
Dun & Bradstreet’s ChatD&B offers a powerful, AI-driven chat interface that simplifies how organizations research and assess companies. Instead of traditional complex filtering, users interact naturally by asking questions in their own words to receive tailored insights such as company financials, risk scores, and market data. The platform taps into the vast Dun & Bradstreet Data Cloud to deliver real-time, reliable information that supports smarter, faster business decisions. Enhanced features include visibility into the data sources behind results, chat history for audit trails, and quick answers to product-related queries. ChatD&B is designed to optimize workflows across sales, finance, and risk management by providing instant access to trusted company data. It helps teams discover new opportunities, evaluate customers, and make confident decisions all through easy chat conversations. The platform also enables better compliance and verification by allowing users to track and reference past interactions. With ChatD&B, organizations can accelerate growth and reduce operational friction.
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Evertune is the Generative Engine Optimization (GEO) platform that helps brands improve visibility in AI search across ChatGPT, AI Overview, AI Mode, Gemini, Claude, Perplexity, Meta, DeepSeek and Copilot.
We're building the first marketing platform for AI search as a channel. We show enterprise brands exactly where they stand when customers discover them through AI — then give them the precise playbook to show up stronger. This is Generative Engine Optimization, also known as AI SEO.
Using applied AI and data science at scale, we give brands statistical confidence in our actionable insights. We decode what gets brands mentioned more and ranked higher, provide reliable brand monitoring and competitive intelligence, then deliver actionable content strategies that move the needle. Our AI SEO and AI search engine optimization tools are built for how LLMs actually work.
Why Leading Enterprise Marketers Choose Evertune:
Data Science at Scale: We prompt across every major LLM at volumes that capture response variations and ensure statistical significance for comprehensive brand monitoring and competitive intelligence.
Actionable Strategy, Not Just Dashboards: Specific content, messaging and distribution tactics that increase your AI search visibility.
Dedicated Customer Success: Hands-on training and strategic guidance to turn insights into improved performance in AI search.
Built for AI search as a channel: Organic visibility today, paid advertising and commerce tomorrow.
Proven Leadership: Founded by The Trade Desk veterans who pioneered data-driven digital advertising. Backed by data scientists from OpenAI, Meta and other AI leaders.
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Xiaomi MiMo Studio
MiMo Studio is an online platform that harnesses the capabilities of Xiaomi’s MiMo models, enabling users to engage with sophisticated language models like MiMo-V2-Flash for interactive conversations, augmented search results, reasoning tasks, and coding assistance. This platform serves as a dynamic “AI playground,” allowing users to converse with the model for information retrieval, clarification, code generation or debugging, and idea exploration without the need for software installation. It features web search integration and adjustable modes to alternate between quick responses and more contemplative outputs, catering to complex tasks and assisting developers and creators with a wide range of projects from research to practical applications. Being browser-based, it ensures straightforward online access to Xiaomi’s innovative AI models, empowering users to experiment with extensive reasoning, effective problem-solving, and engaging multi-turn dialogues. Furthermore, this accessibility fosters a collaborative environment where creativity and technology can merge seamlessly, enhancing the user experience.
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Inkling
Inkling is Thinking Machines’ open-weights foundation model built for customization, multimodal reasoning, and agentic AI workflows. The model uses a Mixture-of-Experts architecture with 975 billion total parameters and 41 billion active parameters, making it large in capacity while activating only a subset of experts per token. Inkling supports up to a 1 million token context window and was pretrained on 45 trillion tokens spanning text, images, audio, and video. It is designed as a broad generalist model with strengths across coding, reasoning, instruction following, factuality, tool use, vision, audio understanding, forecasting, and safety. Developers can tune its thinking effort to trade off latency, cost, and performance, which is useful for production systems that need efficient reasoning at scale. Inkling can be fine-tuned on Tinker, tested in the Inkling Playground, and deployed through partners such as TogetherAI, Fireworks, Modal, Databricks, Baseten, vLLM, SGLang, llama.cpp, and Hugging Face transformers. The model can generate applications, operate tools, create styled artifacts, reason over visual and audio inputs, and support long refinement loops for collaborative work. Thinking Machines also previewed Inkling-Small, a lighter Mixture-of-Experts model with 276 billion total parameters and 12 billion active parameters for lower-cost and lower-latency workloads. By combining open weights, multimodal training, agentic capabilities, efficient reasoning, and fine-tuning support, Inkling gives builders a flexible AI foundation for specialized products and workflows.
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