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AI World Model

Masar

Planning, verification, and memory for AI agents. Give your agent a world model that knows what to build, catches errors before they happen, and learns from experience.

pip install masar-client

Three Capabilities

One API. Three things every agent needs.

Masar Capabilities Neural NodesMasar Capabilities Neural Nodes

Planning

Given a partial result and a goal, Masar produces ordered instructions for what to build next. Dependency-aware, parameterized, ready for your LLM to execute.

Verification

Predicts whether a result is valid in milliseconds, without running the full compiler. Catches 20 categories of structural errors before they become runtime failures.

Memory

Stores agent experiences as structured episodes. Over time, clusters similar experiences into reusable patterns. Your agent gets better at familiar tasks without retraining.

10 Lines to System 2

Your LLM is System 1: fast, intuitive, generates text. Masar is System 2: deliberate, structural, plans and verifies. Wire them together in 10 lines.

< 5ms planning latency

94% validity prediction accuracy

93 built-in behavior patterns

Memory that learns from experience

agent.pypython
from masar import MasarClient

client = MasarClient(api_key="...")

# Plan: what should the agent build next?
plan = client.plan(current=partial, goal=target)
for instruction in plan.instructions:
    result = your_llm.execute(instruction)

# Verify: is the result valid?
check = client.verify(schema=result)
print(f"Valid: {check.valid}, Errors: {check.errors}")

# Remember: store this experience
client.memory.store(episode=result, domain="helpdesk")
Masar How it Works PipelineMasar How it Works Pipeline

How It Works

1

Send State

Your agent sends the current state and goal

2

Plan

Masar plans: ordered instructions with exact parameters

3

Execute

Your LLM executes each instruction

4

Verify

Masar verifies: catches errors in milliseconds

5

Remember

Masar remembers: stores the experience for next time

Built For

Agent Builders

Add structured planning and memory to any LangChain, LangGraph, or custom LLM agent. Masar works with any model: Claude, GPT, DeepSeek, open-source.

Orb Developers

Accelerate .orb schema construction with AI-guided planning. Masar knows 93 standard behaviors and produces instructions the compiler can validate.

Enterprise Workflows

Automate business processes with agents that remember. Helpdesk, CRM, compliance workflows that improve from every interaction.

Get Started

Masar is part of the Almadar platform. Join the community.