xokind ai

Building technology that brings AI advances closer to product teams and end users

Through a combination of cutting-edge approaches including deep learning and graph ML, we make AI more accessible, human-centered, and impactful to real-world use cases.

AI Focus

Domain-specific AI

Bridge the gap between public models and the needs of your domain by ingesting domain-specific or company-specific data to further pre-train models. The resulting models have  more contextual content understanding

Cold-start personalization

Help new customers enjoy the power and convenience of personalized recommendations

Special emphasis on explainability

Make the results of the AI models actionable for your business and for your end users

Technology Focus

Empowering non-ML experts

Pre-built apps that use AutoML, and zero- and few-shot learning with large pre-trained models. Anyone can now build, customize, deploy, scale, monitor and continuously retrain ML models -- technical expertise optional!

End-to-end data and ML pipeline

Connects to unstructured and structured data sources to normalize and synthesize data for ML applications

Powering AI in B2C and B2B products

Scalable stack for NLP, Computer Vision, Personalization & Recommendation, Semantic Search, NL2SQL, Scoring and Forecasting

Engineering Excellence

We care deeply about our craft and leverage modern, scalable technologies including Kubernetes, a Search & Discovery stack, Firebase, React and Flutter.

We iterate quickly in an interdisciplinary manner via product design and agile development processes to prototype and develop new technology.

We thrive with a balance between technology exploration and execution to empower our team to grow and to create. 

Our R&D and engineering is led by Yinyin Liu, CTO & co-founder, who was selected among the top 30 women in AI by Re.Work.


Turn your data into predictive insights in record time