SealVera Python SDK

Tamper-evident audit trails for AI agents — compliance-ready in minutes.

SealVera gives every AI decision a cryptographically-sealed, immutable audit log — so you can prove what your agent decided, why it decided it, and that the record hasn't been touched. Built for teams shipping AI in finance, healthcare, legal, and any regulated industry that needs to answer to auditors, regulators, or customers.

EU AI Act · SOC 2 · HIPAA · GDPR · ISO 42001 — SealVera logs are designed to satisfy the explainability and auditability requirements of major AI compliance frameworks.

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Why SealVera?

• Tamper-evident logs — every decision is cryptographically hashed and chained; any tampering is detectable
• 2-line integration — works as a decorator, callback, or context manager
• Explainability built-in — captures inputs, outputs, reasoning, confidence scores, and model used
• Real-time dashboard — search, filter, and export your full AI decision history at app.sealvera.com
• Drift detection — get alerted when agent behaviour deviates from its baseline
• Works with any LLM — OpenAI, Anthropic Claude, Google Gemini, Ollama, LangChain, CrewAI, AutoGen, and more
• Zero hard dependencies — stdlib only, no bloat, no vendor lock-in

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Installation

pip install sealvera

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Quick Start

from sealvera import init, log

# Initialize once (e.g. in your app entry point)
init(
 endpoint="https://app.sealvera.com",
 api_key="sv_your_api_key_here",
 agent="payment-agent"
)

# Log a decision
log(
 action="approve_payment",
 decision="APPROVED",
 input={"amount": 5000, "currency": "USD", "customer_id": "c_123"},
 output={"approved": True, "reason": "Low risk score, verified merchant"},
 reasoning=[
 {"factor": "risk_score", "value": "0.12", "signal": "safe", "explanation": "Below 0.3 threshold"},
 {"factor": "merchant", "value": "verified", "signal": "safe", "explanation": "KYC passed"}
 ]
)
# Decision logged, hashed, and stored in your tamper-evident audit trail

Get your API key at app.sealvera.com.

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LangChain Integration

The easiest way to audit LangChain agents — drop in the callback handler:

from sealvera import init
from sealvera.callbacks import SealVeraCallbackHandler
from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage

init(endpoint="https://app.sealvera.com", api_key="sv_your_key", agent="langchain-agent")

model = ChatOpenAI(
 model="gpt-4o",
 callbacks=[SealVeraCallbackHandler(agent="langchain-agent")]
)

response = model.invoke([HumanMessage(content="Should I approve this loan application?")])
# Full chain logged — every LLM call, tool invocation, and final answer

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Decorator Usage

Wrap any agent function with a single decorator:

from sealvera import init, trace

init(endpoint="https://app.sealvera.com", api_key="sv_your_key")

@trace(agent="fraud-detector", action="evaluate_transaction")
def evaluate_transaction(transaction: dict) -> dict:
 # Your agent logic here — LLM call, rules engine, ML model, anything
 risk_score = run_fraud_model(transaction)
 decision = "FLAGGED" if risk_score > 0.8 else "APPROVED"
 return {"decision": decision, "risk_score": risk_score, "reason": "..."}

result = evaluate_transaction({"amount": 9800, "merchant": "Unknown Corp"})
# Input, output, decision, and timing logged automatically

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Context Manager

from sealvera import init, SealVeraClient

init(endpoint="https://app.sealvera.com", api_key="sv_your_key")
client = SealVeraClient()

with client.trace(agent="underwriting-agent", action="evaluate_loan") as ctx:
 ctx.set_input(application)
 result = run_underwriting_model(application)
 ctx.set_output(result)
 ctx.set_decision(result["decision"])
# Logged on context exit, even if an exception occurs

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Autoload (Zero-Code Integration)

Add SealVera to any Python app without modifying source code:

python -m sealvera.autoload your_app.py

Or set via environment variables and import at the top of your entry point:

import sealvera.autoload # patches LLM clients automatically

SEALVERA_ENDPOINT=https://app.sealvera.com
SEALVERA_API_KEY=sv_your_key_here
SEALVERA_AGENT=my-agent

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Async Support

Full async/await support for FastAPI, async LangChain, and any async agent framework:

from sealvera import init, log_async

init(endpoint="https://app.sealvera.com", api_key="sv_your_key")

async def process_claim(claim: dict) -> dict:
 result = await run_claims_model(claim)
 await log_async(
 action="evaluate_claim",
 decision=result["decision"],
 input=claim,
 output=result,
 reasoning=result.get("reasoning", [])
 )
 return result

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Decision Vocabulary

Decision	Meaning	Use for
APPROVED	Request approved / allowed	Payments, loans, access grants
REJECTED	Request blocked / denied	Fraud blocks, denials
FLAGGED	Needs human review	Borderline cases, escalations
COMPLETED	Task finished successfully	General agent tasks
FAILED	Task failed	Error paths
ESCALATED	Handed to human/higher agent	Human-in-the-loop
PASSED	Test/check passed	CI, health checks

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Use Cases

• Financial services & fintech — log every credit decision, fraud flag, and payment approval for regulatory review (FINRA, OCC, CFPB)
• Healthcare AI — tamper-evident audit trail for clinical decision support (HIPAA-aligned)
• Legal tech — record document review, contract analysis, and compliance risk assessments
• Insurance — log claims triage, underwriting decisions, and anomaly flags
• HR / hiring tools — demonstrate fair, explainable AI decisions to avoid bias liability
• Any agentic AI system — multi-step reasoning chains, tool calls, and autonomous decisions

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Environment Variables

Variable	Description	Default
SEALVERA_ENDPOINT	SealVera server URL	https://app.sealvera.com
SEALVERA_API_KEY	Your API key (starts with sv_)	—
SEALVERA_AGENT	Default agent name	default
SEALVERA_DEBUG	Enable debug logging	false

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JavaScript / Node.js SDK

Looking for the Node.js version? → npmjs.com/package/sealvera

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Links

• Dashboard & signup — app.sealvera.com
• Full documentation — app.sealvera.com/docs
• Node.js SDK — npmjs.com/package/sealvera
• Support — hello@sealvera.com

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License

MIT