The most efficientfoundation models.

Our proprietary architecture delivers state-of-the-art performance with 10× less compute. Purpose-built for text, audio, video, and physical simulation.

10×
More Efficient
Performance Gain
O(1)
Memory Scaling

Foundation models for every modality.

State-of-the-art performance at a fraction of the compute. Deployable anywhere you need them.

Text Models

Production Ready

High-performance language models with unlimited context windows. Optimized for reasoning, generation, and understanding.

FDRA-1BFDRA-7BFDRA-13B
Long-form GenerationCode CompletionDocument AnalysisConversational AI

Audio Models

Coming Soon

End-to-end audio foundation models for speech and sound. Designed for low latency, real-time applications.

FDRA-Audio-1B
Speech-to-TextText-to-SpeechVoice CloningAudio Classification

Vision Models

Coming Soon

Multimodal models for image and video understanding. Efficient deployment on edge and cloud.

FDRA-VL-3BFDRA-VL-7B
Image RecognitionVideo AnalysisObject DetectionScene Understanding

Simulation Models

Research

Foundation models for physical simulation and scientific computing. High fidelity with real-time performance.

FDRA-Sim-1B
Physics ModelingRoboticsDigital TwinsScientific Computing

Need a custom model? We train bespoke models on your data.

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State-of-the-art at every scale.

FDRA models consistently outperform comparable architectures across standard benchmarks while using a fraction of the compute and memory.

Constant Memory
O(1) memory regardless of context length
Unlimited Context
No artificial context window limitations
Faster Training
10× more efficient than standard transformers

Benchmark Comparison

FDRA-7B vs. comparable 7B models

BenchmarkFDRABaseline
MMLU (5-shot)72.468.1
GSM8K (0-shot)58.345.2
HumanEval48.241.5
IFEval74.965.3

* Baseline represents average of comparable 7B parameter models

A new architecture for AI.

Traditional transformers hit fundamental limits in memory and compute that scale quadratically with context length. FDRA is a ground-up redesign that achieves constant memory usage, enabling models that reason over unlimited context.

Our team has developed a proprietary architecture based on novel mathematical foundations. The result: state-of-the-art performance with dramatically lower compute requirements. We're building the infrastructure for the next generation of AI.

2025
Founded
Cambridge
Headquarters
Series A
Stage

Get started with FDRA

Ready to build with the most efficient foundation models? Talk to our team.