Build
Author the whole solution,
not just the workflow.
A Formula does one job. Real solutions also need an endpoint that other systems can call, a screen people can use, a model that scores what happens next, and a process that keeps working while everyone is away. They are authored in the same place and governed the same way.
APIs
Publish a REST endpoint bound to a Formula. Quadrazene hosts it under your tenant's hooks path, with the same governance and audit as any other run.
Applications
Import an API spec, design pages in plain language, and publish a runnable multi-page app that lives next to the Reactor.
Models
Train predictive models against any SQL-backed System and call them from any Formula or Chain, with the reasons behind each score.
Agents
Background processes, standalone or on a schedule, with defined configuration and a monitored run history.
Endpoints and screens
Let other systems and other people use it.
Hosted REST endpoints
Bind an endpoint to a Formula and it is live under your tenant's hooks path. Callers use scoped API keys, and every call is a governed, audited run.
One spine for callers
The same run machinery answers the Reactor, a Chain, a webhook and an API call, so behaviour never differs by entry point.
Import an API spec
Bring an OpenAPI definition and Quadrazene knows the operations available to an Application.
Design pages in English
Describe a page, adjust it, publish it. The result is a runnable multi-page app, not a mockup.
Runs beside the workspace
Published Applications open from the Reactor menu, under the same sign-in and permissions.
Connected Apps too
An Application can also be the wrapper for a legacy app you sign in through the broker.
Predict, then act
Models that explain themselves.
Train where the data is
Point a model at any SQL-backed System and train natively in the platform, or delegate to Databricks.
Tabular families
A logistic classifier for yes/no outcomes and gradient-boosted trees for continuous ones, both with per-feature contributions.
Call from anything
A trained model is usable from any Formula or Chain, so a score can gate an approval or start a process.
Fine-tune a generative model
Submit prompt and completion pairs to fine-tune a base model, and track the job through to the resulting model id.
A shared model picker
One picker chooses models everywhere, from a curated per-provider catalog with a live refresh against the provider.
Portable
Models, fine-tune jobs, APIs and Applications all travel inside signed Reagent bundles.
Work that continues without you
Agents, triggers and schedules.
Background Agents
Define an agent once, run it standalone or on a schedule, and watch its progress and output as it works.
Five kinds of trigger
A Chain starts on a schedule, an event, a completion, a manual click or an API call.
Event channels
Events can come from mailboxes, webhooks and durable streams, so a Chain reacts to the world instead of polling it.
Agent teams
A Formula can hand its plan to a supervisor that dispatches specialist Formulas in parallel.
Human gates
Any step can stop for an approval in the Inbox, and the risk score can add one automatically.
Immutable once published
Published versions are locked. Change means a new version, so what ran yesterday is still what it says it was.
Ship it as a solution.
Bring one process and we'll build the endpoint, the screen and the score for it together.