Overmind

The open source training platform for continuously improving agents and models

[Overmind @OvermindLab]

Overmind turns anyone into an AI lab.

• Builds a context graph from code and traces
• Curates training and eval datasets
• Evaluates prompts and models
• Trains smaller, specialized models

https://t.co/AEBRXmTE6M

[Overmind @OvermindLab]

@NVIDIAAI @freymehta @nvidia 🤜🤛

[Overmind @OvermindLab]

Overmind's eye sees all at @NVIDIAGTC

The vision in Europe is clear. The future belongs to companies that build their own intelligence.

Overmind brings vision and future into alignment.
Stay tuned.

[Freyam Mehta @freymehta]

in berlin this week for #nvidiagtc, representing @OvermindLab. the last few years were about building the biggest engine, and the next few will be won by the pit crew. come say hi if you are building agents 🙌

[Sam Morris @samsmallmind]

I used to wonder why there has been rising interest in "open weight models" across the realms... 🌎

Then I realised the @OvermindLab eye sees all.

[Overmind @OvermindLab]

How to connect Langfuse, LangSmith, Braintrust or Galileo: https://t.co/gFhJS4SVjl

[Overmind @OvermindLab]

If your traces live in Langfuse, leave them there.
Overmind imports them and trains a model on them.

Works from Claude Code, Cursor, Codex or OpenCode.

Get started: pip install overmind

[Turing Post (Ksenia Se) @TheTuringPost]

Top 14 open-source tools for LLM monitoring in 2026

▪️ Langfuse
▪️ Opik
▪️ Overmind
▪️ MLflow
▪️ LangWatch
▪️ AgentOps
▪️ Helicone
▪️ OpenLIT
▪️ OpenLLMetry
▪️ Evidently
▪️ Weave
▪️ OpenTelemetry Collector
▪️ Grafana OSS stack
▪️ Laminar

Bookmark the list to keep it handy!

Here is also a practical guide explaining all these observability tools - what each one does, and where it best fits → https://t.co/BaJYj4xIxk

[Overmind @OvermindLab]

@jji1jj 🎯

[Overmind @OvermindLab]

Own your agent's decisions.

Decision models pick an answer instead of writing one. Think Jev, Clef or OpenAI's Decisions API.

Overmind trains your agent on those decisions. The weights are yours.

[Overmind @OvermindLab]

47% fewer errors than Jev on a 4B model.

[Overmind @OvermindLab]

https://t.co/nluVGr7wlq

[Overmind @OvermindLab]

@Zai_org Specialists win on legal. Qwen3.5-9B vs GPT-5.6 Luna:

• 7X better at quoting a contract clause word for word
• 4X more accurate at reading a research paper
• 30X fewer phantom clauses in legal contracts

Next step: train one on your own contracts and own the weights.

[Overmind @OvermindLab]

Coinbase built this for their employees.
Overmind ships it for everyone.

Run /overmind finetune in:
• Claude Code
• Cursor
• Codex

Open source, and the model is yours.

[Overmind @OvermindLab]

@Sumanth_077 🎯

[Overmind @OvermindLab]

Coinbase built this for their employees.
Overmind ships it for everyone.

Run /overmind finetune in:
• Claude Code
• Cursor
• Codex

Open source, and the model is yours.

[Brian Armstrong @brian_armstrong]

We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case).

I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves.

We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them:

"/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started"

I imagine we'll have some backend services that could be replaced entirely by this new architecture.

[Overmind @OvermindLab]

@emaann28 Indeed

[Overmind @OvermindLab]

@HeavyDreamscv Agreed, the eval set is the hard part, so /overmind finetune won’t launch without a separate one.

With 500 messy rows our Data Workshop flags answers the inputs don’t support and can generate more training examples. The before/after eval tells you if 500 was enough.

[Overmind @OvermindLab]

@nodolas @jackson_felty 🤝

[Overmind @OvermindLab]

@AsifOnWeb3 ❤️‍🔥

[Kevin Simback 🍷 @KSimback]

@jackson_felty Check out @OvermindLab

[Overmind @OvermindLab]

@KSimback @jackson_felty Word. https://t.co/d3b0FXr7mu

[Overmind @OvermindLab]

Coinbase built this for their employees.
Overmind ships it for everyone.

Run /overmind finetune in:
• Claude Code
• Cursor
• Codex

Open source, and the model is yours.

[Overmind @OvermindLab]

Turn your company into an AI lab.

https://t.co/AEBRXmTE6M