> For the complete documentation index, see [llms.txt](https://docs.layerlens.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.layerlens.ai/1.-introduction/three-experiences.md).

# Three experiences (Public · Premium · SDK)

Stratix Public, Stratix Premium, and the Python SDK — what each one is for and how they work together.

LayerLens Stratix is delivered as three distinct customer-facing experiences. They share one catalog, one judge engine, and one trace pipeline — but each one is shaped for a specific kind of user and a specific kind of question.

## Side by side

|                             | Stratix Public                      | Stratix Premium                            | Python SDK                                                                 |
| --------------------------- | ----------------------------------- | ------------------------------------------ | -------------------------------------------------------------------------- |
| **Where**                   | `stratix.layerlens.ai` — signed out | `stratix.layerlens.ai` — after you sign in | `pip install layerlens --extra-index-url https://sdk.layerlens.ai/package` |
| **Auth**                    | none                                | OAuth (Google, GitHub) + email             | API key (`X-API-Key`)                                                      |
| **Audience**                | researchers, buyers, the curious    | builders, operators, admins                | builders, automation, CI/CD                                                |
| **What you do**             | browse, compare, read               | build, evaluate, govern                    | automate, integrate, batch                                                 |
| **Catalog visibility**      | full public catalog                 | full public + private                      | full public + private                                                      |
| **Private evaluations**     | no                                  | yes                                        | yes                                                                        |
| **Build judges**            | no                                  | yes                                        | yes                                                                        |
| **Trace upload**            | no                                  | yes                                        | yes                                                                        |
| **GEPA judge optimization** | no                                  | yes                                        | yes                                                                        |
| **Org and team management** | no                                  | yes                                        | n/a                                                                        |
| **Cost**                    | free                                | free + ECU PAYG                            | free + ECU PAYG                                                            |

## Stratix Public — the showcase

Anonymous browsing. No account required. Built for researchers, AI buyers, and anyone who wants to know "which model is actually best at X right now."

You can:

* Browse 175+ models with metadata, benchmark scores, and the latest leaderboard
* Browse 52+ benchmarks with descriptions and per-model scores
* Browse 2,000+ public evaluations
* Compare any two models head-to-head across any shared benchmark
* Browse public evaluation spaces — curated bundles of model + dataset + scoring
* Search the entire catalog
* Read the quarterly research reports

You cannot:

* Run a private evaluation on your data
* Save or share work to a personal workspace
* Build judges or scorers
* See trace data

Stratix Public is the doorway. Most users start here, find a model or a benchmark they care about, and continue into Premium when they're ready to evaluate against their own data.

## Stratix Premium — the workspace

Logged-in. Multi-org. Pay-as-you-go on compute. Built for teams shipping AI features.

You can:

* Run **private evaluations** on your own data
* Build **LLM judges** for subjective dimensions and optimize them with **GEPA**
* Upload **traces** and run **trace evaluations** against scorers and judges
* Manage **scorers** (code graders) at the org level
* Run **agentic evaluations** — pre- and post-deployment quality gates for multi-step agents
* Use **BYOK custom models** — register your own OpenAI-compatible endpoint
* Manage **organizations**, multi-org membership, and team seats
* Buy and consume **ECU credits**
* Browse the **Learning Library** and follow **Paths**

The left rail is: Home, Evaluations, Models, Benchmarks, Scorers, Spaces, Agent Evaluation (Traces, Judges), Learning (Library, Paths), Settings, Notifications. ECU balance and Buy Now appear in the header. The in-app **Assistant** offers context-aware help. The **Switch toggle** lets you flip between the Public and Premium catalogs without losing context.

## Python SDK — the automation surface

`pip install layerlens --extra-index-url https://sdk.layerlens.ai/package` (v1.3.0). 11 resources, 138 sample programs.

You can:

* Programmatically create evaluations, judges, scorers, traces
* Run trace evaluations as part of CI/CD
* Sync results into your own data warehouse or BI
* Automate judge GEPA optimization
* Integrate with frameworks (LangChain, LlamaIndex, Haystack, etc.) via instrumentation samples

The SDK is sync-and-async. Both `client.evaluations.create()` and `await client.evaluations.acreate()` work.

## How they work together

A typical team uses all three:

1. **A researcher** browses the public catalog and picks the three candidate models that look strongest on a relevant benchmark.
2. **A builder** logs into Premium, runs a private evaluation on the team's own dataset, and chooses a winner. They build a judge that captures the team's quality bar.
3. **A platform engineer** wires the SDK into CI/CD: every PR that changes a prompt re-runs the evaluation. Judges and scorers gate the merge.
4. **An operator** ingests live traces and runs trace evaluations on a daily cadence. Quality regressions surface in a dashboard before they surface to customers.

## Where to next

* [Stratix Public](/1.-introduction/01-introduction.md)
* [Stratix Premium](https://github.com/LayerLens/gitbook-full/blob/main/05-select/catalog/premium-workspace-overview.md)
* [Python SDK](/6.-build-wire-your-code/sdk-python.md)
* [Getting started](/2.-get-started/02-get-started.md) — choose a path and ship