K-Veritas CLI
K-Veritas binds a published result, or an AI agent's actions, to the exact code, hardware, and time that produced it. Reports are signed by a hosted attestation server that only ever sees hashes, never your data. Verification is offline and needs no account.
The tool does two things:
Wrap a run, capture its metrics, provenance, and hardware evidence, and seal a signed PDF that anyone can verify offline.
Record a tamper-evident, hash-chained log of everything an AI agent does, so no designated action can happen off the record.
Installation
Install the CLI as a single static binary:
curl -fsSL https://github.com/27-GROUP/kveritas-releases/raw/main/bin/kveritas-linux-amd64 -o kveritas chmod +x kveritas sudo mv kveritas /usr/local/bin/
From source
If you have Go 1.22+ installed, build it yourself:
git clone https://github.com/27-GROUP/kveritas-go.git cd kveritas-go make build
Platforms
Prebuilt binaries exist for Linux (amd64, arm64), macOS (Intel, Apple Silicon), and Windows (amd64) - see the Download page. Some capabilities are Linux-only today; each guide notes what is Linux-only and what is coming, and the Reference has a platform-support table.
Quick start
From experiment to verified report in four commands:
kveritas init kveritas run -- python train.py --epochs 50 kveritas seal --output report.pdf kveritas verify report.pdf
initStart a session (redacted disclosure by default).runWrap your experiment: capture metrics, provenance snapshots, and per-process hardware.sealSign everything into a PDF report.verifyCheck the report offline. No account, no internet.
To record a metric, print a KVERITAS_METRIC line from your script in any language - K-Veritas parses it from stdout as the run proceeds:
print("KVERITAS_METRIC name=val_accuracy value=0.9471 step=100")Reports can also be verified in the browser at kveritas.org/verify.