradictions, policy, and terminology.
Keep multi-step orchestration within defined limits and stop conditions.
Require accountable authorization where consequential output is involved.
Keep evidence state, review state, and limitations visible.
Generate with controls
Model-assisted candidate output remains provisional until applicable reliability checks and review gates are satisfied.
Work from explicit sources
Source bundles, provenance, citation integrity, and source-support checks for evidence-linked investigation.
Create provisional artifacts
Versioned work products preserve review state rather than silently becoming approved output.
Bounded orchestration
Multi-step coordination with explicit limits, stop-on-block behavior, and no unbounded external authority.
Apply the Reliability Kernel
Claim decomposition, evidence-state assignment, contradiction and policy checks, terminology control, and escalation.
Application-layer controls
Development controls include authenticated sessions, workspace separation, quotas, metadata-only telemetry, credential handling, audit chaining, and backup tooling. These are not represented as independently assessed production infrastructure.
External review status and preserved internal history.
Positive results and limitations are kept in the same record. External review statements are separated from internal tests and benchmarks.
Review → remediation → remediation-verification
A bounded external engineering review cycle has been completed for the referenced Fieldborne baseline. The public claim is intentionally limited to that reviewed scope and does not generalize to unrestricted production readiness, certification, security assurance, or market validation.
Historical internal records remain visible
Internal test and benchmark records retain their original limitations. Corrective passes do not erase earlier failures and are not represented as independent validation.
Evaluate one bounded workflow at a time.
A pilot is structured around a defined workflow, evidence boundary, accountable reviewer, and success criterion before execution begins.
Choose one concrete process to evaluate.
Identify permitted sources and data classification.
Freeze the measurable comparison before the run.
Use the agreed workflow and preserve the record.
Have the accountable reviewer assess the result.
Review evidence against the predefined criterion.
Best-fit pilot work
Evidence-heavy technical workflows such as claim/evidence mapping, benchmark review, technical diligence, provenance review, and validation-readiness work.
What a pilot does not establish
A paid pilot evaluates the commercial usefulness of a specified workflow. It does not constitute scientific validation of QCE, production certification, or validation of every Fieldborne capability.
Qualification first. Agreement and payment only after scope is approved.
The public site does not use an open checkout. A prospective customer starts with controlled intake, then Fieldborne defines one bounded workflow before any commercial commitment.
Submit a sanitized description of the workflow and business need. No payment is due at application.
Confirm the exact workflow, evidence boundary, accountable reviewer, and measurable success criterion.
Prepare customer-specific scope, deliverables, schedule, limitations, and commercial terms for founder approval.
Execute the approved statement of work before substantive pilot activity begins.
Approved engagements are invoiced through Stripe after the agreement and billing details are confirmed.
Begin only after the agreed data boundary, reviewer, success criterion, agreement, and payment conditions are satisfied.
Commercial terms are customer-specific
Pricing, scope, deadlines, deliverables, concessions, and payment timing are not inferred from the website. They are established only for a qualified engagement and approved before commitment.
Invoice after approval
Fieldborne uses invoice-based billing for approved commercial engagements. A website inquiry or intake submission does not authorize a charge, create a contract, or guarantee acceptance.
QCE: Quantum Measurement, Biological Coherence and Collapse Probability
QCE is a coherence-based research framework proposing a testable Collapse Probability Model for evaluating whether structured Biological Coherence Signals correlate with measurable statistical deviations in quantum measurement distributions under blinded, pre-registered, independently replicable conditions.
Research objective
Test whether structured Biological Coherence Signals correlate with measurable statistical deviations in quantum measurement distributions under blinded, auditable, pre-registered conditions.
Methodology boundary
Defined variables, bounded test conditions, pre-registered thresholds, Null Model comparison, blinded observation, timestamp synchronization, reproducible datasets, empirical p-values, Threshold Comparison, and independent replication.
Know the boundary before you submit anything.
Public materials describe the workflow, engineering record, pilot methodology, and QCE research boundary. Restricted, confidential, or sensitive material should not be submitted unless an engagement explicitly authorizes it.