Research
Open research on decentralized AI.
Tenzro Labs publishes papers, specifications, and reference implementations on distributed AI compute, verifiable training, tokenized inference, and agentic settlement — open and reproducible.
Active research areas
- 01Verifiable trainingDecoupled DiLoCo–style protocols, signed receipts, run-root commitments, and Byzantine-robust aggregation for distributed training across untrusted contributors.
- 02Tokenized inferencePer-token billing, micropayment channels, and proof-anchored receipts for AI inference across heterogeneous providers — STARK proofs and TEE attestation as substitutable substrates.
- 03Confidential AI computeHardware-attested AI workloads across Intel TDX, AMD SEV-SNP, AWS Nitro, and NVIDIA GPU CC — and what it means to make TEE a consensus primitive rather than a sidecar.
- 04Agent identity & settlementSelf-sovereign agent identity (TDIP), FROST-Ed25519 threshold wallets, mandate scoping, and cross-VM settlement for the agentic economy.
- 05Embedded AI clustersScheduling, sharding, and pipelined inference across embedded AI hardware — bringing distributed AI compute to environments where data centers don't reach.
- 06AI governanceOpen standards, on-chain attestations, mandate-based delegation, and evaluation tooling — making AI accountability technically enforceable.
Where to find it
Our research is published openly — papers, specifications, code, and evaluation harnesses.
Reference implementations are in the public Tenzro Network repositories. Specifications and papers are also published through the Tenzro Foundation, the non-profit steward of the public-interest work. Where appropriate, we contribute upstream to open standards bodies on agentic-web protocols, identity, and payments.