Build Trusted AI.

from sakshi import SakshiClient

sakshi = SakshiClient(url, api_key=key)
agent_id = sakshi.register(
    "loan-decision-agent",
    owner_name="R. Sharma",
    owner_email="[email protected]")

# every decision, witnessed
with sakshi.witness(agent_id) as rec:
    rec.step("assess", score=0.81)
    rec.action(outcome="approved")

from sakshi.middleware import (
    watch_openai_compatible)

# OpenAI-compatible, Anthropic,
# Gemini, Bedrock — incl. local
# Ollama / vLLM stacks
client = watch_openai_compatible(
    openai_client)

# model identity + version land
# on the record automatically
resp = client.chat.completions
    .create(model="...", ...)

# route an action through its
# autonomy envelope
curl -X POST \
  $SAKSHI/api/v1/bound/evaluate \
  -H "Authorization: Bearer $KEY" \
  -d '{
    "agent_id": "...",
    "signals": {
      "action": "approve_loan",
      "stakes": 0.7
    }
  }'