Sovereign AI Infrastructure. Encrypted Intelligence.

v3.e-mini. AI on encrypted data.

Zero-knowledge AI inference.
The server processes your data without ever seeing it.

Every AI system today requires access to your data in plaintext. Every cloud API, every hosted model, every inference endpoint sees exactly what you send it. For classified, medical, financial, or sovereign data, this is a non-starter.

Engram eliminates this tradeoff. Our FP2-FHE breakthrough enables neural network inference through 128-bit encryption with zero accuracy loss. Paired with v3.5-mini, a cognitive architecture that reasons across multiple modes, this is sovereign AI infrastructure that requires no trust in the operator.

Try Encrypted Demo Contact
15,500x
Faster Than
Standard FHE
128-bit
Encryption
Strength
8B
Parameters
Proven
100%
Accuracy
Preserved
FHE Mode
Plaintext Mode (FP2)
Encrypted Inference 14.7 min/token
vs Standard FHE 158 days/token
Model Compression 7.1x vs BF16
Error Per Layer 0.09%
Two Models
v3.e-mini
Encrypted Inference
AI that processes data it cannot see. Built on our FP2-FHE breakthrough, v3.e-mini runs full neural network inference through 128-bit homomorphic encryption. The model never decrypts the input. The server never sees the output. Proven on billion-parameter models producing correct answers through encryption.
v3.5-mini
Cognitive Architecture
A reasoning engine that thinks in multiple modes. Diffusion for spatial problems, autoregressive for sequential logic, tree search for exploration. Internal cognitive state modulates every computation. Adapts its reasoning strategy at inference time without retraining. Built for sovereign, air-gapped deployment.
Applications
01
Sovereign Government AI
Run AI on classified data without exposing it to anyone. v3.e-mini processes encrypted queries on untrusted infrastructure. v3.5-mini runs air-gapped on government hardware. Full data sovereignty. Zero foreign API dependency. Auditable reasoning traces for every decision.
02
Defense and Intelligence
Encrypted inference on signals intelligence, sensor fusion, and threat analysis. The AI processes classified inputs through encryption and returns classified outputs. The compute infrastructure never sees the data. Multi-sensor reasoning with full audit trails.
03
Medical and Financial
Patient records, financial transactions, legal documents. Data that cannot leave the client's control, processed by AI models hosted anywhere. The model operator learns nothing. Full regulatory compliance by mathematical guarantee, not by policy.
04
Edge and Autonomous Systems
On-device cognitive reasoning for drones, robotics, and autonomous vehicles. v3.5-mini runs inference locally on embedded hardware. Spatial reasoning, persistent memory, instant adaptation. No connectivity required for mission-critical operations.
Technology
FP2-FHE
Encrypted Neural Inference
Fully homomorphic encrypted inference on real neural networks. 128-bit encryption, zero accuracy loss, proven on 8B-parameter models. A mathematical breakthrough that eliminates the computational barrier that made encrypted AI impossible.
nGDiT
Diffusion Reasoning
Discrete diffusion transformer for spatial and abstract reasoning. Sees the whole problem at once, forms hypotheses, iteratively refines. Not autoregressive. The model reasons about structure, not sequences.
Cognitive Mesh
Multi-Mode Routing
Learned router selects between autoregressive, diffusion, tree search, retrieval, and test-time adaptation. Each problem gets the right reasoning mode. One architecture, five ways to think.
State Engine
Cognitive State Vector
Internal state modulates every computation. Confidence sharpens predictions, uncertainty triggers exploration. The model adapts how it reasons in real time, not just what it outputs.
Anamnesis
Persistent Memory
Streaming compression of unbounded context into fixed-size representations. 160x compression ratio. The model maintains awareness across sessions without the context window ever filling up.
NeuroGen
Instant Adaptation
Generates task-specific model adjustments in a single forward pass. Standard adaptation takes 30 seconds. NeuroGen produces equivalent results in milliseconds. The model specializes itself per-task at inference time.