Quanta Labs unveils 'NeuroShard' — a shardable LLM for on-prem enterprise deployment

AI · 5 min read

Quanta Labs released NeuroShard, a shardable LLM architecture that enables enterprises to split model inference across multiple on-premise nodes. This architecture is aimed at organizations with strict data residency and compliance mandates that cannot rely on cloud-hosted models.

NeuroShard uses a combination of attention routing and compressed context passing to maintain cross-shard coherence, allowing models to behave as a single logical LLM while keeping raw inputs local to a customer's infrastructure. The company claims performance parity with cloud deployments on many common enterprise tasks.

Quanta Labs backed the launch with an $85 million funding round led by Bessemer, earmarked for enterprise integrations, cryptographic auditability features, and partnerships with systems integrators. The offering targets regulated industries such as finance, healthcare, and defense.