AnnaO
Shield.
The same behavioral core that understands a human can, in the wrong hands, manufacture one at scale. AnnaO Shield is the sovereign response to this emerging threat — a detection and neutralization system supervised by humans, never autonomous.
Synthetic humans: the coming threat, and the shield.
The behavioral core powering Stern Tech products is a strategic capability — dual-use by nature. It can help understand a human. It could also be used to simulate one.
Generate synthetic humans
After dozens of hours of interaction, a behavioral profile — or a persona built entirely from scratch — can behave credibly like a human.
In the wrong hands, a weapon
A hostile actor could deploy such agents at scale to impersonate digital identities, overwhelm verification systems, or destabilize coordinated economic or information flows.
AnnaO is the shield
It identifies hostile synthetic actors, traces them to their source, and enables their neutralization — sovereign, defensive, and human-supervised at every stage.
Simulating behavior is a capability.
Detecting its weaponization is a responsibility.
From signal to protective field.
AnnaO Shield applies the same cognitive architecture as the rest of the AnnaO platform — signal, context, modeling, supervised decision — to one precise objective: characterize artificial behavior before it becomes an operational threat.
Multi-source observation
Continuous monitoring of network dynamics without disrupting normal system operation.
Behavioral characterization
Identification of patterns specific to artificial actors: abnormal regularity, coordination, and absence of human variability.
Supervised decision
Hypotheses, confidence levels, and alternative scenarios are returned to an authorized analyst, who remains the sole final decision-maker.
Protection as a phenomenon, not an icon.
Ten stages, from a calm network to delivery to a human operator — with AnnaO never initiating any action autonomously.
Continuous observation
A network of ordinary exchanges is continuously monitored without altering normal operation.
Establishing a baseline
AnnaO learns the natural variability of expected human behavior in this environment.
A deviation forms
One or more nodes diverge from the baseline: excessive regularity, lack of variability, or responses that are too consistent.
Multiple nodes converge
Matching signals across several network points are correlated to assess possible coordination.
Propagation intensifies
The pace and reach of the suspected coordination are measured continuously.
AnnaO characterizes the deviation
The system documents the nature of the anomaly and its associated confidence level.
The protective field adapts
Predefined containment rules are applied to the affected areas of the network.
Suspicious trajectories are isolated
Identified nodes are set apart without interrupting the rest of the system.
Propagation is contained
The anomaly stops expanding under continuous supervision.
Delivery to the operator
Hypotheses, confidence levels, and alternative scenarios are presented to an authorized analyst, who validates the next step.
A governed technology, end to end.
After the intensity of the shield, one principle remains constant: human supervision, traceability, and documented limits for every module.
Human supervision
No autonomous decisions; validation by an authorized professional at every sensitive stage.
Controlled deployment
Parameters, hypotheses, and permitted use cases are defined before any operational deployment.
Governance
An autonomous moral governor oversees AnnaO’s supervised self-development.
Traceability
Every analysis is logged and can be documented for later review.
Data protection
Architecture designed for auditability and aligned with GDPR and the EU AI Act.
Technological sovereignty
A French behavioral core, with computation that can run on client devices.
One core. Three expressions.
The same behavioral core can reveal the coherence of a statement, simulate human behavior, or protect critical systems. Choose a technology to explore one of these three expressions in practice.
Alètheia
The behavioral coherence revealer — statement analysis designed to support human assessment.
Advanced analysis of behavioral coherence.
Alètheia is a behavioral intelligence solution designed to illuminate sensitive situations, assess the coherence of a statement, and reveal weak signals linked to sincerity, concealment, or performance pressure. Its analysis is grounded in more than 70 theories and models from psychology, cognitive science, and the study of human behavior.
Using standard video, Alètheia cross-analyzes vocal, facial, ocular, narrative, and semantic dimensions to produce a structured, documented assessment usable by authorized professionals.
A French, sovereign analysis-support technology designed to strengthen human expertise where information reliability is essential.
Better understand what lies behind a statement.
Speech can be fluent, convincing, and structured while still containing areas of tension or inconsistency. Alètheia helps identify these weak signals without automating the final decision.
Multimodal assessment
The solution analyzes coherence across voice, face, gaze, speech rhythm, micro-signals, and narrative structure.
Sensor-free use
Analysis is performed using a standard camera and microphone, with no intrusive physical device.
Assessment support
Alètheia produces indicators, critical points, and verification leads designed to support human analysis.
behavioral data points analyzed per second.
live, uploaded video, or avatar-assisted interview.
sequence-by-sequence reading of stable and fragile areas.
web-native solution with no physical contact with the person being analyzed.
A method designed for sensitive contexts
Alètheia turns video into structured behavioral analysis by accounting for context, verbal content, non-verbal signals, and the overall coherence of the statement.
Frame
The analysis begins with the general context, detailed context, and information relevant to interpretation.
Capture
The solution uses live or uploaded video from a smartphone or computer, with no specialized hardware.
Observe
Alètheia extracts vocal, facial, ocular, narrative, semantic, and psychophysiological signals accessible through video.
Compare
Channels are cross-referenced to identify alignment, breaks, compensation, and behavioral tension.
Structure
Results are organized into critical points, coherence zones, warning signals, and elements useful for human verification.
Supervise
Alètheia supports professional analysis. The final decision remains human, contextualized, and accountable.
A technology for revealing, not condemning.
Alètheia does not declare a person guilty or innocent. It highlights indicators of coherence, tension, possible concealment, or narrative fragility to help professionals direct their analysis more effectively.
Video analyses and demonstration cases
The demonstrations below illustrate the depth of Alètheia’s analysis. Videos begin with the analysis, followed by interpretation of the results.
Example 01 — coherent statement
In this example, the statement shows strong coherence across the observed channels. Mild presentation tension is present, but the signals remain broadly aligned with the verbal content.
Example 02 — fragile credibility
In this example, the statement may sound credible. The analysis nevertheless reveals control effort, reduced blinking, slower delivery, and narrative fragility.
Case // Jonathann Daval: apparent behavioral concealment
The analysis reveals marked incongruence between verbal discourse and several non-verbal signals.
Observed points
A micro-expression of anger appears in a verbal context dominated by emotional or positive elements.
The slow, irregular pace combined with long pauses indicates high cognitive load.
The system identifies divergences between observable emotional expression and declared content.
Case // Michel Pialle: emotional tension and narrative reconstruction
The analysis shows genuine emotional distress combined with cognitive load and signals of narrative reconstruction.
Observed points
Micro-expressions of sadness appear in passages related to the reported disappearance.
A fast, irregular delivery may reflect an effort to persuade or structure the account.
Some segments show tension between the statements and observed expressions.
Video // Christophe Stern: coherent, controlled presentation
The observed profile is broadly coherent, with moderate tension related to presenting a technical subject.
Observed points
Cognitive load increases during technical or forward-looking passages.
Fatigue signals do not significantly alter the presentation’s overall coherence.
Most observed channels remain aligned with the verbal content.
Case // Chris Watts: compartmentalization and possible concealment
The analysis identifies high cognitive load, emotional distress, and signals consistent with intense emotional control.
Observed points
Micro-expressions of sadness appear during emotionally sensitive passages.
The fast, irregular delivery suggests cognitive tension or an effort to control the narrative.
Stable gaze and reduced blinking indicate significant emotional concentration.
Case // Stuart Hazell: narrative effort and incongruence
The analysis reveals significant divergence between verbal content, vocal signals, and certain non-verbal behaviors.
Observed points
Micro-expressions of sadness appear during emotionally charged appeals.
The fast, irregular rhythm reflects high cognitive load.
The system highlights indicators of a defensive posture and low narrative specificity.
Case // Ryan Ferguson: sincerity and underlying frustration
The observed profile shows general coherence, with stress and frustration signals linked to the context.
Observed points
A micro-expression of anger is consistent with the frustration expressed in the speech.
A fast delivery may correspond to anxiety or extensive preparation.
A controlled appearance coexists with significant physiological tension.
Video // Unknown executive: sincerity with performance pressure
The subject communicates in a controlled, explanatory manner, with signs of performance-related tension.
Observed points
Some micro-expressions may reflect deliberate control rather than concealment.
The fast delivery reflects an effort to maintain pace and structure.
High narrative coherence supports the hypothesis of a prepared presentation.
Video // Kim Kardashian: humorous performance and contextual incongruence
The analysis highlights a controlled performance, with incongruence consistent with a prepared comedic context.
Observed points
Negative micro-expressions must be interpreted within the context of a roast-style monologue.
High cognitive load is consistent with the demands of a public performance.
Fluent speech and the absence of hesitation do not support a fabrication pattern.
Video // Christophe Stern in English: sincerity with linguistic effort
The observed profile indicates a high level of sincerity and engagement in presenting Stern Tech’s innovations.
Observed points
Cognitive load is likely linked to subject complexity and speaking in a non-native language.
Some incongruence scores are contradicted by the overall alignment of verbal and non-verbal channels.
The observed pattern is more consistent with preparation effort than concealment.
An analysis-support technology for sensitive decisions.
Alètheia helps assess the coherence of a statement, identify areas of fragility, and provide professionals with a structured basis for deeper analysis, verification, or contextualization.
Usage notice
Alètheia provides behavioral analysis and decision-support capabilities in sensitive contexts, including assessment, verification, security, and demonstration.
The solution makes no autonomous decisions and does not replace human judgment, the competent authority, or legal or operational responsibility.
The results are analysis-support indicators to be interpreted within a documented, contextualized, and supervised professional framework.
The demonstrations presented on this page use public video content or material supplied for illustrative purposes. They must be understood as demonstrations of analytical capabilities, not as definitive factual conclusions.
Stern Tech acts as a technology provider. Clients and deployers remain responsible for the use framework, informing affected persons, data processing, and decisions made.
Synthetic users
Simulated populations for exploring possible behavior in response to a system, message, or procedure.
Explore possible populations before acting in the real world.
Distinct, contextualized, governed profiles for testing a message, protocol, or interface — without confusing simulation with field evidence.
Synthetic users are simulated profiles — never presented as perfectly reconstructed humans — that make it possible to explore plausible reactions to an interface, message, procedure, or autonomous system in a controlled and documented environment.
Each population is built from the same behavioral core as AnnaO: it inherits its psychological modeling but remains bounded to simulation use — never deployed as an actor in the real world.
Define the population
Context, objectives, constraints, knowledge, preferences, biases, and history for each simulated profile.
Inject the environment
Channel, timing, social context, prior events, other agents, and operational constraints.
Simulate the interaction
The synthetic population is exposed to the interface, message, or procedure under study.
Compare and refine
Differences from field observations are measured, then the population is refined under supervision.
Populations, not an average profile
- Context
- Objectives
- Constraints
- Knowledge
- Preferences
- Biases
- History
- Risk sensitivity
An environment that influences behavior
- Information received
- Channel
- Timing
- Social context
- Prior events
- Other agents
- Operational constraints
Test blind spots
Expose a journey to atypical, contradictory, or constrained profiles to identify failures before they become costly.
Stress-test a protocol
Simulate the response of coordinated groups, fake users, or adversarial agents without deploying them in a real environment.
Compare variants
Measure the effect of a message, interface, or procedure across several populations rather than against an average profile.
Synthetic users are simulation tools intended to test journeys, explore hypotheses, prepare scenarios, and improve systems before they are exposed to real people. They must not be presented as existing individuals or used to impersonate an identity, deceive a third party, bypass a control, manipulate a decision, or automate an action with legal, financial, medical, social, or operational effects.
Generated profiles, behaviors, and results remain probabilistic and depend on the data, parameters, hypotheses, and constraints defined by the deployer. They are neither evidence nor a certain prediction, and they do not replace research with real users when such research is necessary.
Every deployment must include an explicit purpose, a documented scope, access controls, logging, human supervision, and withdrawal or shutdown mechanisms. The deployer remains responsible for compliance, informing relevant parties, data protection, and decisions made from the simulations.
AnnaO.Sapiens
The platform that operates the 325 builder, regulator, and behavioral agents behind every universe.
A behavioral core that builds, regulates, and evolves its modules.
AnnaO.Sapiens orchestrates PACC, its specialized agents, and its cognitive layers within a sovereign, traceable, supervised architecture.
Discover AnnaOAnnaO.Sapiens is Stern Tech Intelligence: the broader sovereign orchestration layer coordinating PACC, the Cyber-Cognitive Analysis Platform, and its 325 builder, regulator, and behavioral agents. The public-facing AnnaO experience is one accessible expression of this wider architecture. Alètheia, Synthetic Users, and AnnaO Shield are specialized technologies within the same supervised platform, governed by explicit safeguards as it evolves.
builder, regulator, and behavioral agents organized into 10 super-agents.
multimodal signal, neuroscience modules, deep psychological modeling.
lower cost: on-device inference via Mixtral, with servers used only when needed.
AnnaO’s self-development overseen by an autonomous moral governor.
Multimodal Signal
Captures voice, face, gaze, gestures, and biometrics without physical sensors.
Psychological Profiling
Models traits, motivations, and behavioral patterns.
Mental Health
Identifies signals of distress and psychological vulnerability.
Alètheia
Analyzes statement coherence and apparent sincerity.
Synthetic Interview
Conducts avatar-assisted behavioral interviews.
Sensory Pegasus
Measures fatigue, attention, and reaction time in simulated environments.
Vectorized World
Runs inference on client devices — sovereign and resource-efficient.
Conversational
Orchestrates natural dialogue between AnnaO and the person.
Synthetic Tester
Simulates user populations to explore a system before deployment.
Self-development
Evolves AnnaO itself under the supervision of the moral governor.
Sovereign by design
- On-device compute
- Open-source core
- GDPR & EU AI Act
- French and auditable
Data flywheel & governance
- Every product trains AnnaO
- Supervised self-development
- Autonomous moral governor
- End-to-end traceability
A behavioral software factory
Each vertical need becomes a reusable module governed by the same architecture and enriched by prior learning.
Radically lean infrastructure economics
Inference on client devices reduces server dependency, improves sovereignty, and concentrates capital on go-to-market.
Every product strengthens the core
Real-world usage, under control and supervision, powers an improvement cycle that benefits every AnnaO module.
AnnaO.Sapiens orchestrates modules for analysis support, software construction, and supervised evolution. Proposals, configurations, applications, or modifications produced by the platform must remain bounded by explicit rules, tested in a controlled environment, documented, logged, and validated by an authorized person before production deployment or any real-world action.
The platform is not an autonomous authority and does not replace business decisions or scientific, medical, legal, regulatory, or cybersecurity expertise. Confidence levels, hypotheses, sources, known limitations, and alternative scenarios must be presented to operators in an understandable form.
The deployer remains responsible for governance, access rights, security, GDPR and EU AI Act compliance, data quality, performance monitoring, and system shutdown in the event of unexpected behavior. Any self-development capability remains subject to the moral governor, technical safeguards, and final human validation.
AnnaO Shield · Stern Tech
Understand what is emerging.
Before it becomes visible.
The behavioral layer
of sovereign AI.
Affective × Cognitive. Governed. Sovereign. Human-supervised. One core to understand, simulate, and protect — with no autonomous decisions.
AnnaO Shield provides analysis-support indicators in sensitive detection, security, and system-protection contexts. The solution makes no autonomous decisions, does not definitively characterize a person or organization, and does not replace human judgment, the competent authority, or an investigation, oversight, or incident-response procedure.
Alerts, confidence levels, and hypotheses must be interpreted in context, cross-checked against other information, and submitted to an authorized operator. Parameters, sources, limitations, thresholds, containment rules, data processing, and possible actions must remain documented, auditable, and proportionate to the intended purpose.
The deployer remains responsible for the legal basis, governance, security, and informing affected persons where required, as well as for any decision or measure taken from the results. Offensive, coercive, or indiscriminate surveillance use is prohibited.
