Resources
Explore practical resources for designing enterprise AI learning systems: organize knowledge, map an agentic workflow, define controls, evaluate it against your own work, and operate the feedback loop after launch.
Start with a browser assessment or worksheet when the workflow is already clear. Use the Blueprint or worked examples when the architecture, authority, or learning signal still needs definition.
Use a resource now
Each card represents a resource that already exists on verdify.ai. Only the AI Control Loop Blueprint includes a public PDF; the other resources remain accessible HTML or browser-based tools.
Interactive assessment
Score one candidate workflow in your browser and surface the control, approval, feedback, and evaluation questions that should shape the next step.
Browser-based. Verdify receives the result only if you submit it.
Run the 3-minute risk checkHTML worksheet
Define what AI may read, draft, recommend, execute, and never touch, along with required approval, evidence, and ownership for each workflow step.
Available as a structured web worksheet.
Use the Control MatrixHTML resource + PDF worksheet
Map the source layer, AI role, control layer, authority, telemetry, private evaluations, feedback, outcomes, and known limits before workflow scope expands.
The resource page explains the method before offering the approved PDF worksheet.
Read and download the BlueprintWorked examples
See how buyer-response, support-triage, and operations-exception workflows connect approved sources, AI assistance, accountable review, private evaluations, and feedback.
Examples of workflow structure, review steps, evaluation, and feedback paths.
Compare the worked examplesFive connected topics
The topics are connected, but they answer different questions. Follow the earliest unresolved topic instead of jumping straight to implementation.
Understand the full loop around an AI model: organizational expertise, approved knowledge, AI-assisted work, authority, operating evidence, outcomes, and feedback.
Map an enterprise AI learning systemOrganize source material, owners, access, freshness, citations, gaps, and correction paths before AI is asked to support consequential work.
Explore enterprise knowledge architectureChoose one repeated, reviewable workflow and define its sources, AI role, prohibited actions, approval path, instrumentation, and handoffs.
Explore agentic workflow patternsDefine organization-specific test cases, reviewer rubrics, control evidence, known limits, and the criteria for an expand, tune, hold, or stop decision.
Define private evaluations and outcome checksTurn reviewer corrections, exceptions, incidents, evaluation results, and real outcomes into controlled changes to the live workflow.
Operate the feedback loopLatest Verdify Updates
Short, linkable notes share what Verdify is testing, changing, and learning across active work and the Public Proof Lab.
Public Proof Lab
Learn why Verdify reports greenhouse stress in temperature and VPD axis-hours, with 48 possible axis-hours in each 24-hour day.
Bring one workflow
Bring the workflow, source evidence, approval path, and decision you need to make. Verdify can help identify whether knowledge architecture, an audit, a workflow sprint, private evaluations, or feedback-loop operations comes first.