Platform Overview

Build complete AI applications on one Shared Application Model.

Design the experience your users work in, give every decision governed data and context, orchestrate AI, tools, policy, and people, then carry the process through durable business action and evidence.

One application definitionContinuous AuthorityInspectable behaviorEvidence
A

App Builder

The surfaces people actually use.

C

AI Control Plane

The governed execution path.

D

AI Data Plane

The context and evidence that decisions rely on.

Business outcome first

Build the application around the business outcome

A useful enterprise AI application rarely ends with an answer. It moves through information, decisions, people, events, external systems, and later proof.

Purpose-built experiences

Dashboards, portals, forms, cases, queues, contextual AI screens, approvals, and evidence views stay connected to the active process.

Governed context

Retrieve knowledge and operational information within the active authority, then assemble decision-ready context with provenance.

Coordinated execution

Combine deterministic logic, models, APIs, tools, policy, approvals, callbacks, retries, and reusable subflows.

Human judgment

Bring reviewers into the same application state with the record, evidence, policy conditions, and proposed action.

Durable workflows

Pause for people, documents, schedules, callbacks, and downstream systems while preserving state, authority, and versions.

Outcome evidence

Update external systems and preserve the evidence behind the resulting business effect.

Three connected responsibilities

One platform. Three connected responsibilities.

The modules are separate so each responsibility is clear, but they share application semantics so the work stays connected.

App Builder

Build the experience around the work: dashboards, portals, forms, cases, workbenches, contextual AI experiences, approval screens, and evidence views.

Gives your team complete operational software instead of generic chat or workflow consoles.

Explore App Builder

AI Control Plane

Define how the application behaves and what it is allowed to do across deterministic logic, models, APIs, tools, policy, approvals, events, retries, and external actions.

Keeps workflows governed when they cross AI, APIs, people, events, and time.

Explore AI Control Plane

AI Data Plane

Give every decision governed access to operational data, retrieved knowledge, context assembly, features, relationships, durable state, cache, memory, provenance, and evidence.

Provides relevant decision-ready information without flattening every data responsibility into a prompt or generic cache.

Explore AI Data Plane
Application journey

See one application move across the platform

1

Experience and context

A reviewer sees the supplier, requested account change, invoices, evidence, risk indicators, status, and pending actions while the Data Plane assembles eligible information.

2

Decision and policy

The Control Plane coordinates deterministic checks, AI analysis, policy, tool calls, human review, durable waits, and step-up authentication.

3

Action and evidence

The final writeback and resulting effect remain tied to the same context package, policy decisions, approval state, and action receipts.

Experience -> Context -> Decision -> Policy -> Human Judgment -> Durable Execution -> Action -> Evidence
Shared semantics

One Shared Application Model keeps the application connected

The model connects the experience, data contracts, execution, identity, governance, context, durable state, and evidence without forcing every workload into one physical engine.

User experience

Pages, forms, dashboards, conversations, workbenches, queues, and evidence views.

Data contracts

Schemas, business objects, queries, mappings, APIs, calculated features, documents, and knowledge relationships.

Execution

Graphs, nodes, edges, subflows, conditions, events, models, tools, deterministic capabilities, and effects.

Authority

Users, workloads, tenants, roles, delegated authority, taxonomy, purpose, assurance, and scope.

Governance

Policies, obligations, approvals, enforcement points, and permitted capabilities.

Context

Operational facts, retrieved evidence, calculated features, prior state, memory, instructions, and history.

Durable state

Execution instances, waits, callbacks, attempts, approvals, operation identities, and recovery state.

Evidence

Versions, provenance, decisions, approvals, capability attempts, action receipts, effects, and causality.

Explore the architecture behind governed AI applications

Start with the platform overview, then go deeper into App Builder, AI Control Plane, AI Data Plane, identity, execution, and evidence as each page is authored.