An operator control plane for licensed virtual-asset businesses
One operating application across custody, compliance, payments and ticketing: queues, maker/checker, exceptions and evidence, with no rip-and-replace.
Evidence & Audit
Articles tagged Evidence & Audit.
Quality and non-conformance management with AI-assisted root cause
Manufacturing quality applications for non-conformances, CAPA, inspections and traceability, where AI helps engineers find patterns faster.
Third-party and supplier risk reviews that keep up with the supplier base
Third-party risk applications that tier suppliers, run due diligence, extract evidence from documents and track issues, with reviewers deciding.
Field service for utilities: work orders, crews and completion evidence
Field-service applications for energy and utilities: job packs, crew dispatch, mobile completion, safety checkpoints and AI-assisted planning.
Operational risk management that runs on live data, not quarterly spreadsheets
Risk registers, KRIs, incidents and control testing as one connected application, with AI that helps risk teams see patterns earlier.
AI in the SOC: alert triage and investigation with evidence
Security operations applications that use AI to enrich, summarize and prioritize alerts while analysts keep the decisions and the evidence trail.
Document intelligence in regulated workflows: extraction with verification
Extracting data from documents with AI is easy to demo and hard to trust. How to build extraction with validation, confidence and human review.
Agentic automation with human checkpoints
How to use AI agents in enterprise workflows safely: bounded tools, read-before-write, explicit approvals and an audit trail of every step.
Compliance evidence should be produced by the workflow, not assembled for the audit
Regulatory evidence collection and control attestation as an application: controls mapped to evidence, captured as work happens, reviewed by owners.
AI model governance should be an application, not a policy document
Model inventory, evaluation, deployment approval and monitoring as one governed workflow, so AI governance produces evidence instead of meetings.
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