VeerOne america

Applied research

Research that becomes product.

VeerOne studies the parts of AI that decide whether a system works in real work: evaluation, review, interfaces, memory, permissions, release, and improvement. Useful results become products, studios, and deployment methods.

Research library

Methods for the work ahead.

Practical research for teams choosing a workflow, setting a launch standard, governing a deployed system, or replacing an expensive model route.

  1. AI Evaluation Before LaunchA launch decision needs representative task evidence, critical acceptance rules, calibrated review, operational tests, and explicit rollback.Research guide · Updated July 10, 2026 / 6 min read
  2. Model Replacement Matrix TemplateA replacement matrix turns model substitution into a task-specific production change with comparable evidence, economics, and rollback.Research guide · Updated July 10, 2026 / 6 min read
  3. AI Governance for Deployed WorkflowsWorkflow governance turns broad policy into operating rules for model actions, human review, data, changes, incidents, and accountable ownership.Research guide · Updated July 10, 2026 / 6 min read
  4. How to Choose the First AI WorkflowChoose the first workflow by balancing operating value, reviewability, available inputs, adoption friction, and the cost of being wrong.Research guide · Updated July 10, 2026 / 6 min read
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Working studios

Inspect the work, not the claim.

AuraOne research becomes an interface, a control, or a working studio. Ideas earn their place by becoming clear enough to inspect and useful enough to operate.

Research you can operate

Each studio turns a research question into a working interface, control, or review flow. These are research prototypes and code-native workflow diagrams — not customer deployment evidence.

Code-native research prototype

Rubric Studio

Author criteria, calibrate judgment, compare changes, and export a review-ready rubric.

Evaluation designRubric StudioReview ready

Criteria authoring

Validation set

Safe refusal behavior

Decline unsupported requests and name the missing evidence.

Rubric dimensions

Grounding
Evidence requiredRequired
Safety
Unsupported action blockedRequired
Clarity
Reviewer judgmentScored
Validation thresholdAll required checks
Review readinessReady for review

Research to release

A question becomes a working system.

Each loop ends with something a team can run, and the next loop starts from what running it taught us.

  1. 01

    Frame the question

    Name the workflow decision the research must improve.

    A useful question

  2. 02

    Make it tangible

    Turn the hypothesis into an interface, rubric, trace, or working prototype.

    Something the team can inspect

  3. 03

    Test the boundary

    Use examples, criteria, review, and failure cases instead of demo confidence.

    Visible evidence

  4. 04

    Put it to work

    Move the pattern into AuraOne, a studio, or a deployment playbook.

    A reusable system

  5. 05

    Watch real use

    Return operating evidence to the next research question.

    A tighter loop

Inspect AuraOne, the product surfaceRead the research guides

Inquiry

Have a workflow the research should touch?

Discuss a research direction