Sprawl
Agents from five vendors, no common language, nobody in charge.
The governed AI agent platform
Build agents
with words.
Run them
with control.
Turn plain prompts into teams of AI agents — deployed into your tools, governed by your rules, and monitored with a human approving every critical step.
Open-source runtime available today.
Platform in development. See what’s next ↗
DESCRIBE THE OUTCOME
“Find candidates for this role. Check the evidence. Prepare a shortlist. Ask me before contacting anyone.”
↳ Outreach pausedYour approval comes first
PROMPT → DEPLOY → GOVERN → MONITORHumans stay in charge ↓
Why Stageflow
Agents are easy to build.
Hard to run.
Getting one agent to do a task is the easy part. Knowing what a team of agents is doing — and keeping it accountable — is where the real work begins.
No audit trail
Who did what? At what cost? A useful result should come with answers.
No control
Without permissions, limits, and approvals, a capable agent can still take the wrong action.
One platform. Four pillars.
From promising agents
to accountable work.
Describe the outcome, connect the work, and decide its boundaries. Stageflow’s platform is being built to keep creation and control in the same place.
Prompt
Describe the work.
Get the agents.
Create a team from plain words, without writing code. Give each agent a role and define what needs your approval.
YOUR INTENT → A SHARED PLANDeploy
Meet the work
where it happens.
Connect agents to email, the web, and your own systems. Move beyond a conversation into a defined workflow.
AGENT ROLES → CONNECTED TOOLSGovern
You set
the boundaries.
Policies, permissions, and limits define what agents can do — and where a person must make the call.
CLEAR RULES → HUMAN GATESMonitor & control
See the work.
Own the decisions.
Follow activity and per-agent costs. Inspect the evidence and approve critical steps before they happen.
VISIBLE ACTIVITY → ACCOUNTABILITYPlatform direction, not a claim that every capability is live. View the build status ↗
How it works / An interactive product preview
Plain words. A clear plan.
Your final call.
You describe the outcome. Stageflow turns it into focused agent roles and a route for the work. You follow the evidence and decide what moves forward. Explore a software delivery example below; the same control model underpins business verticals like SavvyHire.
01 / Give the work a shape
Your intention becomes a plan.
Start with the result you need. In Workshop, shape the roles, tasks, and checks that will take it there.
In this run: plan → implement → review → ship02 / Keep the context intact
Every handoff carries the evidence.
The next agent receives a focused task and a structured result. You can open the artifact and see exactly what moved forward.
Under the hood: typed handoffs and attached artifacts03 / Check before advancing
A failed check changes the route.
A missing test sends the work back for repair. The workflow advances only when its declared checks pass.
Under the hood: verification and explicit repair routes04 / Make the call
Your judgment is part of the workflow.
The run pauses with its evidence ready. Review what changed, approve the next step, or request another pass.
Try the approval controls in the preview.05 / Make it repeatable
A useful result. A route you can reuse.
The run leaves a record of its work and decisions. Keep the workflow in your catalog, version it with your code, and use it again.
Under the hood: portable YAML and inspectable run historyStageflow / agent workspacePRODUCT PREVIEW
csv-export-ship
DRAFT WORKFLOWplan
implement
review
ship
WORKSHOP / AUTHOR
tasks/add-csv-export.yamlattached
stages/csv-review.yamlconfigured
IMPLEMENT → REVIEW / HANDOFF
implementation.artifactready
{
"task": "add-csv-export",
"changed": ["reports/csv"],
"evidence": "csv-review.md",
"next": "review"
}A structured handoff keeps the change, evidence, and next task together.
Inspect the handoff principle
Stage definitions declare the outputs they produce and the inputs they accept. Artifacts remain attached to the run.
REVIEW / VERIFICATION
CSV escapingPASS
Character encodingPASS
Large-file streaming testREPAIR
review → implement → review
Add the missing test, then verify again.
Add the missing test, then verify again.
The failed check has a declared recovery path.
INBOX / HUMAN CHECKPOINT
Ready for your review.
The repair is complete and verification passed. Review the artifact before releasing the next stage.
csv-review.md3 checks passed
CATALOG / REUSABLE WORKFLOW
◇
Ready for the next run.
The workflow, artifacts, and decision history stay connected. Start the next task from the same reviewed route.
csv-export-shipcatalog entry
plan · implement · review · ship4 stages
Explore the runtime ↗Illustrative run · Explore each step · No repository connected
The same thread connects your intention, the agents’ work, and the decisions you make along the way.
Agents you can answer for
Every action logged.
Every cost visible.
- A full audit trail
See who did what, when, and what changed. Keep decisions attached to the work they affect.
- Human approval gates
Pause critical actions until the right person makes the call. An agent’s confidence is not your consent.
- Per-agent cost tracking
Know where spend goes and set limits around the work. Activity and cost visibility are in build; policy controls are planned.
Sourcing agent
$0.18Candidate evidence attached to the run.
Screening agent
$0.12Shortlist prepared for recruiter review.
Outreach held for approval
PAUSEDNo messages sent. A recruiter decides what happens next.
Agent spend · $0.30 / $1.00 example limit
Evidence → decision → action
Evidence → decision → action
Concept view · Fictional activity and costs, not pricing.
Built around real work
We don’t sell generic agents.
We sell complete verticals.
Meet SavvyHire, our AI recruiting product for small agencies. It connects the whole workflow — from a new role to a recruiter-approved shortlist and follow-up. People keep the relationships and the final call.
SAVVYHIRE / PROPOSED PILOTFrom a new role
From a new role
to the next conversation.
Bring the brief, research, review, and follow-up into one connected workflow. Your team decides who advances and approves outreach before it is sent.
AI sourcing
Find the right candidates and bring their evidence together.
Client management
Turn client notes into clear, actionable role briefs.
Minimal ATS
Keep candidates organised as they move through the process.
Outreach & follow-up
Draft messages and sequences for recruiter approval.
AI interviewer
Support structured screening so recruiters can make informed decisions.
Background checks
Later-stage verification within the proposed recruitment scope.
Proposed scope · Designed for human approval at every key handoff.
For builders
Your agents.
A shared set of rules.
Create teams from prompts, connect them to your systems, and define the boundaries. Start with the open-source runtime today; help shape the platform next.
Explore the foundation ↗For businesses
A workflow you recognise.
An outcome you can measure.
Start with a complete vertical like SavvyHire. Work towards a useful business outcome, without assembling and managing a collection of disconnected agents.
Discuss your workflow ↗Built on an open foundation
You can inspect
the machinery.
The Stageflow runtime is open source. Define workflows in YAML, run locally, and keep the route beside your code. The Stageflow platform builds on that foundation.
# After installing the Stageflow CLI
sf init
sf uiAVAILABLE
Open-source runtime, YAML workflows, verification, and local operator console.
IN DEVELOPMENT
The agent workspace and prompt-assisted workflow authoring.
PROPOSED PILOT
SavvyHire recruitment workflows, scoped with early partner teams.
Progress / An honest build log
Where we are.
A clear view of the work — without dressing planned features up as finished product. The runtime is available; the broader platform is being built.
Defined & designed
- Four-pillar product direction
- Recruitment workflow design
- SavvyHire product scope
In build
- Prompt-based agent creation
- Email connection
- Agent activity and cost view
Planned
- Policy and permission controls
- SavvyHire pilot
- Additional vertical packages
FAQ
Straight answers.
What teams usually want to know before putting agents into real work.
Ask us a question ↗Is this another chatbot builder?
No. Stageflow is for building teams of agents that carry out defined work under clear rules, not just chat.
Do agents replace my team?
The goal is to help the same team handle more work. People stay responsible for judgement, relationships, and critical approvals.
What does it cost?
Pilot scope and pricing depend on the workflow, the systems involved, and the amount of agent work. The first step is agreeing on one measurable use case.
How is my data handled?
Access, permissions, logging, and approval rules are designed into the workflow. Exact controls depend on the systems connected during a pilot.
When can we start?
Start with a focused discovery conversation, select one workflow, and define success before the pilot begins.
Build with us
Start with
a four-week pilot.
Choose one workflow, agree on measurable success criteria, and run it with human approvals in place. At the end, we look at the evidence together.
- One clear workflow, not a giant transformation.
- Success measures agreed before we begin.
- Human approval at every critical step.
We’re scoping pilots with early teams. Let’s start with a conversation.
Email us at contact@stage-flow.dev.