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oozmi

Run your team without filing engineering tickets

Approvals in email, team workflow tweaks in a developer ticket queue, performance numbers in a quarterly export that's already three weeks stale — every functional manager runs three loops the rest of the platform can't see. oozmi puts the approval, the team rule, and the team's numbers on the records the team already writes.

  1. 01 Approvals

    Your queue, on the records being approved.

    A manager opens the Approvals queue. Every item — a PO, an expense, a journal entry, a contract, a vendor onboarding — is the actual record being approved, not a copy in a workflow tool. The manager reads the diff — before and after, side effects, and which policy a rule flagged. One click ratifies and writes back to the source row in one transaction. Delegation is a record on the manager's account: time-bounded, audit-logged. No more amount drift between approval and posting, no more chasing an originator to find out what changed.

  2. Approve the record

    A PO approval writes to the PO. A journal approval writes to the journal. The amount cannot drift between approval and posting.

    Diff and side effects

    Each item shows before, after, and side effects of approval — which rows write, which notifications fire, which thresholds trip.

    SoD on the row

    Segregation of duties is enforced at the record, not at a workflow layer the ERP can't see.

    Delegation as a record

    Out-of-office delegation is time-bounded, audit-logged, and a queryable row — not a Slack message and a hope.

    AI proposes route + flags

    AI Builder proposes routing and surfaces policy-violation flags. The manager ratifies; agent_id is on every AI write.

  3. 02 Team rules

    Change a team rule, no ticket.

    A Head of Sales wants quota credit to split 70/30 between closer and SDR. On the old stack, that was a CRM-admin ticket and three sprints. On oozmi, the Head opens admin, edits the credit-split rule as a record, and ratifies. The new split is live on the next closed-won; reps see updated quota attainment in real time; finance reads the new split for commission accrual. AI Builder proposes routing rules from the team's pattern; the manager reviews the diff and ratifies. Every change writes an audit row.

  4. Team rule = record

    Quota splits, routing, escalation thresholds, leave policy — every team rule is a row the manager edits in admin.

    Live on next event

    A rule change applies on the next closed-won, the next leave request, the next case escalation. No deploy cycle.

    No ticket, no quarter

    The bottleneck for a team-policy change is the manager, not the engineering queue. The org chart moves.

    One-click revert

    If the new rule misfires, revert is one click and one transaction. Risk-free experimentation on team policy.

  5. 03 Performance

    Team numbers from the rows the team wrote.

    A manager opens the team dashboard at 09:00 Monday. Quota attainment, ticket SLA, time-to-close, AR aging — every number reads from the same rows the team wrote that week, not from a Friday export that already disagrees with the GL. The dashboard rolls up by team member, by deal stage, by SLA tier — same row, same number across the manager view, the IC's quota view, and the CFO's commission accrual. No reconciliation, no Friday-night CSV dump.

  6. Read the live row

    Dashboards query the same tables the team wrote that week. No export window, no reconciliation drift.

    IC + manager + CFO agree

    The rep sees the same closed-won total the manager sees, on the same row finance accrues commission against.

    Rolls up, drills down

    Group by team, by stage, by SLA, by region — the underlying row is always the source. No cube, no separate BI tool.

    Anomalies surface live

    AI flags numbers outside the team baseline as they post. The manager reviews; nothing slips to Friday.

AI-assisted reviews Planned

Performance reviews drafted from the rows the team wrote — closed deals, tickets resolved, cycle times, peer feedback — with the manager owning every word that ships.

The substrate is the team's actual work. AI Builder drafts; the manager edits and ratifies. No new performance-management tool, no parallel system of record for ratings.

Production vs Pilot

Production today
  • Approvals on the record — PO, journal, expense, contract, vendor
  • Time-bounded delegation as a queryable record
  • Team rule editing by the manager — quota splits, routing, escalation
  • Live team dashboards from the same rows the team wrote
  • audit_events on every approval, rule change, and team-record write
In pilot
  • AI-proposed approval routing and policy-violation flags
  • AI-assisted performance review summaries from the team rows
  • Anomaly detection on team KPIs (close rate, SLA, AR aging)
  • Forecast-vs-actual variance flagged at the rep level
  • Goal-setting with cascade across team rows

Where it fits

A manager runs the team with Ticketing , Workflows , CRM , AI Builder , and ERP — the same row across every module that wrote it. No second copy, no reconciliation step.

Often read alongside: Operations , People , and Front Office .

Next step — 25 minutes

Bring one team rule you've been waiting on engineering for — we'll change it live.

A quota split your finance team won't recalculate mid-quarter, an approval threshold your CFO won't budge on without a forecast, a routing rule that adds a step every onboarding. Twenty-five minutes. We open admin against a sandbox of your team's data, change the rule, run a sample event through, and show what changes when the rule is a record the manager owns.