The timeline is designed to prevent AI work from drifting into open-ended experimentation. Each phase has a decision, deliverable, owner, and go/no-go point.
Agentra qualifies the workflow before you buy a diagnostic. The goal is to reject bad-fit requests early and select one painful slice worth assessing.
The paid diagnostic converts the workflow idea into a deployment decision document with scope, readiness, ROI, governance, and fixed-price proposal.
The pod connects required systems, designs prompts and rules, defines exceptions, and creates the first working path on real workflow cases.
The workflow is tested against edge cases, low-confidence cases, approver feedback, system-update behavior, and audit expectations.
The workflow enters controlled production with humans in the loop, defined ownership, training, and a plan for AgentOps improvement.
No. The 45-day pod starts only after the diagnostic confirms scope, access, owner availability, and deployment readiness.
Sometimes, but Agentra optimizes for a governed live workflow rather than a fragile speed run.
Agentra will qualify owner, KPI, data, access, approval rules, and deployment readiness before recommending a diagnostic or rejecting the fit.