
Donely proposes to build, operate, and white-label an AI employee that handles the day-to-day work an IT admin does inside Linewize - so the admin never has to log in to the content filter again. Qoria sells it. Donely runs it.
School IT admins spend 20–40% of their day inside the Linewize content filter - triaging teacher requests, tuning policies, verifying safeguarding alerts, and chasing bypass attempts.
Donely will deliver a white-label AI employee that does this work for them. It lives in the messaging tool the school already uses (Teams, Slack, Telegram, WhatsApp), drives the Linewize UI on the admin's behalf, and only pings the admin for a one-tap approval when a human decision is required.
Phase 1 ships in weeks using front-end automation over the existing Linewize UI - no Qoria engineering required. Phase 2 swaps the browser layer for direct MCP / API calls as Qoria ships them. Same product, same UX, lower latency.
We are asking for: NDA, a Linewize QA tenant, and 1–2 pilot districts.
One person, often one per campus, sitting between teachers, students, parents, principals, and Linewize. Their day is a steady stream of "unblock this for my class," "why is this getting through," and "the test starts in 10 minutes."
They also own the rest of the school network. Every minute they spend triaging filter requests is a minute not spent on the things only a human IT admin can do.
The admin keeps working where they already work. The agent does the filter work in the background and surfaces a clean approve/decline only when policy or judgement requires it.
Microsoft Teams, Slack, Telegram, WhatsApp. The admin gets a DM, taps a button, the work is done in Linewize.
Day 1: computer-use over the existing Linewize web app - login, navigate, create policy, set expiry, log out.
If the school has a hard rule (no YouTube during class), the agent auto-declines and tells the teacher why. Admin never touched.
Temporary unblock → time-bound policy → reminder before expiry → reply to teacher when done. One thread, zero context-switching.
Past requests, prior IT responses, classroom calendars, and risk signals - used to suggest the right action, not just any action.
When Qoria opens backend APIs, Donely swaps the browser layer for direct calls. Same persona. Lower latency. No re-training the admin.
Worked example - a teacher requests an unblock 10 minutes before a test.
“Need khanacademy.org unblocked for Yr 9 Maths, 11:30.”
Reads the request, checks the school's rules and history, plans the Linewize action.
Telegram DM: “Allow Khan Academy for Yr 9, 11:30–12:30?” [Approve] [Decline]
Logs in as the admin, creates a time-bound policy, sets auto-expiry, signs out.
Replies to the teacher in Teams. Notifies admin: done. Reminds before expiry.
Three scenarios, click-through, across the real Linewize UI, Microsoft Teams, and Telegram. Built so Hansa, the Head of Engineering, and the CPO can each walk it themselves in under two minutes.
Shipped as a managed service under the Linewize brand. Qoria sales enables it per customer in one click - no engineering involvement to onboard a district.
We are explicit with Qoria leadership: no backend APIs exist today, and we are not asking for any. Phase 1 proves the product on the front end. Phase 2 swaps the integration layer underneath, with zero change to the IT admin's experience.
Nothing requires Qoria engineering effort. We are asking for access, not work.
So we can sign NDA, scope, and have a working pilot in front of a real district before the new school year.
Reply with approval to proceedDonely is a venture-backed team based in San Francisco, building the AI-employee layer for the tools schools and businesses already pay for. We've shipped computer-use agents into production - on real workloads, not demos - and we're bringing that to Linewize.
