Skip to content
richbay.ai
PlaygroundsCasesLearnToolsFor Teams
richbay.ai

Learn by Solving. Solve practical problems, test what works, and turn evidence into reusable methods, workflows, and stacks.

Explore

  • Playgrounds
  • Cases

Resources

  • Learn
  • Tools

RichBay

  • For Teams
  • About
  • Privacy

© 2026 RichBay

RichBay.ai is independent and is not affiliated with or endorsed by the model providers or companies referenced on this site.

Tools · Stacks

AI Stacks for a defined outcome

Start with a maintained default, understand why each component is present, and know when to switch.

These are method, workflow, and technical records—not shopping lists. Each one states its data flow, human checkpoints, operating boundary, evidence status, and known limitation.

← All ToolsBrowse Stack records

Maintained starting points

Choose by outcome and operating constraint.

No universal “best stack” is implied. Open a record to inspect default choices, alternatives, switch conditions, and the evidence boundary.

Method StackRichBay tested

Controlled model comparison

Compare model outputs for one bounded task without leaking model identity into the first judgment.

OutcomeA bounded model choice backed by captured outputs, review criteria, and visible limitations.
Versioned task packetControlled model runsEvidence ledgerHuman review checkpoint
For
Teams deciding which model output fits a specific, repeatable task.
Setup
Medium
RichBay tested
Open Stack record →Inspect its Case
Reviewed 2026-09-05
Workflow StackRichBay tested

Evidence-bound workflow pilot stack

Turn one team workflow into a repeatable AI-assisted process with explicit human checkpoints.

OutcomeA repeatable AI-assisted workflow with explicit ownership, review gates, and a decision record.
Workflow scopeSelected tools and modelsReview checklistDecision record
For
Small teams piloting AI in one frequent, bounded operational workflow.
Setup
Medium
RichBay tested
Open Stack record →Inspect its Case
Reviewed 2026-09-05
Technical StackOfficial info checked

RAG knowledge assistant

Build a bounded knowledge assistant over maintained documents instead of relying on general model memory.

OutcomeA question-answering interface that retrieves from a controlled source collection and exposes supporting passages.
Document parserEmbedding modelQdrant reference storeRetrieval and answer service
For
Product teams with a defined document corpus, permissions model, and real evaluation questions.
Setup
High
Official info checked
Open Stack record →
Reviewed 2026-09-05
Technical StackUsed at RichBay

Low-operations AI product prototype

Build and release a small AI product without committing early to a large application platform or a long list of services.

OutcomeOne deployable AI-assisted product flow with traceable releases, bounded data handling, and a clear path to add infrastructure only when needed.
Next.js applicationCloudflare Workers deployment pathServer-side model boundaryOptional D1 and R2 bindings
For
Founders and small product teams validating one complete input-to-output flow.
Setup
Medium
Used at RichBay
Open Stack record →
Reviewed 2026-09-05