GFlow Workflow Platform · Once approved, it runs itself
AI pre-screens: LLMs judge the risk; low-risk items pass straight through
Humans approve: countersign, add-sign, return anywhere — every Chinese-style approval action
Automation follows: the moment it is approved, booking, notifications and ERP write-back run on rule chains
Built on the Apache-2.0 open-source GFlow Engine (on a RuleGo base), with the GFlow Workflow Platform on top providing process, form, rule chain and AI agent designers.
The engine layer, GFlow Engine, is fully open source (Apache-2.0) and free to embed into your systems; the GFlow Workflow Platform builds a complete out-of-the-box product on top of it.
An embeddable Go approval engine: a rule chain DSL is the process definition, 7 tables hold all runtime state — no separate workflow middleware needed.
Countersign, add-sign, reject, transfer, withdraw — Chinese-style approval semantics are the complete foundation. What others cannot tell you is the automation that kicks in after approval.
The automation node calls rule chains: booking, permission grants, notifications and ERP write-back execute together; AI nodes can even pre-screen the risk before a human signs — all written in the same DSL as the approval nodes.
The aiAgent node hands requests to an LLM: it recognizes amount/reason risk, auto-approves low risk and escalates high risk to humans.
Parallel or sequential countersigning, unanimous or by ratio; with OR-sign the first approval settles it. Rules are stored as JSON on the task row.
Insert approvers before or after mid-flight, or remove extra countersigners — the parent-child task chain maintains itself.
Send a request back to the initiator or any past node; variables and form snapshots travel with it, and the flow stays editable after return.
Hand a task to someone else; after delegation the original owner stays traceable — every delegate step is recorded.
Tasks in the candidate pool (roles/departments) are claimed first-come-first-served, with claim time and handler fully recorded.
Initiators can withdraw in-flight requests; completed tasks can be retrieved for rework before the next node acts on them.
The ccTask node produces CC records; listeners call back into the host app to drive in-app and email notifications.
jsSwitch gates branch on form variables; fork/join runs branches in parallel; inclusive activates only the matching subset.
Embed GFlow Engine into your existing systems, or take away a ready-to-use GFlow Workflow Platform.
For developers. One Go library plus 7 tables embeds Chinese-style approval into any existing system — Apache-2.0, modify it freely.
For enterprises. A ready-made product out of the box: server + frontend + designers, delivered with source — a business admin configures the first process in 30 minutes.
Our in-house process designer: tree structure, node drawers, conditional branches with automatic default routes — business admins write zero code. The form designer is built on the same stack.

Runtime and history archiving on separate tracks: in-flight data stays minimal, and reporting/audit queries hit the history tables without dragging down production. No relational maze — each table is self-explanatory at a glance.
The moment an instance finishes, its rows move from wf_instance / wf_task into wf_hi_* and record elapsed time and conclusions; the runtime tables only ever hold "in flight" rows, while the history tables take any index you need for reports — neither disturbs the other.
Designers, frontend app, approval engine and rule orchestration — four layers, all our own code, no black-box dependencies. Each layer stands on its own: the engine embeds into your system without gflow, and gflow never locks in your data.
No middleware to install, no scaffolding to generate. Create the database, connect it, start an instance — you write business code, not workflow code.
GFlow Engine is open source and free forever; the GFlow Workflow Platform is a limited-time 50% off at ¥7,500 (was ¥15,000) with source delivery — no annual subscription, no per-seat billing, no feature black boxes.
The demo environment is a complete production build: log in with admin / admin123 and walk from form design to the final approval stamp — you will know exactly what ¥7,500 buys.