Answers + product direction
Know the system.
Shape what comes next.
Leave feedback Clear boundaries for multi-model workflows, BYOK cloud text adapters, user-owned local models, privacy, planned access tiers, and compatible local fine-tuning—followed by a direct line for improving DecaCap.
Getting started
What is DecaCap Builders?
DecaCap is a configurable multi-model Workbench. Each entitled box can use its own primary role, support role, provider, model identifier, task, and route. Solo Board Chat can target selected boxes, while Solo Begin launches all enabled entitled boxes in parallel. Collaboration runs sequential worker handoffs with a supervisor review between them; Dual divides the workers between two reviewing supervisors.
Are the role labels permanent?
No. Obmil identities stay attached to their boxes, but functional roles do not. You can mix and match primary roles, support roles, specializations, providers, and models for every project.
What do Spores and Magic do?
Spores provides quality guidance and suggested role combinations. Magic contains Solo, Collaboration, and Dual project prompts that can inject suitable roles, support roles, rules, tasks, and outlines into the Workbench for you to review before running.
Providers and cost
Does DecaCap supply cloud-provider API access?
No. DecaCap uses BYOK: each user chooses a supported provider, supplies that provider’s key, and pays any provider usage charges directly. A local-only workflow does not require a cloud-provider key.
Is one API key required for every box?
No. A cloud-provider connection is entered once. Every higher-numbered box assigned to that same provider reuses the encrypted connection while keeping its own model identifier, role, and task configuration. Local Model uses the device companion instead of a cloud API key.
Why are some providers selectable but not executable?
Some providers do not expose a compatible general model endpoint, or require a specialized media adapter. DecaCap keeps those paths visible for workflow planning but labels their execution boundary instead of pretending they work.
Will DecaCap stop a long provider response?
Not because a fixed amount of time elapsed. Worker requests have no DecaCap execution cutoff. In Solo mode, only the user can stop a box. In Collaboration and Dual modes, only the assigned Majesty Obmil Queen supervisor can stop or take over a worker—either through its visible Stop active control or through an enabled timed check that finds explicit evidence in streamed output matching the user’s stop or takeover rules. Silence, slow output, and non-streaming Kimi wait time are never stop conditions.
Local models
Who supplies the local model and computer?
The user does. DecaCap does not own a central GPU or model. The free DecaCap Local Companion connects this browser to a model runtime on the user’s own machine, and the model files, prepared data, adapters, and training output stay there.
Can a local model run inside a normal Workbench box?
Yes. Any entitled box can choose Local Model as its provider and use the same paired device companion and runtime-model name. The request goes from that normal Workbench box to the user’s own companion instead of through DecaCap’s server. GoldCap is not the only local-capable box; it is the dedicated training hub.
Does GoldCap really train a model?
GoldCap is the only destination for training documents and local training controls. It separates data preparation from training, can capture user-approved prompt/output pairs, accepts supported structured or readable documents, prepares local training files, launches a compatible local fine-tuning command, reports the process state and any progress visible in its logs, pauses or resumes where the operating system supports it, and stops the process. Its isolated test targets the runtime model selected by the user; DecaCap does not automatically install or activate a newly created adapter.
Can training happen while I use the Workbench?
Yes, while the Workbench page and local companion are both running, after you explicitly enable automatic pair preparation in GoldCap. Completed pairs are delivered to the local companion. If automatic training is also enabled, a compatible configured profile can start at the threshold you choose. Both options are off until you approve them.
Privacy and accounts
Where are provider keys stored?
Cloud-provider keys are encrypted in the user’s private account vault and are never returned to the interface after saving. The local companion address and pairing token stay in that browser’s local storage and are sent only to the loopback companion on the same device.
Does DecaCap publish my Workbench output?
No. The former public Shared gallery has been removed. Workflows, prompts, imported support files, outputs, and local-training material are private unless you export and distribute them yourself.
Can I export or delete my account data?
Yes. The Account page provides an account export and permanent deletion flow. Local companion data is stored separately on your own device and can be removed from its local data directory.
Plans and access
What is the difference between Builder 5 and Builder 10?
Builder 5 and Builder 10 are the defined future access tiers: Builder 5 covers Boxes 1–5 and Solo workflows; Builder 10 covers all ten boxes, Collaboration, Dual Team, and compatible GoldCap local-learning controls. Customer checkout is not active, so neither tier can currently be purchased through the site. The one configured administrator remains subscription exempt.
Can visitors inspect the Workbench?
Yes. Visitors can explore its structure and locked states. Execution, saving, private files, provider connections, and user-owned local-model operations require sign-in and a server-side entitlement. Because customer checkout is inactive, those protected operations are currently available only to the configured administrator.
Troubleshooting
Why will my local model not connect?
Confirm the DecaCap Local Companion is running, copy its pairing token into GoldCap, keep the default loopback address unless you deliberately changed it, and make sure the chosen model runtime is running. GoldCap’s connection check reports the exact missing layer.
Why did a training job not start?
Prepared pairs alone are not a training job. GoldCap also needs a base model, enough approved pairs, and a compatible fine-tuning toolkit or a command profile configured in the local companion. The job panel reports which prerequisite is missing.
Where should I report a problem?
Use the feedback form below for ideas, confusion, quality concerns, and feature requests. Use Support for account access, privacy, accessibility, provider failures, imports, or anything requiring a reply and follow-up.
Feedback channel
Tell DecaCap what
needs to become better.
Point out confusion, missing controls, workflow friction, accessibility problems, or the next feature that would make the Workbench more useful. Feedback enters the administrator inbox; it is not posted publicly.