FOR CTOs & ENGINEERING LEADERS

AI speed.
Engineering control.

A live canvas where managers, developers, marketers and AI co-operate on one application model — five years ahead of generation-first AI builders, and deployable entirely inside your perimeter.

8–10×Less code to write
On-premBuilder + apps
BYO LLMOr zero-retention API
weezzi.canvas LIVE · 4 ROLES
AI
Manager
Dev
Marketing
↓ ONE SHARED APPLICATION MODEL ↓
Schema · entities · RBAC generated
REST + GraphQL + OpenAPI generated
Multi-language fields · workflows generated
Live Site Editor in production deployed
Java / Python / JS extensions your code
5yrs
→ HEAD START IN PRODUCTION
Why we're not just another AI builder

It's not about having AI.
It's about a system AI plugs into.

Generation-first tools — Lovable, Bolt, v0, Cursor — write React and a Supabase table. The result runs. The structural layer that turns running code into a business — RBAC, multi-language fields, dashboards, runtime editing for non-developers, observability, payments, RAG — still gets built by hand.

Weezzi was a working application platform for 10+ years before the AI layer arrived. The AI doesn't generate scaffolding from scratch every prompt — it shapes a model the platform already knows how to compile into production.

10+ yrs platform IP 17.5M lines trained on Hot-deploy runtime Polyglot via GraalVM Selo I&D · ANI 2025
The live canvas

Four roles. One model.
No translation layer.

Most platforms force a hand-off — AI writes code → devs port it → marketing waits → ops deploys. Weezzi makes all four roles operate against the same living application model, in parallel.

AI Generates structure Tables · queries · pages · rules MANAGER Shapes the system Visual edits · workflows · roles DEVELOPER Extends real code Java · Python · JavaScript MARKETING Operates live site Copy · A/B · personalization — SHARED MODEL — Application Model Schema · code · permissions · pages · content → COMPILES TO PRODUCTION CODE · DOCKER · K8S
AI Prompts shape the application model — not just code snippets.
Manager Visual edits to schema, roles, and workflows — no code, no waiting.
Developer Real code per element. Differentiating logic only — not boilerplate.
Marketing Edits the live production site. No staging, no CMS, no tickets.
Engineering leverage

Write the differentiating 10%.
The platform generates the rest.

Industry studies show low-code platforms deliver 60–90% faster delivery and 50–70% cost reduction. Weezzi pushes that further: AI generation on top of a deterministic platform engine that's been compiling business apps for a decade.

What the platform generates

Per element, deterministically. Thousands of lines, error-free, every time. Devs only write what's actually unique.

Database schema & migrations100%
CRUD & repository layer100%
REST + GraphQL + OpenAPI100%
Auth & RBAC profiles100%
Multi-language fields & dictionaries100%
Cache · observability · queues95%
Pages · forms · tables · dashboards90%
Custom business logicyour code

The 8–10× leverage, visualized

For a typical SaaS, 90%+ of the codebase is undifferentiated plumbing — the same patterns repeated. That's what Weezzi compiles. The rest is yours.

~90% Generated by platform
10% Your code
↑ A typical Weezzi application's code distribution

What this means for engineering

  • Smaller teams ship larger systems
  • Generated code is consistent · zero drift
  • Onboarding new devs measured in days
  • Tech debt shifts from CRUD to actual logic
Beyond the copilot

You rolled out Copilot.
Your team got faster at the wrong things.

Cursor, GitHub Copilot, and Claude Code are typing accelerators. They make individual developers faster at producing the same shape of code your stack already had — including the inconsistency, the duplication, and the tech debt. Weezzi solves a different problem.

We mandated Copilot for the whole engineering org. Velocity went up. So did the code review queue, the inconsistencies between teams, and the time we spend reconciling slightly-different implementations of the same CRUD page.
— What the CTO mandate looks like
after 12 months in production
// WITH COPILOT ALONE

Faster typing.
Same architecture problems.

A copilot suggests the next line. It has no model of your application — no schema, no roles, no workflows, no design system. It autocompletes, but it doesn't standardize.

UserController.ts  ·  team A ⚠ inconsistent
// Dev A: prompts copilot for "user list endpoint" async getUsers(req, res) { const users = await db.users.findAll(); res.json(users); // no pagination, no RBAC }   // Dev B, same week, same task, different file: async listUsers(req, res) { // uses Sequelize, paginated, ad-hoc auth }
×Two implementations of the same endpoint, on the same sprint
×Each developer is faster — the codebase is messier
×RBAC, pagination, multi-language, audit logs all forgotten
×Your code review queue grew 3× in 6 months
×Junior devs ship junior code, just faster
// WITH WEEZZI

Standardized output.
Per-element, every time.

Weezzi compiles your application model into code. RBAC, pagination, multi-language, observability, audit — generated from the model, not hand-coded by whoever picked up the ticket.

users · entity · weezzi.model ✓ deterministic
// One definition. The platform generates: entity User { fields: [name, email, role, locale] rbac: [Admin: rw, User: r-self] }   REST + GraphQL + OpenAPI → pagination · filter · sort → multi-language fields · audit log same shape, every team, every time
One canonical implementation per pattern — no team-A vs team-B drift
Cross-cutting concerns (RBAC, i18n, audit) are non-optional
Code review focuses on actual business logic — not boilerplate
Junior devs onboard against the model, not the codebase
Your copilot still works — it now suggests against a consistent base
90% Of CRUD code
generated, not typed
0 Drift between teams
on same patterns
1 Source of truth
for the application model
+ Use Copilot or Cursor
on top — they get smarter
Polyglot · per element

Five languages.
One application. No rewrites.

Most platforms force one language per project. Weezzi runs Java natively and embeds Python, JavaScript, TypeScript and Scala via GraalVM — choose the right tool per element, not per project. AI converts between them in one click.

Jv
Java
NATIVE · JVM
Core platform language. Full breakpoints & stepping. Best for performance-critical paths.
Ts
TypeScript
TRANSPILED · GraalJS
First-class on the frontend. Type-checked, transpiles to JS for the runtime.
Js
JavaScript
GraalJS
Run any npm-style logic at the element level. Console & log debugging.
Py
Python
GraalPy
For data, ML, scientific work, or whatever your data team writes natively.
Sc
Scala
JVM · NATIVE
For functional, concurrent, and data-pipeline-heavy logic on the JVM.
// language assignment · per element · same project ⟳ AI one-click conversion between any pair
User authentication servicecore/auth · servlet
performance-critical
Java
⟳ Convert
Product catalog frontend componentsite/catalog · component
type-safe UI
TypeScript
⟳ Convert
Webhook handler · payment eventsintegrations/stripe · servlet
small + fast
JavaScript
⟳ Convert
Recommendation engineml/reco · timer
data team writes Py
Python
⟳ Convert
Event-stream processoranalytics/pipeline · timer
functional + concurrent
Scala
⟳ Convert
Admin dashboard widgetsbackoffice/dash · component
team preference
Java
⟳ Convert
All elements above belong to the same project · same deployment artifact · same RBAC · same observability
Architecture & governance

Production-grade.
From day one.

Engineering control isn't an add-on — it's the substrate. Six pillars CTOs ask about on the first call.

Code ownership · zero lock-in

Standard Java, Python, JavaScript code — no proprietary runtime. Export the repo. Self-host on Docker or Kubernetes. Source code escrow available on Enterprise.

JVM · Python · JS · K8s

RBAC & security gateway

Role-based access control is generated, not configured by hand. Multi-tenant isolation. Security gateway runs as a microservice in front of app servers. Encryption-at-rest for credentials.

RBAC · Multi-tenant · Gateway

Observability built in

Logs, traces, metrics generated per app. Prometheus/Grafana ready. Alert routing via email/Slack per environment. No third-party APM bolt-on required for baseline visibility.

Logs · Traces · Metrics

Polyglot · 5 languages

Java, TypeScript, JavaScript, Python and Scala on a single project. Pick the right tool per element, not per project. GraalVM-powered, one-click AI conversion between any pair.

Java · TS · JS · Py · Scala →

Hot-deploy runtime

Sites and components update without server restarts. Multi-environment (dev · staging · UAT · QA · prod) with per-env secrets, deploy targets, observability, and rollback.

Hot-deploy · multi-env

Sovereignty & compliance

Self-host the entire Builder, not just generated apps. Bring your own LLM or use Weezzi's zero-retention API. EU AI Act and GDPR-aligned by design. SOC 2 + ISO 27001 on the roadmap.

On-prem · BYO LLM · Air-gapped
Data sovereignty

The Builder runs inside your perimeter.
Not just the apps it generates.

Most AI builders are SaaS-only — your prompts, schemas, and code travel through their servers. Weezzi is the rare platform where the entire build environment, runtime, and AI inference can run on your hardware. Your code never leaves.

Everything inside your boundary

On-premises and air-gapped deployments are first-class. You control the network, the data, and the inference layer — not us.

// deployment topology Self-hosted
Weezzi Builder
on your K8s
Generated applications
Docker / K8s
Databases & secrets
your DBs
LLM inference (optional)
your GPUs
Logs · traces · metrics
your stack
— OPTIONAL EGRESS —
Anthropic / OpenAI via Weezzi zero-retention API — only if you don't run a local LLM

Why this matters at procurement

Three questions every CTO asks. Three answers Weezzi gives in writing.

  • "Where does our source code live?"

    On your servers. The Builder runs inside your perimeter on Docker or Kubernetes. Generated repositories never leave your network. Source code escrow available for Enterprise.

    Air-gapped supported
  • "Where does our data go for AI generation?"

    Wherever you decide. Plug your own LLM endpoints — Llama, Mistral, Qwen, Claude on Bedrock, Azure OpenAI — and prompts stay inside your tenancy. Or use Weezzi's managed endpoint with a contractually zero-retention guarantee.

    BYO LLM · zero retention
  • "What about regulators and auditors?"

    EU AI Act and GDPR alignment by design. SOC 2 Type I and ISO 27001 on the 24-month roadmap. Audit logs, role-based access, encrypted secrets, and tenant isolation are generated — not retrofitted.

    EU AI Act · GDPR · SOC 2
Three ways to run AI generation

Pick the inference path
that matches your compliance posture.

All three keep generated code on your infrastructure. The difference is where the AI itself runs.

01 / Maximum sovereignty

Your LLM, your GPUs

Point Weezzi at any OpenAI-compatible endpoint inside your network. Llama, Mistral, Qwen, DeepSeek — whatever your AI/ML team has standardized on. Prompts, schemas, and generated code never leave your tenancy.

BYO endpoint Air-gap ready vLLM · Ollama · LiteLLM
03 / Managed by Weezzi

Zero-retention API

For teams that want the simplest setup. Weezzi's managed endpoint routes to frontier providers under a contractual zero-retention agreement — no training, no logging of prompt content, no human review. Same model quality, none of the procurement friction.

No-train clause EU data residency Default for Cloud
The CTO matrix

What you actually evaluate
at procurement time.

Not "fastest first prototype." The dimensions that determine whether the system survives year three.

Dimension AI builders
Lovable · Bolt · v0
No-code
Bubble · Webflow
Enterprise low-code
OutSystems · Mendix
Weezzi
Real code ownership Partial Weak Proprietary Core
Self-host / on-prem Limited Limited Proprietary Core · free
AI-native generation Strong Add-on Copilot retrofit Core
Backend depth (RBAC, payments, queues) Improving Platform-native Strong Strong
Live operator editing in prod Weak Medium Weak Core
Polyglot · per-element language choice JS / TS only Limited One language 5 languages
Standardized output across teams Inconsistent Templates only Strong Core · model-driven
Observability & multi-env Bring-your-own Limited Strong Built-in
Vendor lock-in risk Medium High High None
Request a PoC

Run a Proof of Concept
inside your infrastructure.

We'll deploy Weezzi Builder in your environment — air-gapped, on your Kubernetes, or in your cloud account — and rebuild one of your existing applications as the test case. No data leaves your perimeter.

  • Deployment in your VPC / on-prem / air-gapped
  • One real app rebuilt & benchmarked vs. your current stack
  • Your LLM endpoint or Weezzi zero-retention API
  • Engineering walkthrough with our architect
  • NDA signed before any system details are shared
We respond within 1 business day · NDA-first conversations
✓ Request received We'll reach out within one business day to schedule the architecture call and align on NDA. Your details have not left this page during the demo — in production, this form posts to poc@weezzi.com.