FAQ
What is Redgold?
A vertically integrated platform for building and operating pipeline applications: a checked-in Rust serde schema encoded with CBOR, declared routes and transforms, managed execution, datasets, and Git-backed deployment. Coding-agent workspaces and the compatible model API support that application path and can also be used independently. The overview explains the idea in full.
What is a pipeline app?
The current customer deliverable is a Git-reviewed Rust schema, pipeline TOML, transform, tests, and API contract running on Redgold-operated routing, execution, storage, and deployment. The broader portable package adds declarative pages, client actions, synchronization policy, permissions, and dependencies; those surfaces remain component or product previews. See the pipeline application walkthrough and Pipeline Apps.
What stops an agent from making a mess?
The guardrails are structural. Schemas are validated, routes are declared in a spec and resolved by the edge, code runs in a sandboxed executor with defined capabilities, and every change goes through CI plus an automated reviewer/fixer cycle before it merges or deploys. Model spend is metered per agent, so a runaway session has a bounded cost.
How does this compare to Rama?
Rama overlaps with Redgold's backend and dataflow layer through append-only inputs and materialized views. Its unit is JVM topology code. Redgold's unit is a declarative application spec — typed schema, pipeline manifest, and sandboxed transform code — connected to the agent fleet, model routing, review cycle, and Kubernetes deployment. The full comparison lists the criteria side by side.
Do I have to use the whole platform?
No. Each layer works on its own: the model API from any existing OpenAI or Anthropic client, agent workspaces against your own repositories, or the full pipeline path with managed deployment. You can keep your own application stack and deployment and adopt only the pieces you want.
What can I use today?
Onboarded accounts can run coding-agent sessions from the web application and call the authenticated model API. Managed data and application deployment are available through onboarding while their self-service controls continue to evolve.
Which model SDKs work?
The public model API supports OpenAI-compatible Chat Completions and Responses requests and the Anthropic-compatible Messages request shape. Use /v1/models to discover the model identifiers available to your account.
Does an agent session reproduce the same result?
Session history is persisted and auditable. Model generation, external services, repository changes, and a growing dataset can make a replay produce different output. Reproducible evaluation requires pinned inputs, model and configuration, code revision, and a stable data snapshot.
Why are some reachable endpoints absent from the API reference?
Network reachability is broader than the supported public contract. Product UIs, agents, and internal services use routes that may change with the implementation. Public API pages are generated only from endpoints explicitly approved for external use.
Is there a public SDK for the data platform?
The stable public client surface is currently the HTTP model API. Internal Rust clients and dataflow interfaces exist, but they are withheld from the public reference until the contracts, examples, and compatibility expectations are ready for external callers.