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Custom AI Facial Expression Recognition & Emotion Detection Solutions
We develop custom AI-powered solutions for real-time facial expression recognition and emotion detection. Tailored for healthcare, security, marketing, and other emotion AI use cases.
Why choose KISS Software?
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Engineering expertise in Computer Vision and emotional AIEngineering expertise in Computer Vision and emotional AI
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Custom approach tailored to your business
We adapt models for specific domains: EdTech, marketing, HR, security, UX, and interactive products.
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Security, privacy, and ethics first
We design systems with privacy by design, data protection, anonymization, and compliance with industry standards.
Top 6 use cases for AI emotion recognition
User reaction analysis in UX and games
Detect real-time emotions of players or users to improve interfaces, flows, and engagement scenarios.
Emotional analytics for marketing and advertising
Measure audience reactions to content, videos, and landing pages to better evaluate engagement and impact.
Emotion recognition in learning and EdTech systems
Adaptive learning based on student emotional state: fatigue, boredom, confusion, or interest.
Emotional monitoring in HR and recruitment
Support emotional state analysis of candidates or employees during interviews and assessments.
Security and public space monitoring
Detection of anxiety, aggression, or abnormal emotional patterns integrated with video surveillance systems.
Customer support and user service
Identify frustration or dissatisfaction during interactions with chatbots or support agents.
Need intelligent emotion-driven reactions in your software?
Analyze facial expressions and detect emotional states of customers, employees, or users in real time.
Testimonials
Мы заказывали у KISS Software анимацию для 2D-платформера. Ребята сразу поняли нашу стилистику, предложили интересные решения по эмоциям персонажей, а результат превзошёл ожидания. Игроки отмечают именно «живость» анимации. Будем работать ещё.
Андрей
гейм-дизайнер
Нужно было подключить аутсорс на этапе риггинга и внутриигровых синематиков под Unreal Engine. KISS вошли в проект аккуратно, без долгих вводных, всё отдали в срок, багов — ноль. Отличная техничка, быстрая реакция и понимание продакшн-процесса.
Михаил
продюсер, студия разработки игр
Уже третий проект делаем с командой KISS — всегда всё прозрачно, по делу и вовремя. У них реально хорошее чувство гейм-драмы и движущейся композиции. Отдельно ценим их подход к оптимизации под мобильные платформы.
Денис
CEO
Emotion recognition solution development stages
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Use-case research and requirements analysis
We define goals: UX analytics, security, HR, EdTech, or other scenarios. Determine how images or video streams will be captured. Select emotion metrics (joy, sadness, anger, neutral, etc.). Address privacy, legal constraints, and anonymization. Produce a technical specification tailored to your industry.
Time to deliver
~ 1-2 дня
CV model architecture selection and setup
Choose suitable models (CNN, ResNet, OpenFace, MediaPipe, or custom architectures). Balance accuracy, latency, and resource usage. Design capture pipelines (camera, stream, API). Enable microexpression detection or long-term emotional states. Build preprocessing pipelines.
Time to deliver
~ 2-4 дня
Neural network training and calibration
Use datasets such as FER2013, AffectNet, or collect custom datasets. Train models across varied lighting, angles, and facial expressions. Calibrate using real video from your devices. Improve accuracy in borderline emotions (e.g., anxiety vs surprise). Validate via A/B testing.
Time to deliver
~ 3-7 дней
Integration into UI or backend systems
Integrate via API, WebRTC, native SDKs, or edge servers. Enable real-time or delayed processing. Add visualizations (emotion labels, heatmaps, confidence scales). Configure alerts, logs, and reports. Ensure secure on-premise or cloud deployment.
Time to deliver
~ 5-15 дней
Behavioral adaptation and response logic
Connect emotion outputs to behavioral logic: recommendations, feedback loops, game mechanics, learning paths. Define reaction rules per emotion. Integrate with chatbots, HR platforms, learning systems, or monitoring tools. Support A/B testing and continuous learning.
Time to deliver
~ 2-4 дня
Support, scaling, and maintenance
Maintain and retrain models with new data. Scale across new interfaces, cameras, and devices. Conduct privacy audits and support GDPR / ISO compliance. Provide SLA-based monitoring and long-term support.
Time to deliver
~ 1-2 дня
Technologies and tools we use
Java
Javascript
MySQL
PHP
Java
Javascript
MySQL
PHP
FAQ
Yes. Using WebAssembly, TensorFlow.js, or cloud APIs, it can be embedded directly into web interfaces.
Yes. We optimize models for edge deployment and simplify pipelines without significant accuracy loss.
Up to 90–94% accuracy on six basic emotions, especially when calibrated to your specific scenarios and data.
Want to know how users emotionally react to your product?
Emotional UX analytics helps uncover hidden growth opportunities.
