Research 04EU-hosted inference

Open-weight models, hosted in the EU.

Gedor is a platform for running language models in Europe: one OpenAI-compatible endpoint over a curated catalog of general, coding and embedding models, with managed vector databases alongside. Dedicated infrastructure and ready-made agents follow.

EU
One key.
One endpoint.

Jump to: How it works · Catalog · Layers · Roadmap · Waitlist

request.py

General purpose

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://<gedor-endpoint>/v1",
    api_key=os.environ["GEDOR_API_KEY"],
)

stream = client.chat.completions.create(
    model="glm-5.1",
    messages=[
        {"role": "user", "content": "Summarise our retention policy."},
    ],
    stream=True,
)

Response · streamed

Customer records are kept for as long as the contract runs, plus 24 months. After that they are deleted from production systems and backups within 30 days.

model · glm-5.1/v1/chat/completionsEU

Coding

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://<gedor-endpoint>/v1",
    api_key=os.environ["GEDOR_API_KEY"],
)

stream = client.chat.completions.create(
    model="qwen3-coder",
    messages=[
        {"role": "user", "content": "Validate an IBAN in Python."},
    ],
    stream=True,
)

Response · streamed

def is_valid_iban(iban: str) -> bool:
    s = iban.replace(" ", "").upper()
    s = s[4:] + s[:4]
    digits = "".join(str(int(c, 36)) for c in s)
    return int(digits) % 97 == 1

model · qwen3-coder/v1/chat/completionsEU

Embedding

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://<gedor-endpoint>/v1",
    api_key=os.environ["GEDOR_API_KEY"],
)

result = client.embeddings.create(
    model="bge-m3",
    input="GDPR Article 5: data processing principles",
)

Response · vector

[0.0213, -0.1137, 0.0582, 0.0094, -0.0461, 0.0718, …]
1024 dimensions

model · bge-m3/v1/embeddingsEU

Illustrative · switch the model, not the codeThe same OpenAI client for every model class. Only the model name changes. Endpoint, model IDs and responses are placeholders.

01 · Why EU-hosted

Your prompts stay under EU law

Most hosted LLM APIs run on infrastructure owned by companies outside the EU, so the data they process can fall under non-EU law as well as European law.

For teams handling financial, health, legal or public-sector data, that can rule them out before the first prompt. Gedor runs on GPUs in an EU data center, under EU law: GDPR and the EU AI Act.

EU-resident compute.
Inference and storage stay in an EU data center.
Open weights.
A curated catalog of open-weight models. No lock-in to one vendor's model.
Drop-in API.
Existing OpenAI-compatible clients work unchanged. Point them at a new endpoint.

02 · Architecture

How a request travels

From your code to a GPU and back, every hop after the gateway runs inside the same EU data center.

Gedor request pathA request leaves your application, passes the gateway, is scheduled by the orchestration layer, runs on an inference engine and GPU nodes in an EU data center, and the response returns the same way.Gedor · EU data centerOutside01Your appAny OpenAI client02GatewayAPI keys · rate limitsusage metering03OrchestrationKubernetes · KServescale-to-zero · canary04InferencevLLMPagedAttention · batching05GPU nodesEU data center Gedor request pathA request leaves your application, passes the gateway, is scheduled by the orchestration layer, runs on an inference engine and GPU nodes in an EU data center, and the response returns the same way.Gedor · EU data center01Your appAny OpenAI client02GatewayKeys · limits · metering03OrchestrationKubernetes · KServe04InferencevLLM · batching05GPU nodesEU data center
Request pathRequestResponseEverything after your app happens inside the boundary.
  1. 01

    Gateway.

    One OpenAI-compatible endpoint. It checks the API key, applies per-tenant rate limits and meters usage before anything reaches a model.

  2. 02

    Orchestration.

    Kubernetes with KServe places each model on the cluster, scales idle models to zero and rolls out new versions as canaries.

  3. 03

    Inference.

    vLLM serves the models, with PagedAttention and continuous batching to keep throughput high.

  4. 04

    GPU nodes.

    The compute itself, in an EU data center. The response goes back the way the request came.

03 · Catalog

Coming at launch

The open-weight models teams are deploying, curated, hosted and ready to call. Plus managed vector databases to pair with any of them.

General purpose

  1. 01GLM 5.1MIT
  2. 02Llama 4 MaverickCommunity
  3. 03Llama 4 ScoutCommunity
  4. 04Qwen 3.6 235BApache 2.0
  5. 05Mistral Large 3Apache 2.0
  6. 06Mistral Small 4Apache 2.0
  7. 07Gemma 4 27BGemma
  8. 08Gemma 4 12BGemma
  9. 09gpt-oss 120BApache 2.0
  10. 10Phi-4 14BMIT

Coding

  1. 01Devstral 22BApache 2.0
  2. 02GLM 5.1 CoderMIT
  3. 03Qwen 3 CoderApache 2.0
  4. 04Qwen 3.6 Coder 27BApache 2.0
  5. 05DeepSeek Coder V2MIT
  6. 06DeepSeek V4 ProMIT
  7. 07StarCoder 2 15BBigCode
  8. 08MiniMax M2.7MIT
  9. 09Granite Code 20BApache 2.0
  10. 10Yi Coder 9BApache 2.0

Embedding

  1. 01BGE-M3MIT
  2. 02BGE Large EN v1.5MIT
  3. 03Nomic Embed v1.5Apache 2.0
  4. 04Jina v5 Text SmallApache 2.0
  5. 05Jina CLIP v2Apache 2.0
  6. 06Qwen3 Embedding 8BApache 2.0
  7. 07Qwen3 Embedding 0.6BApache 2.0
  8. 08E5 Mistral 7B InstructMIT
  9. 09GTE Large EN v1.5Apache 2.0
  10. 10MPNet Base v2Apache 2.0

Managed vector databases · 8

  • QdrantApache 2.0
  • MilvusApache 2.0
  • WeaviateBSD-3
  • ChromaApache 2.0
  • LanceDBApache 2.0
  • VespaApache 2.0
  • OpenSearchApache 2.0
  • pgvectorPostgreSQL

The catalog is not final. Models and databases may be added, swapped or removed before launch.

04 · Retrieval

Your documents, next to your model

Start a managed vector database, upload files, and they are split into chunks, turned into embeddings and stored in a collection. Query it from the playground or over the API with the same key.

01 Upload

handbook.pdf

Collection
handbook
Chunks
6
Model
embedding

02 Embed & index

Six new document chunks join a collection of vectors; a query finds its three nearest neighbours.

New chunksQueryTop 3

03 Ask

How long do we keep support tickets?

Support tickets are kept for 24 months after they close, then deleted.

handbook.pdf · chunk 4chunk 5

Illustrative · prototypeUpload, embed, ask: the flow from our working prototype. Retrieval and generation run in the same EU data center.

05 · Platform

Three layers, one platform

The pipeline from model to vector store to agent is meant to be something a team can set up without an ML department.

01 · ModelsLaunching first

Models as a service.

The hosted catalog behind one OpenAI-compatible API, with managed vector databases next to it.

02 · InfrastructurePlanned

Dedicated EU compute.

Dedicated GPU capacity for your own models. Bring a model and its deployment spec, and reach it through the same API.

03 · AgentsPlanned

Agents as a service.

Ready-to-use agents for documents, web research, email and calendar, and long-form research. Already have one? Bring your own agent and run it on EU infrastructure.

06 · Audience

Who it's for

Teams that want open models without sending their data out of the EU.

01

Regulated teams.

Finance, health, legal and the public sector, where data has to stay in Europe.

02

Product teams.

Add language models to a product without building or running the infrastructure.

03

ML engineers and research groups.

Dedicated EU compute for your own models, once the infrastructure layer opens.

04

Business users.

Ready-made agents for everyday workflows, once the agent layer arrives.

07 · Roadmap

Where it's headed

Models first, then infrastructure, then agents.

01
DoneWorking prototype
Managed vector databases, file upload, a chat playground and API keys, running end to end.
02
NextModels API
The catalog, vector databases and self-service keys. The waitlist is open now.
03
PlannedInfrastructure
Dedicated EU GPU capacity for your own models.
04
PlannedAgents
Agents on demand, fine-tuning pipelines, our own vector store and agent memory.

08 · Waitlist

Get in line

Gedor is built by Astro Synapse. Join the waitlist for early access and a say in what goes into the catalog.

Code samples and figures on this page are illustrative. The model catalog is not final.