All comparisons

What happens when AI agents have no accountability?

Without trust scoring, every agent is a black box. No identity, no audit trail, no way to know if an agent is behaving as expected until something goes wrong.

Dimension
With Trust Scoring
Without
Agent Identity
AAIN-registered, cryptographically verifiable
Anonymous — no way to identify or trace
Compliance
Audit-ready evidence generated automatically
None — hope for the best
Authority
Earned over time through demonstrated behavior
Unlimited from day one — no guardrails
Risk Detection
Trust score flags anomalies in real time
Undetected failures until post-mortem
Accountability
Every action logged, attributed, auditable
Black box — no attribution, no trail

The cost of no governance

The average AI-related incident costs $3.6Mto remediate, according to IBM's Cost of a Data Breach Report. When agents operate without identity or scoring, you cannot detect drift, prevent unauthorized actions, or prove compliance to regulators. The question is not if an ungoverned agent will cause harm — it is when.

72%

of enterprises lack any AI agent governance framework

214 days

average time to identify an AI-related breach

What Shulam delivers

100%

of Shulam agent actions are auditable

0

cross-tenant data leaks

7-factor

trust scoring model

<200ms

trust evaluation latency

Why switch to governed agents?

Prove compliance instantly

Regulators ask for evidence. Shulam generates it automatically for every action your agents take.

Catch drift before damage

Trust scores detect behavioral anomalies in real time, not in a post-incident report six months later.

Scale without risk

Go from 10 agents to 50,000. Every one is identified, scored, and accountable from day one.

Start with trust from day one.

Every agent identified. Every action auditable. Every deployment governed.

Start with trust from day one