The Problem
AI systems shine on benchmarks but break in the wild—brittle under distribution shift, costly to retrain, hard to audit, and slow to adapt. The need: hybrid paradigms that integrate frontier models into systems that improve over time, generalize reliably, and explain decisions.

Our Approach
Founded by MIT CSAIL scientists, we combine research and product innovation to build hybrid AI systems—composite architectures that are auditable, governable, and adaptive by design.

Our Product
As software becomes more accessible, the frontier shifts to what's harder to replicate: systems strategy, adaptive AI, deep collaboration, and governed context.
Daice Labs is the collaboration fabric where human teams supervise, co-build, and co-own long-horizon outcomes—products, discoveries, and innovations.
An automated (VC-like) incubator layer sponsoring builders and backing key products and research through integrated "Engineering-in-a-Box" workflows with shared context, sandboxed execution, role-based verticals, and a co-ownership ledger for governance and attribution.

Our Research
Our R&D lab ships the primitives that power Daice Labs' long-horizon execution engine: (i) accelerating discovery through hybrid AI; (ii) building system-level governance through systems engineering, natural intelligence, and bio-inspired design—composite frameworks combining generative model intuition, symbolic precision, and bounded modularity; (iii) engineering adaptive systems for long-horizon execution.

The Next Leap
We believe we're entering an era of systems of systems, where the next leap in productivity comes from long-horizon collaboration—co-building on shared context and governance, pushing boundaries together.

Our Name
Pronounced “dice”—exploration & programmable adaptation.
DAICE = Data‑driven AI for Context‑aware Evolution.
Dais = the stage—platform for co-builders.

We're hiring—get in touch!