Real-Time Intelligence Platform

Turning data into real-time intelligence.

Eight layers that provision, process, decide, and act — autonomously.

$ curl -sSL https://get.plasma.sh | sh
$ plasmactl platform:create my-platform
$ plasmactl platform:up

specialized layers

Eight layers for an infinity of platforms. Each has a dedicated purpose and its own message bus. Cross-layer communication flows through explicit relays.

Hover a layer to learn more

How Plasma works

Plasma implements standardized building blocks for real-time intelligence platforms. Ontology organizes information. Topology organizes computation. Applications interface the world. Agents react to it. Autonomous from infrastructure to dashboard.

Nature

Sovereign

You own the full stack. No managed dependency, no external control plane, no vendor lock. Plasma provisions bare metal (OpenTofu), configures everything (Ansible), builds, and runs — from OS to dashboards. Air-gapped if you need.

# Provision — any substrate
on-premise, dedicated, VMs, cloud

# Configure — full stack
plasmactl node:provision  # OpenTofu
plasmactl platform:up     # Ansible

# Result — you own everything
bare metalrunning platform
Nature

Reactive

Event-driven at every level. Events carry complete state (ECST) — consumers never query back. Each layer has its own bus tuned to its semantics. Behavior emerges from channel topology, not a central coordinator. Cross-layer data flows through explicit relays with backpressure.

# Bus per layer — tuned semantics
integration: NATS   # business events
cognition:   Kafka  # analytics streams
conversation: Matrix # utterances

# Cross-layer via relays only
relay: Bento # backpressure
Structure

Ontology

Organizes information. Entities define WHAT exists, Metrics define HOW to measure. Together they form the stable data contract between all systems. Protobuf schemas are the source of truth, enabling automatic schema evolution.

# Entity — describes the world
entity: Person, Project, Utterance

# Metric — measures the world
metric: Engagement, Sentiment, Risk

# Schema = contract (protobuf)
package platform.person;
Structure

Topology

Organizes computation. Topology sections map logical architecture to physical resources. Nodes allocate to topology, Agents and Applications attach to it. Each section gets the right compute profile.

# Topology distributes to components
cognition.data    → GPU nodes
foundation.kv    → storage nodes
interaction.obs  → balanced nodes

# Nodes allocate, components attach
node topology {app, agent}
Behavior

Application → Service → Software

Applications interface the world. An Application orchestrates WHY (business purpose), Services configure WHAT (deployment context), Software defines HOW (programs).

# Application (WHY) — orchestrates
dashboards: monitoring system

# Service (WHAT) — configures
dashboards-grafana: prometheus + oauth2

# Software (HOW) — computes
grafana: visualize time-series data
Behavior

Agent → Skill → Function

Agents react to the world. An Agent decides WHEN (event-driven triggers), Skills configure WHAT (parameters), Functions define HOW (generic computation). One function serves many use cases through different skills.

# Function (HOW) — generic computation
score(input, model, threshold)

# Skills (WHAT) — one function, many configs
risk_scoring: bayesian + threshold 0.8
quality_gate: coverage + threshold 80%

# Agent (WHEN) — event-driven
sprint_reviewer: on sprint_completed

Packages, models, and services

Packages bundle components for a domain. Models compose packages into platforms. Integrators deploy them. Managed services run them.

Packages
1 Co plasma-core

plasma-core soon

Foundation, Integration bus, Conversation — the kernel everything depends on. Kubernetes, IAM, NATS, mail bridge, observability.

2 Wk plasma-work

plasma-work soon

Project management, team messaging, calendar, video calls, initiative tracking. Plane, Element, Jitsi.

3 Da plasma-data

plasma-data soon

Analytics pipeline, data lake, OLAP engine, dashboards. Spark, Kafka, Druid, Superset.

4 Tk plasma-talk

plasma-talk soon

AI conversational interface. MCP server for natural language interaction with your platform.

5 Cd plasma-code

plasma-code soon

Git repositories, CI/CD pipelines, code review, artifact management. GitLab integration.

6 Ln plasma-learn

plasma-learn soon

Learning paths, knowledge base, skill assessments, certifications. Moodle LMS.

7 Lb plasma-lab

plasma-lab soon

Low-code experimentation — data connectors, workflow automation, spreadsheet database. Airbyte, n8n, NocoDB.

Models
7 Ta The Agency
soon

A complete digital operating system for service companies. Manages projects, tracks time, handles invoicing, analyzes team communication, and runs CI/CD — all on your own infrastructure.

plasma-core plasma-work plasma-data plasma-talk plasma-code plasma-learn plasma-lab
Integrators

Skilld

Plasma creator. Turns recurring operational decisions into autonomous, auditable responses — from situation identification to live execution in 6 weeks.

Deploy Plasma for your clients?

Become an integrator →
Managed services

Plasma Cloud

Fully managed Plasma. Infrastructure, updates, monitoring, and support handled for you. Deploy Ta or a custom composition. Operated by Skilld.

Offer managed Plasma hosting?

Become a provider →

Install in seconds, deploy when ready

Prerequisites: Docker and Git. Runs on Linux, macOS, and Windows.

1.

Install plasmactl

The CLI tool for all platform operations.

$ curl -sSL https://get.plasma.sh | sh
> irm https://get.plasma.sh/install.ps1 | iex
2.

Create a platform

Initialize a new platform with the interactive wizard.

$ plasmactl platform:create my-platform
3.

Deploy

Bring your platform up on your infrastructure.

$ plasmactl platform:up

Full documentation

Comprehensive guides, tutorials, and reference at docs.plasma.sh.

Open source, open development

Core repositories that make up the Plasma ecosystem. The plasmactl toolchain is open source today; the packages are being published progressively.

plasmactl Core CLI framework for Plasma platform management
Go
plasmactl-platform Platform lifecycle — deploy, compose, graph
Go
plasmactl-node Node provisioning and multi-provider infrastructure
Go
plasmactl-component Component versioning, bumping, dependency management
Go
plasmactl-model Model blueprints for package structure and deployment
Go
plasmactl-topology Topology management — map zones to physical resources
Go
plasmactl-processors Data processors for Cognition layer pipelines
Python
plasma-core Foundation, integration, conversation — the kernel
Plasma soon
plasma-work Project management, messaging, calendar, video
Plasma soon
plasma-data Analytics pipeline, cognition functions
Plasma soon
plasma-talk MCP server, AI conversational interface
Plasma soon
plasma-code GitLab integration, CI/CD
Plasma soon
plasma-learn Moodle LMS, learning paths
Plasma soon
plasma-lab Airbyte, n8n, NocoDB — low-code experimentation
Plasma soon
ta The Agency — a complete platform model for service companies
Plasma soon

Build with us

Plasma is built in the open. Every contribution matters.

Learn

Architecture guides, tutorials, and reference. From first install to production deployment.

Documentation →

Discuss

Ask questions, share ideas, and connect with other Plasma engineers and contributors.

Discussions →

Contribute

Pick an issue, open a PR, improve docs, or propose a new component. All contributions are welcome.

Contributing guide →

License

EUPL-1.2 — copyleft, OSI-approved, GPL-compatible. Use, modify, distribute freely.

View license →