Access isn’t adoption. People default to the workflow they already know, aren’t sure which tool fits, or don’t want to stop and figure out the right prompt. So valuable, AI-suitable work keeps getting done by hand — quietly, all day, across every team.
They don’t recognize the moment as an AI opportunity.
They don’t know which approved tool actually fits.
Stopping to find the right prompt costs more than just finishing it by hand.
Discover, decide, activate and learn — continuously improving how AI gets applied to work.
Recognizes a valuable AI opportunity from the workflow context already in front of the employee — before they’ve thought to look for one.
Weighs whether AI should help here, and which approved capability — tool, model and resource — actually fits the task.
Surfaces a lightweight, contextual recommendation at the right moment, with a one-click handoff and the prompt already prepared.
Learns from what happens next — accept, dismiss, ignore or override — and gets better at when to intervene and what to recommend.
Actaiv is designed to recognize different kinds of work where AI could meaningfully help — then determine whether to intervene and which approved capability fits.
Comparing accounts, reports, research or information by hand can signal an opportunity for deeper AI-assisted analysis.
Actaiv recognizes the opportunity.
Notes, research and scattered information often need to become a summary, brief, communication or first draft.
Actaiv identifies where AI can help.
Different work can call for different approved AI capabilities. Actaiv determines which available option best fits the task.
Actaiv decides what fits.
Actaiv considers the work, available AI capabilities, organizational constraints and employee behavior to determine the best way forward — including when AI shouldn’t be used at all.
Actaiv can consider the approved AI platform, model and reasoning level appropriate for the task — rather than treating every request the same.
Platform · Model · Reasoning level
Usage, capacity, availability and cost can inform how much AI resource a piece of work should receive.
Usage · Capacity · Cost · Resource level
Actaiv can account for changing availability, switch between approved resources when appropriate, and carry relevant context across tools.
Switching · Load balancing · Context handoff
Employee responses and organizational patterns help Actaiv improve future decisions while giving administrators intelligence into where AI is helping, being ignored, or creating friction.
Behavioral learning · Admin intelligence
Actaiv isn’t designed to maximize AI usage. When the existing workflow is already the better path, that should be a valid decision too.
Actaiv works across the AI your company already has. It understands the capabilities and constraints of approved tools and helps determine which resource fits the work — without asking employees to navigate the ecosystem themselves.
Every recommendation gets a response, whether or not the employee means to give one. Actaiv uses all four to decide when to speak up next, and what to suggest.
Confirms the recommendation was useful.
Flags this moment, this time, as not worth interrupting for.
No response at all — a quieter signal that still counts.
Employee picks a different tool — teaching Actaiv what actually fits.
Actaiv is being designed to use the minimum permitted workflow context necessary to recognize valuable AI opportunities — without becoming an employee surveillance system.