Platform architecture

The infrastructure layer under your AI product.

Four layers that every production enterprise AI solution needs: context, execution, governance and integration. Deployed privately, in your cloud or inside your client's environment.

Partner architecture

One operating layer between your solution and every client environment.

You build the solution. The customer keeps its environment. SmoothOperator.ai runs the layer between them.

Trace a request through the layers

Technical request path

From a user request to a reviewable result.

This is the logical flow of a partner solution on SmoothOperator.ai. It shows where context is scoped, when controls apply, and what can be reviewed; it is not a network-topology diagram.

Logical request trace
Illustrative · not a network map
  1. 01 / Request

    A user starts a partner-defined workflow.

    The partner solution supplies the user experience and domain logic. The workflow begins with the user's request and its permitted operating context.

  2. 02 / Context

    The workflow sees only its approved collections.

    Collection, agent and workflow permissions scope which client knowledge is available. Client context remains separate from partner templates and other clients' collections.

  3. 03 / Controls

    RunControls bound what the workflow can do.

    Execution controls define the allowed actions while agents run, rather than relying only on a review of the final answer.

  4. 04 / Execution

    Agents work with configured models and tools.

    Orchestrated or specialised agents use the model access and authenticated, allowlisted tool connections agreed for the deployment.

  5. 05 / Evidence

    The result retains its review path.

    Cited answers, agent steps, tool calls and structured outputs can be traced and exported for review against their sources.

Sequence shown for explanation; the deployment and data boundary are scoped per solution.

The deployment boundary matters.

Where execution runs, which systems are connected, and whether a model is external depend on the solution and the agreed deployment. This logical sequence does not assert that every request stays inside one network.

Sensitive data and external models.

For workflows that use an external model, review the anonymization layer and the proposed data boundary during technical scoping.

For the actual hosting topology, model and tool configuration, access model, and evidence format, request a technical session for your proposed deployment.

Four production layers

The parts your solution should not have to rebuild.

01

Private context layer

Your clients' knowledge, inside their boundary.

A governed document and knowledge layer built from collections. Each collection sets what an agent can see and act on, by role. Terms like "customer", "policy" or "case" mean the same thing across every agent and workflow, without that knowledge ever sitting in a vendor's cloud.

Why it matters to partners

Each client's data stays separate, and your templates and rules stay separate from theirs.

02

Agent execution

Multi-agent workflows that hold up in production.

Orchestrated agent teams for complex reasoning, and specialised agents for fast domain queries. Every run produces structured outputs (threads, attachments, exports) that your clients' teams can review, reuse and audit.

Why it matters to partners

You design the workflow once and deploy it to every client.

03

Governance and controls

Compliance is a property of the system, not a report.

RunControls define what each workflow may and may not do, and enforce it while the agent runs. Access is controlled at the collection, agent and workflow level. Every tool call, agent step and output is traceable.

Why it matters to partners

You can sell into regulated clients, where "the AI said so" is never an acceptable answer.

04

Open integration

Any model. Your keys. Your client's systems.

Works with any model provider using your own keys. Native MCP tool server support, with consistent authentication and allowlists, lets agents act across your clients' existing systems. Switching models is a configuration change, not a migration.

Why it matters to partners

Your product never depends on one model vendor's roadmap or pricing.

Evidence-grade outputs

Every answer can be defended.

Answers are cited and checked for citation integrity. Any result exports as an audit-ready bundle that traces the question to the answer to the source.

Built for partners

What you need to run a product on us.

CapabilityStatus
Per-client deployment (cloud, on-prem, air-gap)Available under partner agreement
Collection-level data separation per clientAvailable under partner agreement
Any model, bring your own keysAvailable under partner agreement
Native MCP tool integrationAvailable under partner agreement
White-label and co-branded deploymentAvailable under partner agreement
Multi-tenant hosting with tenant isolationAvailable under partner agreement
Per-tenant usage meteringAvailable under partner agreement
Partner administration consoleAvailable under partner agreement
APIs and SDKsAvailable under partner agreement

Capability scope and deployment details are agreed for each partner solution.

See how your solution would run on SmoothOperator.ai.