Evertune
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.
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: We decode exactly what gets brands mentioned more and ranked higher, then deliver the specific content, messaging and distribution moves that improve your position.
Dedicated Customer Success: Our team provides hands-on training and strategic guidance to help you execute on insights and improve your AI search visibility.
Purpose-Built for AI as a Channel: Evertune was founded in 2024 specifically for how LLMs select and rank brands. While others retrofit SEO tools, we're architecting the infrastructure for where marketing is going: AI search with organic visibility today, paid placements and agentic commerce tomorrow.
Proven Leadership: Our founders helped build The Trade Desk and pioneered data-driven digital advertising. We've shepherded an entire industry through transformation before and have seen early adopters grab the competitive advantage. Our investors, including data scientists from OpenAI and Meta, back our vision because they see where this channel is heading.
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AthenaHQ
AthenaHQ is a platform dedicated to Generative Engine Optimization (GEO), designed to help businesses dominate AI-driven brand discovery. The platform supports real-time monitoring of brand mentions and perception in AI-generated content, enabling businesses to refine their AI strategy. AthenaHQ integrates advanced tools for competitor analysis, AI search volume tracking, and sentiment analysis, providing businesses with crucial insights to adjust and optimize their approach. By focusing on AI readability and structured data, AthenaHQ helps brands enhance their visibility across generative search engines, positioning them for long-term success as the search landscape shifts towards AI-driven discovery.
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DeepSeek-V3.2-Exp
We are excited to present DeepSeek-V3.2-Exp, our latest experimental model that evolves from V3.1-Terminus, incorporating the cutting-edge DeepSeek Sparse Attention (DSA) technology designed to significantly improve both training and inference speeds for longer contexts. This innovative DSA framework enables accurate sparse attention while preserving the quality of outputs, resulting in enhanced performance for long-context tasks alongside reduced computational costs. Benchmark evaluations demonstrate that V3.2-Exp delivers performance on par with V3.1-Terminus, all while benefiting from these efficiency gains. The model is fully functional across various platforms, including app, web, and API. In addition, to promote wider accessibility, we have reduced DeepSeek API pricing by more than 50% starting now. During this transition phase, users will have access to V3.1-Terminus through a temporary API endpoint until October 15, 2025. DeepSeek invites feedback on DSA from users via our dedicated feedback portal, encouraging community engagement. To further support this initiative, DeepSeek-V3.2-Exp is now available as open-source, with model weights and key technologies—including essential GPU kernels in TileLang and CUDA—published on Hugging Face, and we are eager to observe how the community will leverage this significant technological advancement. As we unveil this new chapter, we anticipate fruitful interactions and innovative applications arising from the collective contributions of our user base.
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DeepSeek-V3.2
DeepSeek-V3.2 represents one of the most advanced open-source LLMs available, delivering exceptional reasoning accuracy, long-context performance, and agent-oriented design. The model introduces DeepSeek Sparse Attention (DSA), a breakthrough attention mechanism that maintains high-quality output while significantly lowering compute requirements—particularly valuable for long-input workloads. DeepSeek-V3.2 was trained with a large-scale reinforcement learning framework capable of scaling post-training compute to the level required to rival frontier proprietary systems. Its Speciale variant surpasses GPT-5 on reasoning benchmarks and achieves performance comparable to Gemini-3.0-Pro, including gold-medal scores in the IMO and IOI 2025 competitions. The model also features a fully redesigned agentic training pipeline that synthesizes tool-use tasks and multi-step reasoning data at scale. A new chat template architecture introduces explicit thinking blocks, robust tool-interaction formatting, and a specialized developer role designed exclusively for search-powered agents. To support developers, the repository includes encoding utilities that translate OpenAI-style prompts into DeepSeek-formatted input strings and parse model output safely. DeepSeek-V3.2 supports inference using safetensors and fp8/bf16 precision, with recommendations for ideal sampling settings when deployed locally. The model is released under the MIT license, ensuring maximal openness for commercial and research applications. Together, these innovations make DeepSeek-V3.2 a powerful choice for building next-generation reasoning applications, agentic systems, research assistants, and AI infrastructures.
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