Sakana Marlin
Sakana Marlin is your Virtual CSO for Ultra Deep Research, built so AI handles research and humans focus on decision-making. It is not just another deep research assistant; it is an autonomous agent designed to take on the kind of substantial strategy research that a Chief Strategy Officer and a small team might otherwise spend weeks on. Powered by Sakana AI’s core reasoning architecture, Sakana Marlin scales inference-time compute to execute up to eight hours of continuous, autonomous reasoning. Once a research topic is set, it works without further human input, repeatedly forming hypotheses, gathering information, navigating the web, and resolving contradictions on its own. Instead of generating text in seconds, its focus is long-horizon, sample-efficient reasoning that cycles through hypothesis testing and web research to extract what truly matters from vast amounts of information. Sakana Marlin does more than summarize.
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Perplexity Computer
Perplexity Computer is an AI-powered super agent designed to autonomously complete complex digital tasks from start to finish. Users simply describe the outcome they want, and the system breaks the request into structured subtasks executed by specialized AI models. It can build websites, generate reports, compile datasets, and create multimedia content with minimal manual input. The platform dynamically selects the most suitable AI models for each component of a project, optimizing for research, images, video, or quick searches. Designed for extended autonomous operation, it can run workflows for hours or longer without interruption. By abstracting away technical complexity, it transforms high-level intent into fully executed results. Perplexity Computer streamlines advanced AI capabilities into a single, outcome-focused interface.
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Gemini Deep Research Max
Gemini Deep Research is Google’s next-generation autonomous research agent, designed to plan, execute, and synthesize complex, multi-step research tasks across the web and private data sources into high-quality, structured outputs. Built on top of advanced Gemini models such as Gemini 3.1 Pro, it introduces a system where the AI can break down a user’s query into sub-tasks, search across multiple sources, evaluate relevance, and iteratively refine results before producing a comprehensive, cited report. It is positioned as a “step change” in long-horizon research workflows, enabling autonomous exploration of both public web content and custom enterprise data while maintaining context and coherence across extended reasoning chains. It supports features such as MCP (Model Context Protocol) integration, native visualizations, and significantly improved analytical quality, allowing users to generate insights.
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Apodex
Apodex is a self-evolving heavy-duty solver for deep research, built to answer the questions that matter with verified reasoning rather than a quick chat reply. It reasons through hard problems step by step, checks every conclusion before moving to the next, and produces a verified brief with citations in every report. Designed for complex inquiries with no easy existing answer, Apodex performs deep research, explores evidence, and verifies each step so users can trust how the final conclusion was reached. Signed-in users can save every inquiry, return, and continue anytime, search across threads, branch off any report, and review a step-level reasoning trace. Apodex-1.0 is a verification-centric model for deep research that can run as a standard tool-using ReAct agent, while its heavy-duty mode deploys an asynchronous agent team where specialized sub-agents handle retrieval and verification, route findings through a shared evidence pool, and feed a global verifier.
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