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Project Everflow

Governance-first collaborative AI applications — on your infrastructure, with your rules.

This is the CORE branch: concept, methodology, and orientation for users and operators.
The runnable software lives on the product branch:

Development-Everflow

License Apache-2.0
Install / code Product branch (link above)
Roadmap ROADMAP.md on Development-Everflow

What Everflow is

Everflow is a self-hosted platform where teams build, review, and deploy AI-powered applications inside pre-approved boundaries. It is inspired by creative AI app spaces (e.g. HuggingFace Spaces) but adds organizational governance so innovation does not outrun compliance, data handling, and security policy.

Core ideas

  1. Governance first — Global rules for compliance, data access, and agent behavior sit at the platform layer, not as optional add-ons.
  2. Isolated projects — Every project runs in its own microsandbox microVM. Work is contained; tenants and projects stay separated by design.
  3. One public API — Browsers and tools talk only to the Everflow platform API. A privileged sandbox-agent owns KVM and the microVM SDK; it is not a public client endpoint.
  4. Your infrastructure — Docker/Podman compose install; images can stay in an embedded local registry. Data sovereignty is a product goal, not an afterthought.
  5. Agents with guardrails — Coding and automation agents (harnesses, MCP tools, workflows) operate inside org policy and project scope.

Typical flow

Team member → Platform UI / API
                 → Project + policies
                 → Sandbox agent provisions microVM
                 → Agent harnesses + toolkits build the app
                 → Preview / review / deploy within org rules

Methodology (how to think about Everflow)

Layer Responsibility
Organization Membership, invites, shared credentials, org-level policy
Project One app/workspace; owns a sandbox lifecycle
Sandbox Isolated microVM: filesystem, desktop/tools, harnesses
Knowledge & marketplace Org-approved skills, docs, and tools agents may use
Workflows Automation nodes (integrations, AI steps) under the same control plane

Design principles we optimize for:

  • Least privilege by default — sandboxes and tokens are scoped; mock mode is for CI/dev only.
  • Approve the boundary, free the builder — once policies and tools are approved, individuals move fast inside that box.
  • Operator honesty — production refuses default secrets; install is container-native, not a fragile host toolchain.
  • Open methodology, open code — concept lives here on CORE; implementation is open on the product branch under Apache-2.0.

Get the software

Quick install (product branch)

git clone -b Development-Everflow https://github.com/real-limitless/ProjectEverflow.git
cd ProjectEverflow
./scripts/everflow          # interactive TUI
./scripts/everflow setup-admin
# UI → http://localhost:3000

One-liner

curl -fsSL https://raw.githubusercontent.com/real-limitless/ProjectEverflow/Development-Everflow/scripts/get-everflow.sh | bash

Host needs: Linux, Docker or Podman + Compose, and /dev/kvm for real microVMs (or mock mode for limited dev).

Full install, production checklist, and architecture:
README on Development-Everflow


Branch map

Branch Audience Contents
CORE (this branch) Everyone Concept, methodology, install pointers
Development-Everflow Operators & developers Runnable monorepo, scripts, compose, packages
Release tags (when published) Operators Pinned install via EVERFLOW_VERSION=vX.Y.Z

Private work

GitHub cannot hide individual branches on a public repository. For personal experiments, Red Hat pitch materials, or private notes, use a private fork or private sibling repository — never push secrets or internal-only docs to this public remote.


Resources


License

Apache License 2.0 — see LICENSE.

About

Everflow a self-hosted platform where teams build, review, and deploy AI-powered applications inside pre-approved boundaries.

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