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What's your next
big move?

Every computation you run could be cryptographically provable. Every Databricks job, every Snowflake query - all backed by tamper-evident attestation that auditors actually trust.

Runs on AWS • Azure • GCP • Databricks • Snowflake

AWS
Google Cloud
Azure
Databricks
Snowflake

Trust Issues

How do you prove your ML model actually trained on the data you claim? Now you can.

Audit Trails

Compliance teams love cryptographic proof. No more explaining why your results are valid.

Reproducibility

Research should be verifiable. This makes your computational work actually reproducible.

For Engineers

Three steps. Takes about two minutes to set up. Works with whatever you're already doing.

1

Install Anansi

Works with your existing setup

Just a pip install. No config files, no setup scripts, no headaches.

pip install anansi-compute
2

Wrap Your Function

One line change

Your code stays the same. Just wrap it and get cryptographic proof of execution.

import anansi
result = anansi.compute(your_function, data, proof=True)
3

Get Your Proof

Tamper-evident results

Standard cryptographic proof that anyone can verify. No trust required.

{
  "result": your_computed_result,
  "proof": "0x7f8a9b2c3d4e5f6a...",
  "attestation": "verified",
  "timestamp": "2025-01-20T23:33:38Z"
}

For Compliance

Every computation generates a cryptographic proof bundle. Here's what auditors see.

Proof Bundle Structure

Job Identity

Who ran it, what code, which data inputs

Execution Environment

Cloud, region, instance type, timing

Cryptographic Attestation

CPU and GPU hardware verification

Digital Signature

Tamper-evident seal over the entire bundle

Sample Proof Bundle

VERIFIED
{
  "version": "1.0",
  "proof_id": "prf_2025-08-21_7c2a",
  "job": {
    "job_id": "dbx-13482",
    "caller": "analyst@company.com",
    "entrypoint": "s3://bucket/ml-training:sha256:3f8f...e21"
  },
  "route": {
    "cloud": "azure",
    "region": "eastus",
    "instance": "NCCads_H100_v5"
  },
  "timing": {
    "started_at": "2025-08-21T01:03:12Z",
    "ended_at": "2025-08-21T01:07:55Z"
  },
  "attestation": {
    "cpu": {
      "type": "SEV-SNP",
      "verified": true
    },
    "gpu": {
      "type": "NRAS",
      "verified": true
    }
  },
  "signature": {
    "alg": "EdDSA",
    "verified": true
  }
}
Signature verified against public key
CPU attestation validated
GPU attestation validated
Timing and policy constraints met

Want to Try It?

It's going open source soon. If you find bugs or have ideas, let me know. Always looking for feedback from people actually using this stuff.