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Adopters

{/* Editorial rule for this page: every entry is a named organisation that has confirmed its own usage. No anonymous testimonials, no aggregate counts, no logos we have not been given permission to show. An adopters page that overstates is worth less than a short one — and this is the page an evaluator checks first. See planning/branding: “No fabricated proof.” */}

Adopters

PromptPack v1.5.1 is published and running in production at AltairaLabs, with a reference implementation and a LangChain.js integration. Entries below are named and attributable.

If you are running PromptPack, tell us and we will list you.

AltairaLabs
Industry AI development tools
Use case Authoring and operating the PromptKit reference toolkit
Scale Production use across testing, CI/CD and runtime workloads

AltairaLabs created PromptPack and uses it for:

  • Operating the PromptKit reference toolkit (runtime, promptarena, packc)
  • Internal agent engineering workflows
  • Testing agent behavior across providers
  • The examples and documentation on this site

altairalabs.ai →

Reference implementation

PromptKit

A Go runtime plus npm-distributed CLIs for testing, validating and compiling packs.

  • Full PromptPack v1.5.1 support — agent loops, workflows, compositions, multi-agent, skills, evals
  • Provider integrations: Claude, OpenAI, Gemini, Azure, local models
  • promptarena testing CLI and packc compiler CLI
  • GitHub Actions for CI/CD

View on GitHub →

LangChain.js integration

@promptpack/langchain loads packs directly into LangChain.js.

Worked examples

The examples in the specification are written to demonstrate the format — a support router, a code-review loop, a content pipeline, a tutor. They are illustrative, not case studies of deployments by third parties.

Getting listed

We are as interested in what the format got wrong as in an endorsement — the first is more useful to the RFC process.

What qualifies: production or substantial development use of the specification, and willingness to share enough implementation detail that the entry means something to a reader.

How: open a GitHub Discussion with your organization, use case and scale. We will follow up to confirm details before listing you.

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