Mynd Labs ResearchThe core
AI Lab
How intelligence systems should be built, run and trusted.
The question
What would it take for an AI system to be something you can actually hold accountable?
Every Mynd Labs field runs on the same layer: models, agents, memory and tools. The AI Lab is where that layer is questioned from first principles, before any field depends on it.
Programs
5 directions we are working on.
- 01
Agent runtime
How an agent run becomes a thing you can pause, inspect, replay and compare, instead of a black box that either worked or did not.
- 02
Memory and context
What an assistant should remember, forget and refuse to carry across tasks, and how to prove it did what it said.
- 03
Evaluation
Tests that reflect real work. We want measures a field expert would sign off on, not only leaderboard numbers.
- 04
Safety and control
Permission, injection and failure behaviour in long, chained workflows, studied where they actually break.
- 05
Efficient intelligence
Doing more with smaller, cheaper and more local systems, so capability is not reserved for whoever can afford the largest cluster.