From a mailbox
A mailbox queue watches an inbox. The AI classifies, drafts and routes; nothing sends until a human approves it.
Work moves through queues. A person or an agent pulls one item at a time, rules decide when it may move, and a human approves anything that leaves the building. Everything on this page builds on that.
All three land on the same queues and the same rules — just from a different door.
A mailbox queue watches an inbox. The AI classifies, drafts and routes; nothing sends until a human approves it.
Enrichment queues run a saved query against your data sources and attach the result to the work item before anyone looks at it.
Drop a PDF, scan or attachment on a queue; extraction fills the workflow's form, ready for a person to review.
Pull-based work. A person — or the AI — asks for the next item and gets exactly one, leased and locked. No cherry-picking, no dropped work, natural load-balancing across a team.
Compose queues into a process with routing and business rules. WYSIWYG forms capture structured data; validation and conditional logic keep every work item clean and complete.
Auto data-gathering. A dedicated queue runs saved queries and data-source lookups against a work item, attaching the context the AI needs to decide — before a human ever sees it.
Multi-tenant from the ground up. Invite members, scope roles, and isolate each organization’s workflows, queues and data. Bring a team; keep everyone in their lane with RBAC.
Quota enforcement built into the seam. Plans and limits are set per organization during early access; scaling up never changes how anything works.
A project layer over your queues: dependencies, milestones and critical-path scheduling so the AI can manage by project logic — not just work items one at a time.
A single self-contained desktop agent executes anything that touches an outside system — using credentials that never leave your device. The cloud decides what happens; your machine is the only thing that acts.
Drop in a document. The AI ingests it, fills the workflow’s form, enriches it from your data sources, routes it to the right queue — and waits for a human before anything leaves the building.
The AI reads the document and extracts fields, entities and intent.
Query-enrichment queues attach related records and context automatically.
Rules place the work item in the correct queue with the right priority.
A human confirms; only then does the external action fire.
See the flagship in production — WorkflowHub building itself →
Recent releases, all live today — and all visible in the real screenshots.
Throughput per week, per-stage cycle times (p50/p85), aging with stuck-item flags judged against each stage's own history, and cost per finished item — computed from your runs, no BI project required.
Point-and-click reports — filter, group, split, chart (bars, stacked, lines), custom fields as columns, CSV export. Saved reports run server-side: paste one URL into PowerBI or Excel and it refreshes against live data.
HMAC-signed webhooks on create, route, finish, field change and note — from every mutation path including the rules engine — with retries, a delivery log, and SSRF protection. Built for n8n-style orchestration.
Operating guides and documents in a searchable, taggable gallery — plus a zoomable knowledge map that shows what connects to what and where your documentation is thin.
Drag-and-drop upload, one-click download, inline preview for images, PDFs and text — plus reference-only links for commits and PRs, so evidence travels with the work item.
One-click theme presets — two light, five dark — previewed live across the whole app, plus your name, logo and brand colors per environment.
We're onboarding early-access teams: your workspace, your first workflow designed with you, and the local agent for anything that reaches outside systems.