Teach Video
to Feel.
The missing layer for Generative Video and World Models. We provide the frame-by-frame emotional ground truth to align video AI with human intent.
Video needs a Value Function.
Sora and Runway have mastered physics, but they lack the biological feedback loops that drive efficient learning. TargetLens provides the Emotional Data Layer that turns generative video into sentient storytelling.
The Video Intelligence Stack.
Hybrid Video Engine
Agent + Human-in-the-Loop. Automated visual agents handle frame-by-frame tracking, while psychology-trained reviewers annotate for intent and subtext.
- Temporal Consistency
- Expert Human Verification
GenAI Benchmarking
Video Model Evaluation. Test your model's outputs against our "Golden Set" of human emotional responses. Ensure your avatars and characters behave authentically.
- Safety & Bias Scores
- Affective Congruency
RL Reward Models
Training Environments. We convert video clips into reward functions for Reinforcement Learning. Train video agents that not only act but feel the consequences.
- Reward Function Modeling
- Gymnasium Compatibility
const videoStream = await targetLens.analyze({
source: 's3://generation_batch_04.mp4',
models: ['affective_v2', 'intent']
});
// Stream Output
{
"frame": 1042,
"primary_affect": "contemplation",
"intensity": 0.94,
"facs_units": [
{ "au": 4, "name": "brow_lowerer" }
],
"valence": -0.2,
"video_consistency_score": 0.99
}
Structured Video Data.
Integrate psychological depth into your video training pipeline with a single API call.
- Annotated by psychology-trained reviewers
- Multimodal verification (Audio + Visual)