The center of gravity in AI research is shifting. As large language models have reached remarkable fluency, the field is increasingly recognizing their limits: language alone does not capture how the world works. Intelligence must be grounded in reality, shaped by cause and effect, time, uncertainty, and physical constraints.
Palona builds AI systems that perceive, reason, and act in the real world. Our systems operate continuously in production—integrating perception, memory, decision-making, and action in environments where outcomes matter.
Emotionally Intelligent AI
Our agents don't just process requests—they understand and respond with emotional intelligence. Built on advanced conversational models, they adapt to dynamic conversations, picking up on nuances in tone, context, and customer needs.
Voice cloning captures not only voices, but also accents and dialects.
High EQ interactions know when to upsell, empathize, or escalate.
Multi-language support with seamless language switching.
Contextual awareness that remembers past interactions.
Leading Accuracy and Self-Evolution
Palona has achieved 98%+ order accuracy—best in the industry—through innovative benchmarking and continuous improvement systems. Our AI doesn't just work. It learns, adapts, and gets better over time.
Order simulation continuously tests performance.
Automated benchmarking identifies weaknesses and optimizes responses.
Real-time learning from every customer interaction.
Self-improving algorithms that adapt to customer patterns.
Multimodal Architecture
Palona's platform is built on a sophisticated multi-modal, multi-model architecture that seamlessly integrates voice, text, images, and video to deliver comprehensive AI capabilities.
Unified, seamless voice and text processing.
Visual analyses of restaurant processes and contexts.
Video processing for camera-based applications.
Multimodal memory maintaining context across interaction types.
Palona Real-World AI is our applied research effort to build and study grounded, multimodal intelligence systems in live environments. We treat restaurants as a deliberately chosen slice of the real world: a setting dense with language, audio, timing, interruptions, human behavior, and operational constraints, where actions have immediate and measurable results.
Restaurants are not the end goal—they are the proving ground.
For researchers interested in how AI systems behave when outcomes matter, signals are imperfect, and conditions change, Palona offers a rare opportunity to work on real-world intelligence at scale.
Grounded multimodal learning
Learning representations that integrate language with live signals—audio, system state, temporal context—grounded in real-world interaction rather than static datasets.
World state modeling and persistence
Building structured, evolving representations of environments that persist over time, enabling reasoning about partial observability, uncertainty, and cause-and-effect relationships.
Long-horizon decision-making in live systems
Planning and acting across multiple steps under real-world constraints, interruptions, and non-stationary conditions.
Closed-loop learning from interaction
Incorporating feedback from actions taken in production to continuously update internal models and policies.
Robustness under noise and failure
Designing systems that degrade gracefully in the presence of latency, missing signals, system errors, and human variability.
Evaluation beyond benchmarks
Developing metrics and methodologies that assess intelligence based on reliability, outcomes, and sustained performance in real environments.
Hungry for a New Challenge?
We're building AI systems that operate in the real world, under real constraints, with real impact.
If you're interested in multimodal learning, world models, decision-making under uncertainty, or robust deployment of AI in live systems, we want to talk to you.
