Copilots write hundreds of source files for you to read, review, and stitch together. In Weezzi, the AI shapes a visual canvas of structures — tables, pages, forms, dashboards — and the platform compiles those structures into thousands of error-free files behind the scenes. You design the system, not its source code.
A heap of source files is the wrong unit for understanding a business application. Tables, pages, forms, dashboards, workflows — the things you actually think about — are the unit on Weezzi's canvas. The platform compiles them down to error-free code; you stay at the level where decisions are made.
Each file is authored by an LLM, opened, read, fixed, integrated. The unit of work is the file. The unit of review is the line.
AI defines structures — tables, components, forms, table views, dashboards. Site and backoffice are separate canvases. The platform emits the code.
Founders, managers, and developers talk to the same Weezzi AI to evolve the system — across the whole project, not file by file.
Not one big diagram. Each layer of the system has its own visual surface — and the platform keeps them consistent.
See the schema as nodes and edges. Add a field, change a type, draw a relation — Weezzi regenerates migrations, REST/GraphQL, validators, and admin views in lockstep.
Public-facing site lives on its own canvas: pages, components, content blocks, multi-language fields. Marketing edits content live on production via the Site Editor.
Backoffice is a separate canvas with built-in page types: list views, detail forms, master-detail, kanbans, calendars. Add a table to the model, get a CRUD page generated. No layout work.
KPI cards, charts, sparklines, donuts, time-series — drag in a metric, pick a chart type, point it at a query. No charting library wiring, no React boilerplate.
Not "do worse." Cannot do, because the architecture starts in a different place.
Copilots ask you to read source code to understand the system. Weezzi shows you the system: tables and their fields, components, forms and their layouts, page-level table views, backoffice pages, dashboards. You see structure, not strings.
See, don't readAI shapes structures on the canvas. From those structures the Weezzi platform deterministically emits hundreds, even thousands of files — error-free, with zero LLM context spent on boilerplate. Developers receive a working system out of the box, not a probabilistic draft to debug.
AI for intent · platform for codeWeezzi AI is always present, with full context of the project. A founder prompts "add a referral program" and it ships. A manager asks for a new dashboard and gets it. A developer asks for a structural refactor and it happens — across the whole project. Same AI, same context, role-aware permissions.
Context-aware · role-awareThe Site Editor sits inside the production app. Marketing edits content, layouts, multi-language fields, A/B variants, and scheduled publishes — directly on the deployed system. No coding tool offers this, because shipping code faster doesn't solve a problem that isn't a coding problem.
Operate the live appBuilding a multi-tenant SaaS with auth, billing, and a marketer-editable site.
refactorThe difference is structural. A code generator emits code once and walks away — you own and maintain everything that came out. Weezzi maintains the generated layer for you. When the application model changes — a new field, a new role, a new feature — migrations, REST endpoints, GraphQL schema, RBAC checks, admin panel, and multi-language fields all update with it. You only own the code you wrote: the differentiating logic. The model is the source of truth, not the generated output.
And the embedded AI isn't a bolt-on. Because Weezzi knows the application model — every table, role, page, workflow — its assistant has context no IDE-based copilot can match. A founder, manager, or developer talks to it about features and scope; it updates the model; the platform regenerates what changed. No file-by-file prompting. No drift between layers.
And because the generated code is standard Java, Python, and JavaScript on Docker or Kubernetes, you can always export the whole thing and walk away. The lock-in concern that's legitimate against Bubble or OutSystems doesn't apply — the exit door is a git clone and docker compose up.
Try the pilot. Bring your editor.