Daice Labs

Daice Labs — Digital co‑builders engineering adaptation The Problem Current AI shines on benchmarks but breaks in the wild—brittle under distribution shift, costly to retrain, hard to audit, and slow to adapt. The need? new hybrid paradigms that integrate today's models into systems that learn continuously, generalize, and explain their decisions. Approach Founded by MIT CSAIL scientists, we build hybrid/composite frameworks that combine LLMs/DL with symbolic reasoning and bio-inspired system design to deliver new architectures. Our name Pronounced “dice.” Dice evokes exploration; for us it’s programmable adaptation. Two meanings. 1) DAICE = Data‑driven AI for Context‑aware Evolution. 2) Dais = or stage—an integrative platform for co-builders. Two focus tracks 1) Product Lab Building a collaboration platform where human teams co-build with hybrid AI. Features: shared context fabric, role‑based models (ops, finance, R&D, commerce), vertical applications composed into a business‑in‑a‑box, and co‑ownership ledger audits for governance. 2) AI Research Lab Our lab investigates how principles of natural intelligence can guide the design of hybrid AI architectures. For example, living systems excel at "coordinated collaboration" via specialized structures or scaffolds. We believe that mimicking their system-level design will unlock new frameworks for AI generalization. - Translating biological, cellular, and evolutionary principles into system design. - Advancing perturbation‑aware learning and rule‑guided frameworks. - Developping cell-inspired architectures for guided program synthesis. The next Leap We believe that the next leap in productivity comes from collaboration—human teams and specialized AIs co-building on shared context, pushing boundaries for adaptation together. Interested? We're hiring–get in touch!

Website

https://daicelabs.com/

External link for Daice Labs

Industry

Research Services

Company size

2-10 employees

Headquarters

Brookline, MA

Type

Privately Held

Founded

2025

Specialties

Hybrid AI models, Composite architectures, Modeling, Data integration, Edtech, Commerce adaptation, Multi-model workflows, AI4Science, Bio-inspired computing, Natural intelligence, Neurosymbolic AI, Platform engineering, Context-aware systems, AI R&D, and Fintech