Turn messy aliases into governed search context.

SkeinRank governs profiles, bindings, snapshots, and evidence workflows for terminology-aware search, RAG, and Elasticsearch integrations.

Run Docker beta Local SDK quickstart View on GitHub

Open-source terminology control plane for search and RAG

Turn messy aliases into governed search context.

SkeinRank sits beside your search stack, normalizes domain jargon, pins runtime snapshots, and makes every query context explicit through profiles, bindings, and evidence workflows.

Run Docker beta Explore console workflow View on GitHub

Input aliases Noisy company language

SkeinRank Terminology control plane

snapshot infra_incidents / S42

Runtime output Search-ready context

Messy aliases k8s · kube · pg · postgres

SkeinRank profiles · bindings · snapshots

Runtime context canonical query · evidence · RAG

The problem

Enterprise search loses context when terminology is unmanaged.

Without SkeinRank

Search and RAG pipelines depend on raw text. k8s, kube, postgres, pg, team names, and internal aliases compete without a governed runtime model.

With SkeinRank

Terminology changes are reviewed, bound to specific search contexts, rolled out through enrichment, and served from immutable snapshots that explain what runtime search is using.

Console workflow

From terminology governance to verified search behavior.

The governance console is designed as an operator workflow: run the Docker beta stack, define terminology, apply it to an index, run enrichment, audit the active snapshot, and test the runtime query path before integrating it downstream.

Profile

Create a terminology profile with canonical terms, aliases, slots, suggestions, and guardrails.

Binding

Attach one profile to one Elasticsearch index, alias, or scoped document collection.

Enrichment

Run dry-runs and jobs that write canonical attributes or prepare rollout metadata.

Snapshot

Audit the immutable runtime version currently pinned to each binding.

Search Playground

Verify canonical queries, matched aliases, snapshots, and search hits from the UI.

Product shape

A side-car for terminology-aware search, not a replacement for your search stack.

◎

Runtime search context

Use bindings to decide which terminology profile, index, fields, filters, and snapshot belong to a query.

Console beta

↔

Canonicalize terminology

Normalize aliases and jargon into stable technical values controlled by profiles and guardrails.

Available

⌘

Run locally with SDK/CLI

Validate dictionaries, extract attributes, and canonicalize text or documents without deploying services.

Available

◈

Govern changes

Review suggestions, enforce stop-lists, manage users/tokens, and keep terminology changes auditable.

Console beta

⇡

Enrich search indexes

Run dry-runs and enrichment jobs against Elasticsearch bindings with job history and rollback metadata.

Preview

▣

Audit runtime snapshots

See which immutable version is active for each binding and why a search context is ready or stale.

Console beta

Side-car model

SkeinRank sits beside Elasticsearch, RAG, and internal search UIs.

It does not need to replace the existing search engine. It manages domain terminology, produces canonicalized signals, and exposes runtime APIs that your application can call by binding or search scope.

Read the side-car model → Run the Docker beta stack →

Existing stack Search UI / backend / RAG service

calls SkeinRank runtime API binding_id

uses runtime snapshot pinned

searches Elasticsearch / document index existing data

Current status

Public positioning: usable core, beta governance platform.

The site presents SkeinRank honestly: the core SDK/CLI path is the smallest stable entry point, while the governance console and Elasticsearch workflows are documented as beta/platform preview.

Area Status Meaning

Core SDK / CLI Available Local validation, extraction, canonicalization, and explainable passport output.

Governance console Beta Dashboard, Terms, Suggestions, Guardrails, Integrations, Snapshots, Search Playground, API Access, and Users.

Elasticsearch enrichment Preview Bindings, dry-runs, enrichment jobs, graph view, rollout metadata, and snapshot audit.

Docker beta stack Beta docs Local Docker Compose quickstart for the governance UI, API, PostgreSQL, Elasticsearch, RabbitMQ worker, and optional observability profile.

Try the beta stack

Run the console locally, then follow the workflow.

Start with Docker Compose for the platform beta, or read the runtime model before connecting real search indexes.

Run Docker beta Read runtime model