Plasma AI

Agent infrastructure for teams running AI work at scale

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What is Plasma AI?

Plasma AI builds infrastructure for running and governing many AI agents at once, with per-agent budgets, permissions, persistent history and open primitives for inter-agent messaging and indexed knowledge. Its main coordinated work environment, Fractal, is announced as coming soon.

Plasma AI is building infrastructure for coordinating large numbers of AI agents, with the premise that managing agents at scale resembles running an organization rather than operating a single chatbot. The company's homepage lays out four principles: model routing that matches each agent to the right model for its task, persistent identity and shared history between runs, hard boundaries and explicit permissions per agent, and real-time visibility into what each agent is doing and spending. A live node view shows named agents with individual budgets and timestamped activity logs, so an operator can watch spend and output as work progresses. The product is aimed at teams that want to hand real, multi-step work to a system of agents and trust the result. Rather than one monolithic assistant, Plasma describes nodes with their own cost ceilings and permissions, coordinated inside a single system. Two open primitives already ship: Radio, positioned as the easiest way for agents to talk to each other, and Wiki, an indexed knowledge base with command-line tools for agents. The Wiki loop is described as reading only what a task needs, learning from each run, and indexing knowledge so later runs improve. The main deployable layer, Fractal, is listed as coming soon. It is meant to bring agent creation, coordination, communication and shared knowledge into one work environment. That timing matters for buyers: today the public surface is research and open primitives, not a finished management console. Teams evaluating Plasma should plan around a preview or waitlist posture rather than immediate production rollout, and should test Radio and Wiki first to judge whether the underlying coordination model fits their workflows. Compared with single-purpose agent builders, Plasma competes on governance and cost control across many agents rather than on ease of authoring one.

How do you use Plasma AI?

  1. 1Request a demo and scope your agent workload
    Start on the Plasma homepage and use the demo request to describe the multi-step work you want agents to handle. This is the documented entry point for prospective users.
  2. 2Review the core principles against your needs
    Read the homepage sections on model choice, compounding work, delegation boundaries and visibility. Decide which of these governance features your team actually needs before committing.
  3. 3Explore Radio for agent-to-agent messaging
    Read the Radio research page to understand how agents communicate within a Plasma setup. Assess whether your workflows require this kind of inter-agent channel.
  4. 4Explore Wiki for indexed agent knowledge
    Review the Wiki page and its command-line tooling. Map which of your internal documents or references would become indexed knowledge bases for agents to read selectively.
  5. 5Check the full research index for further primitives
    Browse the research index for additional open components beyond Radio and Wiki. These indicate where the platform is heading before Fractal ships.
  6. 6Contact the team about Fractal access
    Use the contact page to ask about Fractal availability, onboarding and commercial terms. The homepage lists no self-serve signup, so this step substitutes for it.

Pros and cons

Pros

  • Clear governance model: agents get explicit permissions and hard budget boundariesAI
  • Real-time node view shows what each agent is doing, spending and producingAI
  • Persistent identity and shared history mean procedures carry across runsAI
  • Radio and Wiki primitives are open and usable before the main platform shipsAI
  • Model routing principle lets teams spend on frontier models only where it mattersAI

Cons

  • Fractal, the flagship work environment, is marked coming soon rather than generally availableAI
  • No pricing figures published on the homepage, so budgeting requires a sales conversationAI
  • Limited public detail on integrations, SDKs and existing tool supportAI
  • Documented material is weighted toward research demos, not deployment guidesAI
  • No self-serve signup path visible; access appears to start with a demo requestAI

How much does Plasma AI cost?

Support

No public documentation site or help centre is listed. The contact page is the stated route for reaching the team.

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Features

Core concepts cover per-agent model routing, persistent identity and history across runs, hard permission and budget boundaries, and a real-time node view with audit trails. Open primitives include Radio for agent-to-agent messaging and Wiki, an indexed knowledge base with command-line tools. Fractal, the combined creation and coordination environment, is announced as coming soon.

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Frequently asked questions about Plasma AI

  • How do you use Plasma AI?
    The walkthrough on this page covers 6 steps: 1. Request a demo and scope your agent workload 2. Review the core principles against your needs 3. Explore Radio for agent-to-agent messaging 4. Explore Wiki for indexed agent knowledge 5. Check the full research index for further primitives 6. Contact the team about Fractal access.
  • What platforms does Plasma AI support?
    Plasma AI is available on Web App.
  • What are the limitations of Plasma AI?
    Fractal, the flagship work environment, is marked coming soon rather than generally available. No pricing figures published on the homepage, so budgeting requires a sales conversation. Limited public detail on integrations, SDKs and existing tool support.