Forge Studio is a multi-tenant agentic application builder and runtime. You describe what you want to do — what you store, what people do, who's allowed to do what, and what the rules are — and the AI helps you get that definition right. Then Forge builds and runs the application from it.
Get the definition right first. The app follows from it.
Forge Studio is the end-user app builder. If you're a developer interested in pure agentic SDLC — AI-assisted pipeline, code generation, agent orchestration, and dev workflows — take a look at PlatinumForge instead.
Most software gets built the same way. Someone describes what they need. Someone turns that into tickets. Someone builds database tables. Someone else builds forms, APIs, validation, and permissions. By the time it ships, the original meaning has been guessed at, lost, and recovered four times over.
Forge Studio works the other way round. Before any code is generated, the AI coaches you to build a complete, precise definition of your business — what we call an ontology. Not a schema. Not a UI mockup. A real definition: what the business stores, what people do, which actions are allowed, which rules must hold, which workflows exist, and what the app must enforce.
Once that definition is solid, Forge builds and runs the application from it. The definition is the source of truth. The app lives on top of it.
The secret: the "application" is mostly just a versioned business definition that Forge knows how to interpret, validate, generate from, and deploy — as if it were a fully hand-coded app and pipeline. But it isn't. It's a description that Forge brings to life.
How it works
| 1. Understand your intent | The AI asks the right questions: what are you trying to run, who does what, what needs to be stored, what are the real business rules? |
| 2. Define your business first | Together you build the definition — things to store, actions, validation rules, workflows, roles, and permissions — before any app is generated. |
| 3. Pick your components | Ready-made templates, screen layouts, workflow engines, auth rules, skins, and views are selected to wrap around your definition. |
| 4. Generate and run | Your application is generated, versioned, deployed, and runs as a real business app — not a demo or a prototype. |
| 5. Change safely | Future changes go back into the definition. The screens, workflows, permissions, tests, and deployments update from the same source. |
Everything else — multiple views, workflow engine, skins, validation, storage, authentication, realtime updates, versioning, deployment — is the machinery that makes your definition useful as a running application.
What the definition covers
| Your data | What the business stores: records, relationships, states, events, and how they connect. |
| Your app's shape | Pages, forms, lists, detail views, actions, navigation, and dashboards — generated from your definition, not hand-built per screen. |
| Your rules | Validation, required fields, approval conditions, automation triggers, notifications, and generated tests. |
| Who can do what | Roles, permissions, what each role can see and do, audit trails, and data boundaries between tenants. |
| Version history | Every change to the definition is versioned. Generated code, migrations, deployments, and test results are tied to that history. |
That means the application can be flexible without being a mess. Two customers can have completely different apps, rules, and workflows — but the differences are in their definitions, not scattered through hand-coded exceptions.
What Forge Studio can do
Forge is being built to cover the full range of business application features, with your definition as the driver rather than hand-coded screens.
| Feature | What that means in practice |
|---|---|
| Multiple business views | The same data can produce different screens for different roles — lists, forms, dashboards, queues, admin views, and operational screens. |
| Multiple business flows | Workflows become proper states, transitions, approvals, task queues, and notifications — not custom code bolted on per customer. |
| Validation | Required fields, relationship rules, state transitions, and acceptance criteria are checked before anything is accepted as correct. |
| Workflow engine | Approvals, escalations, lifecycle changes, automated steps, and audit events all come from the process rules in your definition. |
| Generated screens | Forms and tables are generated from your definition — no hand-building the same screen layout for every customer. |
| Styles, layouts, and skins | Customers can have their own look and feel — visual styles, layout templates, branded shells, density modes — without touching the underlying logic. |
| Storage and history | Customer data, definition versions, generated artifacts, workflow events, and validation results are stored durably and traceably. |
| Login and permissions | Roles, customer isolation, permissions, visibility rules, and audit trails are enforced at runtime — not just described in comments. |
| Live updates | Real-time updates support live workflow progress, collaborative editing, validation status, and generated app feedback. |
What the AI actually does
The AI isn't a chatbot bolted onto a database app. Its first job is coaching: ask the right questions, spot missing rules, separate things from actions, find unsafe assumptions, and turn vague business requirements into a proper definition before anything gets generated.
Once the definition is stable, different agents work on it. One expands vague ideas into concrete concepts. Another challenges assumptions. Another shapes the data model and workflows. Another checks security and rule consistency. Another validates the generated output against your original requirements.
The useful pattern isn't "ask an AI to build an app". It is:
| You describe | Forge Studio produces |
|---|---|
| A business concept | Records, fields, and relationships in your definition. |
| Rules and conditions | Validation logic, policies, tests, and review gates. |
| A workflow | States, transitions, actions, approvals, and automations. |
| User roles | Permissions, navigation, what each role can see, and audit requirements. |
| Acceptance criteria | Executable tests that must pass before the generated output is accepted. |
Concrete example: a customer describes an asset inspection process — sites, assets, inspections, findings, photos, risk ratings, remediation tasks, and approval states. Forge coaches that into a proper definition first: what gets stored, which actions exist, who can take them, what must be validated, which workflows make sense. Then it generates the app: data structures, forms, list and detail screens, business views, workflows, role-gated actions, tests, and a clear trail showing why each part exists.
When that customer later adds "contractor sign-off" or changes a risk rule, that's a change to the definition — not a disconnected backlog item. The affected screens, validation, workflow, permissions, tests, and runtime behaviour update from the same source.
Why this matters when you have many customers
Multi-tenant platforms fall apart when every customer becomes a special case. One needs a custom field. Another needs a different approval flow. Another has different permissions. Eventually it's not a platform any more — it's a pile of exceptions.
Forge Studio keeps customer differences in their definitions, not in the code. Two customers can have completely different apps, workflows, and rules. The platform stays consistent. The differences are explicit, versioned, and reviewable.
- Isolation — each customer has their own definition, generated app, and runtime configuration.
- Traceability — every screen, rule, and behaviour points back to the definition that produced it.
- Governance — AI suggestions are reviewed, validated, and versioned before they become live behaviour.
- Reuse — common patterns become templates. Customer-specific meaning stays in their definition.
The short version
Don't make every layer of the app guess what you meant. Define it once, properly, with help from the AI. Let Forge build and run the app from that definition. When things change, change the definition — not every screen, every rule, and every test separately.