Deployed Labs helps leadership teams decide which workflows are worth applying AI to and what it will take to put those systems into production. The strategy covers ownership, technical requirements, and the order in which the work should happen.
Identify the workflows worth pursuing and define what success should look like for each one.
Define who owns the AI initiative and how responsibilities are divided across the teams involved in delivery.
Map how the AI system will connect to existing data, applications, and tools.
Choose the model approach based on the performance, cost, and latency requirements of the workflow.
Set the access requirements, human approval points, and process for reviewing AI activity.
Prioritize what should be built first and what needs to happen before each workflow moves into production.
Agentic AI is useful when a workflow requires the system to complete several steps or take actions through other tools. Deployed Labs defines what the agent can do on its own, where a person needs to approve an action, and how those actions will be reviewed.
Tell us which workflows you are considering for AI and what work has already been done. Deployed Labs will propose a strategy scope based on where the project stands today.
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