While everyone pastes work material into AI on their own personal accounts, nobody can say what actually left. DroFi brings your team's AI use into one place — your team decides what goes out, and what went out can be verified later.
Start with a two-week pilot on one team — everyone keeps the AI they already use.
Banning it is not the answer — a ban only pushes the same work onto personal accounts, so the visibility is what disappears. Governance is not about stopping AI use; it is about deciding what leaves.
People paste internal documents into AI on personal accounts. The organization has no way to tell which material reached which AI, and when an audit request lands, there is no record to produce.
Everyone briefs their AI with a different version of the background, so quality swings from person to person. New joiners rebuild that background from zero — onboarding cost repeats per head.
Carefully tuned prompts and guidelines live only in private chat histories. When someone leaves or hands over, that capability evaporates without leaving anything behind.
How well you write guidelines is what separates organizations that get value from AI from those that don't. DroFi is the container that keeps that skill from evaporating in private chats — so it accumulates, is enforced, and gets reused.
Documents, decisions and guidelines live together per project. The organization's workspace is the reference point instead of private chat threads, and changes are picked up by everyone's AI automatically.
Each person's AI receives context that fits their role and the task at hand. Least privilege stops being a rule about what people may open and starts applying to what an AI gets to see.
Anything marked no-export never rides along to any AI. It isn't filtered out after the fact — what must not leave is never packed in the first place.
Who received what, and through which AI, is written down. When an audit lands, you answer from the record rather than from memory — it can be verified later.
Guidelines set at the organization level reach the AI on every project. No project can override them, so quiet per-team exceptions don't accumulate.
AI usage is metered per person, and you can set a ceiling. Once you can see who spends what, next quarter's cost becomes predictable instead of a surprise.
This is not a tooling migration. Everyone keeps the AI they already use; what changes is where the context is governed.
Bring in the documents and repositories of a project already in flight and you're running. Three things get tested here: does output quality even out, is what left visible in the record, and does no-export actually hold.
Promote what the pilot proved into org-wide guidelines, then decide which context each role receives and what stays no-export. This is where security gets a seat at the table — your team decides what goes out.
Every team you add reuses the guidelines and prompt assets already written, so onboarding gets shorter each time. Usage and delivery records stay in one place as you scale.
Business for teams of ten and up; Enterprise when you need auditing, security review or self-hosting. Compare all plans →
Two weeks with one team is enough to judge it. Tell us your scope and security requirements and we'll take it from there.