Maple AI OS

Keep operating authority outside the model

Use the strongest intelligence available while Maple preserves identity, memory, permissions, policy, execution boundaries, and proof across providers.

OS Architecture

Four layers that remain stable while models evolve

Maple Brain

Interprets intent, chooses models, proposes tools, supervises agents, and explains outcomes without receiving execution authority.

Deterministic kernel

Owns identity, capabilities, commitments, approvals, budgets, policy, and fail-closed authorization.

Agent and driver layer

Connects MCP tools, A2A agents, Wish, enterprise APIs, local services, and model providers through explicit contracts.

WorldLine and evolution

Preserves user-owned memory, receipts, provenance, evals, canaries, lineage, and rollback across model changes.

Open By Design

Frontier models and open protocols plug into Maple

GPT / Claude / Gemini / Hermon / local models
                         |
                    Maple Brain
                         |
       MCP tools <- Maple AI OS -> A2A agents
                         |
              deterministic services
                         |
              WorldLine + receipts

Request Lifecycle

Reason freely. Authorize explicitly. Execute deterministically.

Step 1

A user or agent presents intent under a durable Maple identity.

Step 2

Maple Brain selects GPT, Claude, Gemini, Hermon, or a local model and drafts a typed proposal.

Step 3

The kernel evaluates capabilities, policy, risk, budgets, and required human approval.

Step 4

A deterministic service executes only the authorized consequence.

Step 5

WorldLine records the proposal, decision, execution, and outcome receipts.

Step 6

Evals, canaries, and rollback improve the system without erasing its history.

Design your first Maple-governed agent

Begin with one model, one capability boundary, and one receipt trail. Add providers and agents without changing the authority model.

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