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Architecture

Seven layers, from the AI employees at the top to the infrastructure at the bottom, each one assembled from what is underneath it

Forward this page to IT. It is the whole stack on one screen: what an AI employee runs on, what a workspace is assembled from, and what all of it relies on.

How to read it

Seven bands, joined by the relation each one has to the band beneath: runs on, built on, secured by, connects to, relies on.

The shape says one thing: nothing at the top is a separate product. An AI employee has no storage and no permissions of its own. It is L1 executing through the same L4 components a person's screen executes through, under the same L5 controls, which is why an answer from an agent and a number on a dashboard cannot disagree.

L1 · AI employees

The autonomous workforce: hiring and mandates, skills, the tool surface, retrieval over your own knowledge, model choice, budgets, guardrails and the approval gate, escalation to a person, and a decision trace on everything.

A runtime with identity, boundaries, a budget and a record, not a chat window. See AI harness and AI organisation.

L2 · Workspaces

Where work and business state live: applications and portals, spreadsheets, task boards and inboxes, chat, collaboration threads, dashboards, and the exploration surface.

Every one of them is a view onto the same platform objects. See Applications, Sites and portals, Spreadsheets, Collaboration and Analytics.

L3 · Workbench

How the things above get built and changed: AI-first generation, applications as code in the built-in git, the process editor, the data-model builder, the marketplaces, the prototype canvas, the page and chart builders, and the design system.

This is the layer that decides whether you own the system or wait for someone else to change it. See Applications and Versions and the built-in git.

L4 · Platform

The core components everything above is assembled from: orchestration and the workflow builder, the query engine and semantic layer, the data catalogue and master data, the ledger, ETL and writeback, API integration, the MCP server, scheduling and triggers, object storage, realtime transport, notifications, roles, the audit trail, and separate development, test and production landscapes.

These are shared services, not per-application copies. That is the mechanical reason two applications installed side by side behave as one system. See Platform.

L5 · Security

Built into the core rather than layered on: single sign-on over standard protocols, roles and resource grants, row-level security, column masking, agent mandates and least privilege, a fail-closed approval gate in front of consequential actions, organisation isolation by schema, encrypted credentials, the audit log, and air-gapped operation.

The property worth checking: the platform applies these where it plans the query and where it dispatches the tool call, not in the interface. See Access and isolation.

L6 · Connectors

What it connects to: business systems, databases, warehouses, object storage, files, directories and any REST API. 130+ sources, with the typed connector registry behind them.

See Connectors and Sources and storage.

L7 · Foundation

What it relies on: containerised microservices on Docker and Kubernetes, cloud or on-premises, an open API-first architecture, an event-driven core, a stateless API layer that scales horizontally, an in-memory analytical engine, columnar data on object storage, zero-copy reads, and zero telemetry.

See Platform for the deployment and scaling detail, and Privacy and on-prem for what a self-hosted installation takes.

What this means in one sentence

Every property here comes from where it sits in the stack. Access holds everywhere because L5 sits under L4; the numbers agree because there is one query engine; an AI employee is governed because it executes through the same components a person does; and you can change any of it because L3 authors the layers above it as artifacts, not as code somebody else owns.

Next: All capabilities.

AIpril platform — component architecture
L1AI employeesThe autonomous workforce
Hiring & mandatesSkillsTools & MCPKnowledge & retrievalModels & providersBudgets & limitsGuardrails & approvalsHuman escalationProactive executionDecision trace
L2WorkspacesWork interfaces, decisions and business state
Apps & portals (CRM · Projects · Service desk · Price management)SpreadsheetsTask boards & inboxChat & copilotCollaborationDashboardsExploration
L3WorkbenchBuild & configure
AI harnessAI-first generationApps as code (built-in Git)Process editor (BPM)Data model builderApp marketplaceSkills marketplacePrototype canvasSite & page builderCharts / BI builderPixel-perfect reportsDesign system & themes
L4PlatformCore components
OrchestrationWorkflow builderQuery engineSemantic layerData catalogueMaster dataLedgerETL & writebackAPI integrationMCP serverScheduler & triggersObject storageRealtime (SSE · CRDT)NotificationsRoles managementAudit trailDev / Test / Prod landscapes
L5SecurityBuilt into the core
SSO / OAuth 2.0 / OIDCRBAC & resource grantsRow-level securityColumn maskingAgent mandates & least privilegeFail-closed approval gateTenant isolation (schema-per-tenant)Encrypted credentialsAudit logAir-gap ready
L6Connectors130+ sources and systems
QuickBooksGoogle SheetsPostgreSQLClickHouseOracleMS SQLS3REST APIFiles (Excel · CSV)LDAP (AD)+ 120 more
L7FoundationCore infrastructure
MicroservicesDocker · KubernetesCloud or on-premisesOpen architectureAPI-first (REST)Event-drivenStateless API layerHorizontally scalableIn-memory engineGo · Rust · JVMDuckDB · Apache ArrowParquet on object storageZero-copy dataZero telemetry