Services
Delivery models and flagship work
Alopex Family
Asopitech Labo
NiminoDesktop
A lightweight WebView desktop foundation in Nim
NimculusEditor
A GPU-native editor in Nim and Metal
PoieraPlatform
A control plane concept for AI agents, carrying compact contracts through authorization, deployment, and verification
TheatoraBackend
A composable backend construction kit concept for swapping providers, runtimes, and topology
RhyzoraFramework
A concept for building CLI, TUI, Web, desktop, and MCP interfaces from declarative contracts
Labo overview
What the R&D lab is working on
Enterprise plans
Use case
Alopex ships Python wheels with every release (officially supported). Use SQL, vector search, and graph straight from Python, with no separate infrastructure to stand up — and scale from a single embedded instance to a production cluster on the same data file.
Install
pip install alopexThe alopex package — both the Database and DataFrame APIs.
Use it from Python
import alopex
db = alopex.Database.open("./my_data")
results = db.execute_sql(
"SELECT * FROM docs WHERE category = ?",
["science"],
)
similar = db.search_hnsw("docs", query_embedding, k=10)The same data file, seamlessly from embedded to server to distributed cluster.
VECTOR type, HNSW, and vector_similarity() built into SQL.
Full SQL, plus a Polars-style lazy DataFrame API.
Runs embedded, scales out when you need it — no second infrastructure.
Database
An open-source database for teams that start with an embedded database and want to keep the same one as they scale.
AI / RAG
Microsoft GraphRAG for AWS (Bedrock + Anthropic)
Database
SQLite for the MVP, Postgres as you grow, a vector DB for AI features. See how Alopex DB cuts that chain of migrations, stage by stage.