Anaconda is an AI-native development platform that gives teams a governed path from early experimentation to production AI deployment. The platform is built around trusted open-source packages, secure Python package management, controlled environments, and production-grade orchestration. Anaconda helps organizations avoid broken environments, dependency conflicts, security gaps, and deployment delays that can slow AI initiatives. Anaconda Core provides validated packages, automated security scanning, and intelligent dependency conflict resolution for Python and data science teams. Its platform capabilities support AI orchestration, trusted distribution, and enterprise workflows for building and scaling models. Anaconda is widely used across the AI, data science, Python, and enterprise developer communities. The company positions open source as a foundation for AI innovation and emphasizes Python as a core language for the next era of AI development. Anaconda also provides learning courses, certifications, reports, guides, professional services, documentation, and support resources. By combining package governance, environment management, open-source security, and AI development workflows, Anaconda helps teams build trusted AI systems on their own terms.
Learn more
The sovereign AI that turns every answer into lasting expertise.
Cut response times by up to 90%. Optivalue.ai automates information discovery and drafting, freeing experts for the high-impact personalization that wins bids. It acts as an expert librarian for your knowledge base: submit a questionnaire — RFP, audit, security or compliance — and get a complete, source-verified draft in minutes.
Every answer is built on 89 Domain-Specific Language Models specialized by function and industry, not a generic LLM. Each answer carries a 0-100 confidence score and precise source citations (document, page, timestamp) for full traceability. When no source supports an answer, Optivalue.ai says "I don't know" rather than hallucinate. You don't just answer correctly — you prove it.
It's an engine of progress for your organization. Optivalue.ai runs a gap analysis to identify weaknesses in your documentation. Following the recommendations strengthens your internal documents and builds lasting expertise across the organization.
Your data stays yours: a private AI per client, never shared, deployed on-premise or in a sovereign cloud. Enterprise-grade security, compliant with GDPR, ISO 27001, HIPAA, SOC 2 and FedRAMP. All plans include unlimited users and unlimited projects. Start your 14-day free trial — no credit card, no commitment.
Trusted by L'Oréal, Stellantis, Thales Alenia Space, Exaion (EDF Group), Equans and Mango. Winner of the European Sovereignty Prize 2026 (AI category).
Learn more
Cerebras-GPT
Training cutting-edge language models presents significant challenges; it demands vast computational resources, intricate distributed computing strategies, and substantial machine learning knowledge. Consequently, only a limited number of organizations embark on the journey of developing large language models (LLMs) from the ground up. Furthermore, many of those with the necessary capabilities and knowledge have begun to restrict access to their findings, indicating a notable shift from practices observed just a few months ago.
At Cerebras, we are committed to promoting open access to state-of-the-art models. Therefore, we are excited to share with the open-source community the launch of Cerebras-GPT, which consists of a series of seven GPT models with parameter counts ranging from 111 million to 13 billion. Utilizing the Chinchilla formula for training, these models deliver exceptional accuracy while optimizing for computational efficiency. Notably, Cerebras-GPT boasts quicker training durations, reduced costs, and lower energy consumption compared to any publicly accessible model currently available. By releasing these models, we hope to inspire further innovation and collaboration in the field of machine learning.
Learn more
Dolly
Dolly is an economical large language model that surprisingly demonstrates a notable level of instruction-following abilities similar to those seen in ChatGPT. While the Alpaca team's research revealed that cutting-edge models could be encouraged to excel in high-quality instruction adherence, our findings indicate that even older open-source models with earlier architectures can display remarkable behaviors when fine-tuned on a modest set of instructional training data. By utilizing an existing open-source model with 6 billion parameters from EleutherAI, Dolly has been slightly adjusted to enhance its ability to follow instructions, showcasing skills like brainstorming and generating text that were absent in its original form. This approach not only highlights the potential of older models but also opens new avenues for leveraging existing technologies in innovative ways.
Learn more
