Artera
Artera strengthens how healthcare providers communicate and care for patients. We bring together text, email, phone, and voice AI agents in one platform built for healthcare. Our voice AI agents handle the routine conversations that consume staff time: appointment scheduling, patient intake, referral management, payments, and care gap outreach. Artera pairs its secure agentic platform, Artera Harmony, with dedicated AI Service Squads who work within each practice's workflows to design and build custom AI solutions around their needs. Trusted by 1,000+ specialty practices, FQHCs, health systems, and federal agencies with 11+ years of healthcare-native experience.
SOC 2 Type 2, HITRUST, HIPAA compliant, and FedRAMP Class D Certified. Patient data is never used to train AI models.
2B+ Annual Comms. | #1 Best in KLAS (Patient Communications, 2026) | 11+yrs Experience | FedRAMP Class D Certification | 200M+ Patients | 1,000+ Provider Customers
Learn more
Qwen-7B
Qwen-7B is the 7B-parameter version of the large language model series, Qwen (abbr. Tongyi Qianwen), proposed by Alibaba Cloud. Qwen-7B is a Transformer-based large language model, which is pretrained on a large volume of data, including web texts, books, codes, etc. Additionally, based on the pretrained Qwen-7B, we release Qwen-7B-Chat, a large-model-based AI assistant, which is trained with alignment techniques. The features of the Qwen-7B series include:
Trained with high-quality pretraining data. We have pretrained Qwen-7B on a self-constructed large-scale high-quality dataset of over 2.2 trillion tokens. The dataset includes plain texts and codes, and it covers a wide range of domains, including general domain data and professional domain data.
Strong performance. In comparison with the models of the similar model size, we outperform the competitors on a series of benchmark datasets, which evaluates natural language understanding, mathematics, coding, etc.
And more.
Learn more
Galactica
Information overload is a major obstacle to scientific progress. The explosive growth in scientific literature and data has made it ever harder to discover useful insights in a large mass of information. Today scientific knowledge is accessed through search engines, but they are unable to organize scientific knowledge alone.
Galactica is a large language model that can store, combine and reason about scientific knowledge. We train on a large scientific corpus of papers, reference material, knowledge bases and many other sources. We outperform existing models on a range of scientific tasks. On technical knowledge probes such as LaTeX equations, Galactica outperforms the latest GPT-3 by 68.2% versus 49.0%. Galactica also performs well on reasoning, outperforming Chinchilla on mathematical MMLU by 41.3% to 35.7%, and PaLM 540B on MATH with a score of 20.4% versus 8.8%.
Learn more
Qwen2.5-Max
Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.
Learn more
