An invisible software layer that compresses KV cache load and reduces memory overhead — across text, image, audio, and video. No retraining. No weight changes. Built for production inference.
115 GB → 252 MB · 456× memory reduction.
100 users at 8K-token prompts, Mistral-7B.
syntropic.activate(model) into an existing transformer workflow and keep inference behavior intact.
456×Memory Reduction
8×KV Compression
+5.3%vs Google TurboQuant
70+Patent-Pending Applications
H100 SXMValidated
$300B+Total Addressable MarketSyntropic patches your model's attention layers transparently. Inference runs exactly as before — compression is invisible.
Transparent to your inference pipeline. Your application calls the model exactly the same way — Syntropic handles everything inside the attention layers.
syntropic.deactivate(model)# pip install syntropic[huggingface] from transformers import AutoModelForCausalLM import syntropic model = AutoModelForCausalLM.from_pretrained( "mistralai/Mistral-7B-v0.1" ) # One line — patches all attention layers syntropic.activate(model) # Inference is unchanged outputs = model.generate(**inputs) # Live stats stats = syntropic.get_compression_stats(model) # → {'ratio': 8, 'memory_reduction': 456, # 'ppl_delta': 0.0935} syntropic.deactivate(model) # fully reversible
A multi-layer patent portfolio spanning compression algorithms, inference systems, training-side techniques, multimodal extensions, and security & compliance. Detailed architecture available under NDA.
VALIDATED ON: NVIDIA H100 SXM · Production-grade benchmarks · Mistral-7B & Llama-3.1-8B · Real forward passes · v0.8.0 Docker container.
Forward-pass benchmarks on production hardware. Real models. Real perplexity. No simulations.
Every industry that generates, stores, or transmits AI data. Syntropic's compression works across all of them — text, image, audio, video, embeddings.
A focused team turning patent-pending compression research into production infrastructure.
Founder and sole inventor on Syntropic's 70+ pending patent applications. Architected the platform from foundational compression algorithms through production deployment. The technical lead on every layer.
Former Microsoft executive. Enterprise-scale operational leadership and institutional investor relationships, scaling from invention to global market.
Built the Syntropic GPU benchmark suite — validated KV-cache compression on Mistral-7B & Llama-3.1-8B on NVIDIA H100 SXM. Engineering lead across every Syntropic layer.
Brand identity, thesyntropic.com, and core web presence. Translates the technical platform into investor-grade visual communications.
Strategic business development across AI infrastructure. Connects Syntropic's compression platform with enterprise integrators, channel partners, and ecosystem alliances.