Quickstart - AgentSystems

1. Set Up Your S3 Bucket

The SDK writes raw logs directly to your S3 bucket — you maintain full control.

Create an S3 bucket (names are globally unique, so include your company name — e.g., acme-corp-raw-ai-logs)

Create the following IAM policy:

{
  "Version": "2012-10-17",
  "Statement": [{
    "Effect": "Allow",
    "Action": ["s3:PutObject", "s3:GetObject", "s3:ListBucket"],
    "Resource": [
      "arn:aws:s3:::acme-corp-raw-ai-logs",
      "arn:aws:s3:::acme-corp-raw-ai-logs/*"
    ]
  }]
}

Create an IAM user and attach the policy
Generate access keys for the user (select “Application running outside AWS”) and save them

2. Install the SDK

LangChain
CrewAI

mkdir notary-demo && cd notary-demo
python3 -m venv .venv
source .venv/bin/activate
pip install agentsystems-notary langchain-anthropic python-dotenv

mkdir notary-demo && cd notary-demo
python3 -m venv .venv
source .venv/bin/activate
pip install agentsystems-notary crewai python-dotenv

3. Configure Environment

Create a .env file:

# AWS credentials for your S3 bucket
ORG_AWS_S3_BUCKET_NAME=acme-corp-raw-ai-logs
ORG_AWS_S3_ACCESS_KEY_ID=...
ORG_AWS_S3_SECRET_ACCESS_KEY=...
ORG_AWS_S3_REGION=us-east-1

# Arweave hash storage
ARWEAVE_BUNDLER_URL=https://node2.bundlr.network
ARWEAVE_PRIVATE_KEY_PATH=path/to/rsa-4096-private.pem

# Your LLM provider
ANTHROPIC_API_KEY=...

4. Integrate the SDK

LangChain
CrewAI

Create test_langchain.py:

import os
from dotenv import load_dotenv
from agentsystems_notary import (
    LangChainNotary,
    RawPayloadStorage,
    ArweaveHashStorage,
    LocalKeySignerConfig,
    AwsS3StorageConfig,
)
from langchain_anthropic import ChatAnthropic

load_dotenv()

# Where full audit payloads are stored (your S3 bucket)
raw_payload_storage = RawPayloadStorage(
    storage=AwsS3StorageConfig(
        bucket_name=os.environ["ORG_AWS_S3_BUCKET_NAME"],
        aws_access_key_id=os.environ["ORG_AWS_S3_ACCESS_KEY_ID"],
        aws_secret_access_key=os.environ["ORG_AWS_S3_SECRET_ACCESS_KEY"],
        aws_region=os.environ["ORG_AWS_S3_REGION"],
    ),
)

# Where hashes are stored — Arweave for independent verification
hash_storage = [
    ArweaveHashStorage(
        namespace="my_namespace",
        signer=LocalKeySignerConfig(
            private_key_path=os.environ["ARWEAVE_PRIVATE_KEY_PATH"],
        ),
        bundler_url=os.environ["ARWEAVE_BUNDLER_URL"],
    ),
]

# Initialize notary
notary = LangChainNotary(
    raw_payload_storage=raw_payload_storage,
    hash_storage=hash_storage,
    debug=True,
)

# Add to any LangChain model
model = ChatAnthropic(
    model="claude-sonnet-4-5-20250929",
    api_key=os.environ["ANTHROPIC_API_KEY"],
    callbacks=[notary],
)

# All LLM calls are now logged
response = model.invoke("What is 2 + 2?")
print(response.content)

Run it:

python test_langchain.py

Create test_crewai.py:

import os
from dotenv import load_dotenv
from agentsystems_notary import (
    CrewAINotary,
    RawPayloadStorage,
    ArweaveHashStorage,
    LocalKeySignerConfig,
    AwsS3StorageConfig,
)
from crewai import Agent, Task, Crew, LLM

load_dotenv()

# Where full audit payloads are stored (your S3 bucket)
raw_payload_storage = RawPayloadStorage(
    storage=AwsS3StorageConfig(
        bucket_name=os.environ["ORG_AWS_S3_BUCKET_NAME"],
        aws_access_key_id=os.environ["ORG_AWS_S3_ACCESS_KEY_ID"],
        aws_secret_access_key=os.environ["ORG_AWS_S3_SECRET_ACCESS_KEY"],
        aws_region=os.environ["ORG_AWS_S3_REGION"],
    ),
)

# Where hashes are stored — Arweave for independent verification
hash_storage = [
    ArweaveHashStorage(
        namespace="my_namespace",
        signer=LocalKeySignerConfig(
            private_key_path=os.environ["ARWEAVE_PRIVATE_KEY_PATH"],
        ),
        bundler_url=os.environ["ARWEAVE_BUNDLER_URL"],
    ),
]

# Initialize notary (hooks register automatically)
notary = CrewAINotary(
    raw_payload_storage=raw_payload_storage,
    hash_storage=hash_storage,
    debug=True,
)

# Create LLM
llm = LLM(
    model="anthropic/claude-sonnet-4-5-20250929",
    api_key=os.environ["ANTHROPIC_API_KEY"],
)

# Create agent and task
agent = Agent(
    role="Research Analyst",
    goal="Answer questions accurately",
    backstory="You are an expert analyst.",
    llm=llm,
)
task = Task(
    description="What is 2 + 2?",
    expected_output="The answer to the math question",
    agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])

# All LLM calls are now logged
result = crew.kickoff()
print(result)

Run it:

python test_crewai.py

With debug=True, you’ll see confirmation that the log was written to S3 and the hash was uploaded to Arweave.

5. Verify

Anyone can verify your logs using the open-source CLI — no account required:

npm install -g agentsystems-verify

agentsystems-verify \
  --namespace my_namespace \
  --start 2026-01-01 \
  --end 2026-01-31 \
  --logs logs.zip

See Independent Verification for full CLI documentation.

Signer Options

The examples above use a local RSA-4096 private key. You can also use managed key services:

LocalKeySignerConfig — Local RSA-4096 private key (PEM file or env var)
AwsKmsSignerConfig — AWS KMS managed key
GcpKmsSignerConfig — GCP Cloud KMS managed key
AzureKeyVaultSignerConfig — Azure Key Vault managed key

Using Custodied Storage (Optional)

If you prefer AgentSystems to manage hash storage, you can use our custodied option instead of (or in addition to) Arweave.

Create Account

Go to notary.agentsystems.ai and sign up.

Generate an API Key

From the Dashboard, click Add under API Keys
Name your key and select environment
Copy and save the key — it’s only shown once

Add to Environment

AGENTSYSTEMS_NOTARY_API_KEY=sk_asn_test_...

Add Custodied Hash Storage

from agentsystems_notary import CustodiedHashStorage

hash_storage = [
    ArweaveHashStorage(...),  # Keep Arweave for independent verification
    CustodiedHashStorage(
        api_key=os.environ["AGENTSYSTEMS_NOTARY_API_KEY"],
        slug="customer-123",
    ),
]

Verify via Portal

Go to notary.agentsystems.ai → Tenants → Generate Verification Ticket
Export logs from your S3 bucket
Upload both to verify.agentsystems.ai

See Verification Guide for full portal documentation.

​1. Set Up Your S3 Bucket

​2. Install the SDK

​3. Configure Environment

​4. Integrate the SDK

​5. Verify

​Signer Options

​Using Custodied Storage (Optional)

​Create Account

​Generate an API Key

​Add to Environment

​Add Custodied Hash Storage

​Verify via Portal