Agent architecture
Tools, permissions, retrieval, state, memory, orchestration, human approvals, failure handling, audit records and monitoring are designed around the workflow.
Commercial investigation
Build AI agents around explicit work, authority and evidence.
PlanckCyber engineers agents as controlled software systems - not autonomous demonstrations detached from operating responsibility.
Evaluation
Test sets, expected outputs, policy constraints, adversarial cases, latency, cost and escalation behavior are defined before production release.
Human authority
Material actions and uncertain exceptions retain explicit human ownership. Autonomy is bounded by risk, reversibility and evidence.
Security
Secrets, data access, prompt injection, tool abuse, excessive agency, output handling and supply-chain dependencies are reviewed as system risks.
Production readiness
Deployment requires accountable ownership, observability, incident response, change control, rollback and a funded operating model.
Decision standard
Define the evidence before the commitment.
Do not imply guaranteed savings, security, accuracy, regulatory compliance or implementation outcomes. Any price is planning guidance subject to scope and contract.