Specialists you hire. Sign-off you keep.
Sharkflow ships with named AI agents that do real jobs — accounting, HR, support drafts, platform maintenance. They propose; your team decides. Try the live demo — that division of labor is enforced by the product, not promised in a policy.
The record
Your decisions land here — attributed and append-only.
Four specialists, one policy: propose, never execute.
Molly
Accountant
Reads statements and receipts, drafts the entries, matches bank lines, and prepares GST workpapers.
- Every proposal arrives with evidence and a confidence score
- Stops at your review queue — nothing posts unapproved
- Asks instead of guessing when a document is ambiguous
Samantha
HR manager
Watches leave, claims, and attendance exceptions; chases responses and prepares decisions with context.
- Daily sweeps surface what needs an HR decision
- Two-party absence flows keep employees in the loop
- Approvals always stay with your team
Emily
Assistant
The front door: answers questions across your data, drafts email replies, and routes work to the right specialist.
- Lives in a chat pane on every page, aware of where you are
- Questions come back as tappable options, not essays
- Delegates to Molly and Samantha when the work is theirs
Felix
Platform engineer
Watches the platform itself — investigates failures and proposes narrow fixes as reviewable patches.
- Every proposed fix is a before/after diff you can read
- Applies nothing without an explicit human approval
- Keeps the machinery boring so your team never sees it
Every piece of AI work follows the same four steps.
Control is a feature, not a setting.
- Guardrails you can read
- When an agent holds back, it says why — “Blocked: invented price” — with the rejected draft visible, not hidden.
- Spend caps per task
- Every agent runs under cost limits. A runaway task is terminated, not billed.
- An append-only record
- Approvals, rejections, costs, and outcomes land in an audit trail that cannot be quietly edited.
- Dangerous actions gated
- Anything that sends, posts, or deletes requires an explicit human confirmation — by design, not by policy document.
Automation without giving up oversight.
That's the whole thesis. Sign in and watch the review queue prove it.