When your regulator asks
about your AI,
you'll have the answer.

# Zero-friction path — no code changes needed
npm install sealvera
export NODE_OPTIONS="--require sealvera/autoload"
export SEALVERA_API_KEY=sv_...
# Done — run your agent as normal

# Or wrap explicitly:
const SealVera = require('sealvera');
const { OpenAI } = require('openai');

SealVera.init({ endpoint: 'https://app.sealvera.com', apiKey: process.env.SEALVERA_API_KEY });
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const agent  = SealVera.createClient(openai, { agent: 'loan-underwriter' });

// Your existing code unchanged — every call is now a signed audit record
const result = await agent.chat.completions.create({ model: 'gpt-4o', messages });

# LangChain — one callback, full compliance trail
from sealvera.callbacks import SealVeraCallbackHandler
from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor

handler = SealVeraCallbackHandler(
    api_key=os.environ["SEALVERA_API_KEY"],
    agent="loan-underwriter"
)

# Works with any LangChain LLM or chain
llm = ChatOpenAI(model="gpt-4o", callbacks=[handler])
agent = AgentExecutor(agent=..., tools=..., callbacks=[handler])

# CrewAI — wrap the LLM the same way
from crewai import Agent, Crew
crew_agent = Agent(role="Underwriter", llm=llm)

# Every chain step, tool call, and decision is a signed compliance record

// Go SDK — explicit wrappers per provider
import sealvera "github.com/sealvera/sealvera-go"

sealvera.Init(sealvera.Config{
    Endpoint: "https://app.sealvera.com",
    APIKey:   os.Getenv("SEALVERA_API_KEY"),
})

agent := sealvera.NewAgent("loan-underwriter")

result, err := agent.WrapOpenAI(ctx, "evaluate_application", input,
    func() (any, error) {
        return openaiClient.Chat.Completions.New(ctx, params)
    },
)

// Anthropic with extended thinking chain capture
const SealVera = require('sealvera');
const Anthropic = require('@anthropic-ai/sdk');

SealVera.init({ endpoint: 'https://app.sealvera.com', apiKey: process.env.SEALVERA_API_KEY });

const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
const agent = SealVera.createClient(anthropic, { agent: 'my-claude-agent' });

// Extended thinking chains are captured as native evidence automatically
const result = await agent.messages.create({
  model: 'claude-3-7-sonnet-20250219',
  max_tokens: 16000,
  thinking: { type: 'enabled', budget_tokens: 10000 },
  messages: [{ role: 'user', content: '...' }]
});

# No SDK required — works with any language or framework
# Point your existing OTel exporter at SealVera:

OTEL_EXPORTER_OTLP_ENDPOINT=https://app.sealvera.com/api/otel
OTEL_EXPORTER_OTLP_HEADERS="X-SealVera-Key=sv_..."

# Add these attributes to your AI decision spans:
#   ai.agent      = "my-agent-name"
#   ai.action     = "evaluate"
#   ai.decision   = "APPROVED"
#   ai.model      = "gpt-4o"
#   ai.input      = '{"amount": 25000}'
#   ai.output     = '{"decision": "APPROVED", "confidence": 0.94}'

# If you already run OTel, this is a single config change.

# Install the SealVera skill
clawhub install sealvera

# Set your API key — logging starts immediately
export SEALVERA_API_KEY=sv_...
export SEALVERA_AGENT=my-agent-name

# Every LLM call your OpenClaw agent makes is now audited
# No other changes needed