LLMs plan. Ploston executes.

Deterministic workflow execution for AI agents. Cut token costs 75-95%. Make agents production-ready.

Why Ploston?

📉

94% Token Savings

Multi-step workflows cost 90%+ less than raw agent orchestration. The more steps, the more you save.

📝

YAML Workflows

Define workflows as code. Version control, code review, CI/CD pipelines. No visual builder lock-in.

🔒

Self-Hosted & Secure

Runs in your infrastructure. Your data never leaves your environment. Air-gapped deployments supported.

How It Works

Define workflows in YAML. Ploston exposes them as MCP tools. Your agent calls once, Ploston handles the rest.

Without Ploston

LLM calls tool #1 (500 tokens)
Result flows back to LLM (800 tokens)
LLM calls tool #2 (1200 tokens)
Result flows back to LLM (1500 tokens)
LLM calls tool #3...
Total: ~10,000+ tokens

With Ploston

LLM calls workflow (300 tokens)
Ploston executes steps 1, 2, 3... (0 LLM tokens)
Final result to LLM (300 tokens)
Total: ~600 tokens (94% savings)

Define workflows in YAML

# workflows/summarize-and-store.yaml
name: summarize-and-store
version: "1.0"

steps:
  - id: fetch
    tool: http_get
    params:
      url: "{{ inputs.url }}"
  
  - id: summarize
    tool: llm_summarize
    params:
      text: "{{ steps.fetch.output }}"
  
  - id: store
    tool: db_insert
    params:
      table: summaries
      data: "{{ steps.summarize.output }}"

output: "{{ steps.store.output }}"

Your agent calls workflow:summarize-and-store once. Ploston handles the rest.

Ploston Pro is coming soon.

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