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Become Agent Ready for Modern Marketing without losing control

AI accelerates decisions.

Without governance, it amplifies error.

Agent readiness comes before automation.

Agent Readiness

Signal hygieneDecision ownershipMeasurement logicReward designControlled automationSignal hygiene
Explore the readiness diagnostic
FIRST STEP

Marketing Operating Model Review

A 2–3 week, decision-focused review to assess readiness, identify risk, and define where automation should and should not be applied

Not a tool audit • No implementation • No media execution

Why modern marketing breaks under AI

They optimise for fragmented proxies, not for commercial outcomes.

AI accelerates decisions
Weak signals distort them
The system amplifies the error

Signal and decision infrastructure.

KaiSignals doesn't sell tactics. We build operating models and decision infrastructures that enable your teams to make automation safe.

Automation only works when decision logic is explicit.
Signals must be owned, bounded, and reconciled.
Escalation paths must exist before agents act.

Agent Readiness Stack

Four layers that make agents governed, measurable, and reversible.

Signal & Ownership

Telemetry, tagging, definitions with clear owners and drift checks.

Measurement & Reconciliation

Triangulated measurement, thresholds, and rituals that resolve disagreements.

Decision & Control Layer

Rituals, playbooks, and escalation logic that bound decisions and keep humans in control.

Agentic Deployment

Reward functions, safeguards, and rollback plans so agents act safely on trusted signals.

Readiness starts with brilliant basics
USE CASES

Where teams use KaiSignals

High-level entry points. Flexible execution. No lock-in.

Measurement & Decision Diagnostics

Diagnose where signals, models, and incentives distort decisions.

Focus on commercial truth, not reporting accuracy.

Digital Media Planning Under Uncertainty

Reframe planning around marginal returns, pressure, and risk.

Portfolio thinking replaces budget silos.

Unified Measurement Architecture

Align MMM, experimentation, incrementality, and platform signals into one decision loop.

Measurement as an operating system, not a reporting layer.

Signal & Data Integrity Audits

Identify where weak, lagged, or proxy signals are driving AI systems off course.

Fix signal hygiene before automation scales error.

Experimentation as a Learning System

Move from test-and-learn theatre to structured exploration.

Surface uncertainty instead of hiding it.

Agent OS Integration (Optional)

Select teams may pilot agents for planning, experiment design, or signal synthesis

only once readiness is established.

ENGAGEMENT MODES

How we engage

Strategic Advisory

  • Board-level decision diagnostics
  • Measurement, planning, and signal strategy
  • Redesigning how decisions get made under uncertainty

Agent Readiness

  • Readiness diagnostics across signal, measurement, and control
  • Governance before automation
  • Clear ownership and escalation paths

Agent OS

  • Optional, post-readiness
  • Agents for planning, experimentation, synthesis
  • Human-in-the-loop by design
INSIGHTS

Signal and decision infrastructure

Field observations on readiness, governance, and the signal systems that make automations safe and decisions commercially safe.

Book an Agent Readiness Diagnostic

Review to score readiness, map risks, and prioritise pilots.