Run every client engagement from one AI workspace
Agencies juggle a dozen clients across inbox, tasks, and calendar. Hugo connects them behind a single AI co-pilot that catches commitments, drafts follow-ups, and surfaces what is slipping — before a client has to chase.
Sound familiar?
The overhead that slows agencies down
Promises buried in email
A commitment made in paragraph three of a thread that nobody re-reads.
Work scattered across tabs
The task is in one app, the email that created it in another, the file in a third.
Deadlines that live in someone’s head
If it never becomes a dated, owned item, it depends on memory — the least reliable system you have.
Context lost on every handoff
Bringing a teammate up to speed on a client means an archaeology dig through old threads.
How Hugo helps
One AI co-pilot across your client work
Mail, tasks, calendar, and files connected so nothing slips between engagements.
An inbox that triages itself
AI sorts what’s urgent, drafts replies, and flags threads that have gone quiet.
Tasks that create themselves
Commitments from email and meetings become tracked work, linked back to the source.
Real availability, not just meetings
Calendar with task and deadline overlays so you see your true capacity per client.
Client context, instantly
Ask what’s happening with any client and get open tasks, recent email, and deadlines in one answer.
FAQ
Questions agencies ask
How is Hugo different from a project-management tool for agencies?
Project-management tools are great for planning, but client work is created in your inbox and on calls. Hugo’s AI sees your mail, tasks, and calendar together, so it can catch a commitment in an email and turn it into a tracked task automatically — instead of you copying it across tools.
Does Hugo work with the tools my agency already uses?
Yes. Hugo connects via OAuth to Google Workspace (Gmail, Calendar, Drive), Microsoft 365 (Outlook, OneDrive), Slack, and Dropbox, and acts with the exact permissions you approve.
Is each client’s data kept separate?
Your whole workspace is isolated at the database level via Postgres row-level security, so organizations never see each other’s data, and your information is never used to train shared models.