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.
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
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
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
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.