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Detect when decisions feel right — but aren’t

Affecta forms the conviction layer of the system - detecting when confidence and evidence diverge before action is taken.

Conviction is not visible. Until it fails.

Most systems evaluate what was decided. Affecta evaluates how it felt — and whether that confidence was justified.

It detects when conviction and evidence diverge — surfacing risk before action is taken.
Affecta modulates decisions at the Execution Boundary — ensuring actions are not driven by unstable or misaligned conviction.

From reaction to regulated response

Emotional escalation drives decisions
WHAT HAPPENS

Decisions are shaped by emotional drift rather than intent.

WHAT AFFECTA DOES

Detects shifts in emotional state and flags when decisions deviate from baseline.

Bias operates below awareness
WHAT HAPPENS

Bias shapes decisions without being recognised.

WHAT AFFECTA DOES

Surfaces bias signals before they affect outcomes.

Signals are invisible until outcome failure
WHAT HAPPENS

Warning signals exist — but are ignored or misinterpreted.

WHAT SOCRATES DOES

Surfaces early emotional and behavioural indicators of risk.

Af·fec·ta (from Latin affectus)
The emotional forces shaping perception and judgment.

Af·fec·ta (from Latin affectus)
The emotional forces shaping perception and judgment.

01
Signal
02
Calibration
03
Adjustment

Multimodal input layer

Integrates language, behaviour, and optional biometric inputs to detect shifts in emotional state.
It captures emotional and behavioural signals as structured data — forming a continuous record of how conviction evolves over time.

Secure handling of sensitive data

Designed for sensitive emotional data, with strict privacy controls, auditability, and transparent handling.

Security points:
  • Explicit consent-based signal capture
  • No passive emotional inference without disclosure
  • Role-based access control
  • Encrypted state data
  • Transparent model outputs

Built for healthcare, finance, public sector, and other regulated decision environments.

Measurable conviction signals

Reduction in reactive decisions

Track decline in high-arousal decision clusters.

Increased decision stability

Measure variance in decision volatility over time.

Plugins Integrated

Bias correlation mapping

Surface emotional weighting linked to judgment drift.

/ Ready to model emotional signal at scale? 
/ Ready to model emotional signal at scale?