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Projects using FastStream#

Below are projects and organizations with public evidence involving FastStream: repository and package dependencies, employer job postings, and individual team members' reports. Each section identifies the evidence and its scope. Tools with a FastStream integration are listed separately.

About this list

This list is compiled from public sources. Job requirements and personal accounts are not organization confirmations or proof of current production use. Inclusion does not imply endorsement, support, or any affiliation with the FastStream project. If your organization is listed and you would prefer not to be, open an issue and we will remove the entry.

Science and Public Sector#

Name Who they are Project
ECMWF European Centre for Medium-Range Weather Forecasts IonBeam — streaming library for IoT data
Hydro-Québec Quebec's public electricity utility building-intelligence — building data middleware, four services, plus predictive control
it@M IT services provider of the City of Munich zammad-ai — GenAI agent for Zammad, and riski
Rubin Observatory / LSST Science Quality and Reliability Engineering (SQuaRE) team Safir — their framework for FastAPI services
NCATS (NIH) / PolusAI National Center for Advancing Translational Sciences aithena — RAG systems
Catasto Open Italian land registry catasto-cdc — change data capture for property changes
Data Cellar EU federated energy dataspace participant-template — participant onboarding services
LMDDC Luxembourg Media & Digital Design Centre alice.skilltech.tools — educational chatbots grounded in course materials
NHS Lancashire & South Cumbria SDE NHS secure data environment neulander — three services
IT'IS Foundation Foundation for Research on Information Technologies in Society osparc-simcore — simulation framework
CTIC CTIC Technology Centre, Spain connector-building-blocks — Eclipse Dataspace Components tooling
QCrBox Quantum Crystallography Toolbox QCrBox — small-molecule crystallography
NERSC National Energy Research Scientific Computing Center, US DOE interactEM
HBB (AI·SW Maestro 17th) Dev team in AI·SW Maestro, a software talent programme in Korea Kkori-AI — AI worker of Kkori, an interview-prep service: analyses uploaded resumes and generates interview reports

Companies#

Name Who they are Project
Red Hat enterprise open-source vendor qontract-reconcile — App-SRE reconciliation tooling
MWS MTS Web Services, digital product ecosystem data-rentgen — data lineage
Numberly marketing technology company reviewate — AI code review agent
Gravitate AI platform for the fuel supply chain bb-integrations-library — shared integration-job logic
hao.vc builders of AI-autonomous orchestrators haolib — their default backend template
KIWIQ multi-agent AI vendor kiwiq — multi-agent orchestration platform
Lemma runtime for agent-built software lemma-platform — workspace where humans and AI agents work as one team
spoo.me link management service spoo — API-first link management infrastructure
EggAI agentic workforce automation EggAI — async-first multi-agent meta framework
AgentArea control layer for agent teams agentarea — cloud-native AI agent orchestration
xi.effect / Sovlium education platform xi.back-2 — main backend service
Aeluin Technologies data integration and analytics vendor Galadril — causal analysis and system foresight platform
Waldiez multi-agent AI orchestration platforms runner — deploys Waldiez flows
traide AI AI for customs processes traide-core-python — shared library for their services
TogetherCrew open-source community tooling hivemind-bot — their LLM bot
TL;DR.tv TL;DR.tv platform team tldr-common — shared utilities and models

Organizations Naming FastStream in Job Postings#

These employer postings and their mirrors name FastStream in the team's stack, development responsibilities, requirements or desirable skills. The distinction is recorded in each row: requirements and alternative tools show demand for skills, but do not establish adoption. Some roles involve client projects; unidentified clients are not counted as adopters.

All posting links below are archived snapshots from 2026-10-06. These include closed and historical postings, which describe the stated technologies at the time rather than current hiring or confirmed production deployments. Locations refer to the vacancy's market or work location.

Organization / vacancy market What the posting says Archived posting
AI Implementation Group — Tashkent, Uzbekistan Requirements: Python backend role accepts knowledge of one or more frameworks, including Django/Flask, FastAPI or FastStream; it does not identify an established FastStream stack. LinkedIn, archived 2026-10-06
Arnia Software — Romania Requirements: Senior Python developer for energy trading and risk management; experience with Python, FastAPI and FastStream. The end client is not identified. LinkedIn, archived 2026-10-06
Code Metal — United States, remote Nice to have: Senior backend engineer; event-driven architecture experience with tools such as Celery, FastStream or Kafka. FastStream is an example, not a declared dependency. Built In Boston, archived 2026-10-06
Global Changer — Berlin, Germany Team stack: Senior Ruby backend role lists Python, FastAPI and FastStream under AI & Services, with NATS for messaging. Built In, archived 2026-10-06
HUDstats — Bulgaria, remote Development responsibilities: Backend engineer building Python services with FastAPI/FastStream for real-time esports computer vision and data processing. LinkedIn, archived 2026-10-06
mylantech GmbH — Bulgaria, remote Development responsibilities: Python application engineer building event-driven microservices with FastAPI and FastStream, alongside Kafka and Azure/Kubernetes. The end client is not identified. LinkedIn, archived 2026-10-06
Next Kraftwerke — Cologne, Germany Team technologies: Python developer for balancing energy and redispatch; Django, FastAPI and FastStream, with RabbitMQ and Azure. Employer career site, archived 2026-10-06
Octopus Energy Trading — London, UK Team stack: Software engineer; FastStream for streaming microservices supporting energy trading, alongside Redis, FastAPI and Airflow. Work in Green, archived 2026-10-06
Partoo — Paris, France Team stack: Senior backend developer; FastStream alongside Python, FastAPI, Celery and SQLAlchemy. HubMub, archived 2026-10-06
TripleTen / Nebius Academy — remote Team stack and responsibilities: Full-stack developer in the upskilling team; FastStream in the Python backend and Kafka/FastStream data-flow orchestration. Neo Remote Jobs, archived 2026-10-06
Unumbio — remote LATAM Desirable skills: Python PDF, scraping and ETL role; FastStream is one of the task-orchestration tools listed alongside Celery and RQ. LinkedIn, archived 2026-10-06
Yolk — Tel Aviv District, Israel Team stack: Senior backend engineer for an AI sales-coaching platform; RabbitMQ and FastStream for messaging. LinkedIn, archived 2026-10-06

Additional postings and organization-confirmed deployments are listed in ADOPTERS.md.

Usage Reported by Individual Team Members#

These authors describe their work on specific products. Their accounts are attributed to them, not presented as organization confirmations. They do not establish current organization-wide or production use; the Magalu Cloud account refers to the employment period shown below.

Organization Reported use Source
Magalu Cloud — Brazil Lucas França reports working on the first Load Balancing as a Service (LBaaS) product as a senior software developer, December 2023–June 2024. His project technologies include FastStream, RabbitMQ, FastAPI and OpenStack. This is a historical account of one team. Lucas França’s public CV, p. 2, archived 2026-10-06
Skan.ai Mubarak Abdulla (author bio: Chief Architect) describes using FastStream to decouple Skan.ai's event-processing application logic from RabbitMQ and enable future migration to Kafka or NATS. The article does not establish deployments on those other brokers. Architecture case study by Mubarak Abdulla, published 2026-01-06
Tektome — Tokyo, Japan Pumidol Leelerdsakulvong reports designing and implementing an ingestion, conversion and extraction queue for 3D models and large PDFs using RabbitMQ and FastStream. Tektome’s team page confirms his role as Technical Product Lead. Technical lead’s personal site, archived 2026-10-06; official team page

Tools Shipping a FastStream Integration#

These are not users but neighbouring projects that took on maintaining an integration of their own.

Name Who they are Integration
Pydantic Logfire observability platform from the Pydantic team FastStream integration — documented and covered by CI tests
RabbitMQ message broker client libraries and developer tools — FastStream listed among the clients in the official documentation
EMQX MQTT broker MQTT-Client-Examples — mqtt-client-Python-FastStream in the official client examples
NATS messaging system official blog — guest post on FastStream
dependency-injector dependency injection framework examples/miniapps/faststream — plus a documentation page
dishka dependency injection framework dishka — built-in FastStream integration
AnyDI dependency injection framework anydi — built-in FastStream integration
that-depends dependency injection framework that-depends — built-in FastStream integration

Community Extensions#

Packages built on top of FastStream by the community:

Add Your Project#

Using FastStream in production? There are two lists, and they serve different purposes.

ADOPTERS.md — organization confirmations maintained by adopters themselves. Add your organization along with the brokers you run, your use case and your scale. That last part is what other teams are really looking for, and only you can supply it. The quickest route is editing the file in the browser — GitHub opens the pull request for you. If you would rather not open one, comment on issue #3143 and we will add the row for you.

This page — compiled by us from public repositories, package metadata, job postings and attributed team-member reports. Include a public source and distinguish a dependency, a stated team stack, a skill requirement or a personal account. If we have missed a project, open a pull request against docs/docs/en/who-uses.md, or comment on issue #3143.

If you are listed on either and would prefer not to be, open an issue — no explanation needed and no questions asked.