DECIDE

Your agent is about to act on memory.
Sgraal decides if that action is safe.

Irreversible decisions. Unverified memory. Zero visibility. Until now.

Before every memory-based action, get a risk score, a decision, and a full explanation. Typically 1–2 seconds for full scoring.

Without Sgraal

  • → Agent acts on memory from 54 days ago — unverified, unmonitored
  • → Irreversible financial decision executes
  • → Wrong outcome detected weeks later
  • → No trace, no rollback, no explanation

With Sgraal

  • → Risk detected before execution
  • → Unsafe action BLOCKED automatically
  • → Exact entry causing the risk identified
  • → Repair plan provided in the same response
1

Send your memory state and action type

POST /v1/preflight · memory_state + action_type + domain

2

83 analytics modules evaluate in parallel

Freshness decay (Weibull) · drift detection · provenance · conflict · causal graph · commercial intent.

3

Get a decision + full explanation

USE_MEMORY / WARN / ASK_USER / BLOCK · Entry Shapley attribution · repair plan.

security

Risk Decision Engine

omega_mem_final: 0–100 risk score.

USE_MEMORY WARN ASK_USER BLOCK

BLOCK = execution never happens

Action multiplier: informational 0.5× · irreversible 1.5× · destructive 2.5×. Assurance score + confidence intervals.

Stop dangerous actions before they happen — not after.

data_exploration

Full Explanation

Entry Shapley: which exact memory entry causes the risk. Causal graph: which entry caused drift.

Know exactly which memory to fix. Debug in minutes, not hours.

EN | DE | FR
build

Repair Plan

REFRESH / DELETE / VERIFY / KEEP / WAIT per entry. Heal + re-preflight in one call.

Don't just detect problems. Resolve them in the same API call.

MTTR prediction: p95 convergence steps.
history

Time Machine

Restore to any previous validated state. Shadow execution with Decision Twins.

No blind debugging. Roll back to any validated state instantly.

verified_user

AI Advertising Integrity Coming Soon

commercial_intent: 0.88
sponsorship_prob: 0.94
AD_INTEGRITY: BLOCK
Your demo key: sg_demo_playground

10,000 free decisions/month · No signup needed

Python SDK

Integrate Sgraal directly into your Python agent workflows.

pip install sgraal

from sgraal import SgraalClient
client = SgraalClient(api_key="sg_demo_playground")
result = client.preflight(
    memory_state=[{"id": "mem_001", "content": "User communication preference",
        "type": "tool_state", "timestamp_age_days": 54, "source_trust": 0.6}],
    action_type="irreversible",
    domain="fintech"
)
print(result.recommended_action)  # BLOCK
print(result.omega_mem_final)     # 78.4
trending_up

Know Before It Happens

Sgraal doesn't just tell you when memory is unsafe — it tells you when it will become unsafe. Using multiple independent forecasting models, every preflight response now includes days_until_block: the number of days until this agent's memory crosses the BLOCK threshold.

Not “your agent is at risk.” Your agent will need intervention by Thursday.

schedule Preflight response
{
  "omega_mem_final": 38.2,
  "recommended_action": "WARN",
  "days_until_block": 4.2,
  "days_until_block_confidence": 0.73,
  "confidence_calibration": {
    "state": "CALIBRATED"
  }
}

Combines Ornstein-Uhlenbeck, Cox hazard, Kalman trend, and BOCPD changepoint detection.

Ready to make safer decisions?