mozilla.ai

@MozillaAI
218 Followers
10 Following
179 Posts
Open, transparent AI for real world impact. Built for developers, creators, and teams shaping what’s next.
Websitehttps://www.mozilla.ai/
Agent Platformhttps://www.mozilla.ai/product/agent-platform
Choice-First Stackhttps://www.mozilla.ai/open-tools/choice-first-stack

We’re happy to welcome Caroline Bohu to Mozilla.ai as our new Solutions Engineer.

Caroline focuses on making technology easier for people to understand and use, working closely with partners and teams adopting AI tools.

Outside of work she’s a proud mum who enjoys good food, great adventures, and a good book.

We’re hosting the Octonous workshop in Lisbon 🇵🇹 today.

It’s a hands-on session where you’ll build an AI agent for a real task.

Bring a task and leave with a working AI agent.

No technical skills needed.

A few seats are still available.

Join here: https://link.mozilla.ai/octonous-lisbon

https://Mozilla.ai is now a launch partner of Flower Hub.

We published a new project called **fed-phish-guard**, which trains a phishing URL classifier using federated learning.

Each client trains locally and only sends model updates back to the server, keeping browsing data private.

Read the blog post here: https://link.mozilla.ai/flower-hub

Check the project page here: https://flower.ai/apps/mozilla-ai/fed-phish-guard/

LLM providers differ in streaming behavior, error semantics, and supported features.

any-llm-go normalizes those differences behind a single Go interface so applications can work across multiple providers.

Take a look at the repository: https://link.mozilla.ai/any-llm-go-repo

BYOTA combines a few tools to experiment with timeline algorithms.

https://Mastodon.py retrieves posts from Mastodon timelines.
llamafile runs language models locally.
marimo provides an interactive notebook in the browser.

Watch the full talk: https://link.mozilla.ai/sfscon-byota

The real bottleneck for many solo contractors is the paperwork.

Nathan Brake, Senior ML Engineer, is leading Clawbolt: a messaging-first AI assistant built for teams of one.

Estimates, memory, voice memos, photo documentation, reminders.

Check out our latest project: https://link.mozilla.ai/clawbolt-ai

Many timeline algorithms share the same basic steps:

1. Moderation
2. Candidate generation (posts you’re likely to like)
3. Ranking and re-ranking (changing the order)

It’s a simple structure, but it shapes what you see.

Watch the full session: https://link.mozilla.ai/sfscon-byota

https://Mozilla.ai is headed to SCALE 23x in Pasadena.

SCALE takes place March 5 to 8, 2026 and is North America’s largest community run open source conference.

Anushri, Raz, Nathan, and John will be there.

Visit us at booth #126 and say hello. Join us in Pasadena: https://link.mozilla.ai/scale23x-2026

any-llm is meeting developers where they already build.

Recent integrations:
• JupyterLiteAI via any-llm-gateway (OpenAI-compatible endpoint)
• langchain-anyllm on PyPI, now in official LangChain docs
• Headroom + any-llm backend for context optimization

Build with us: https://link.mozilla.ai/any-llm-integrations

We tend to focus on prompts.

But where are your API keys stored?

any-llm Managed Platform encrypts keys client-side and keeps them out of your codebase.

One virtual key across providers. Usage + cost tracking built in.

Give it a go: https://link.mozilla.ai/any-llm-platform