Research AI Agents Agentic AI directory: Find intelligent solutions from premier AI agencies and automation specialists globally.

Agentic AI in "Research AI Agents" Category | AI Agent Store

Helpfull is an innovative platform that enables businesses to obtain immediate feedback by leveraging a pool of over 50,000 human panelists and customizable AI personas. It facilitates various research activities, including market surveys, A/B testing, usability studies, and copy evaluations. Users can design tailored surveys, select specific demographics, and receive actionable insights within minutes, streamlining the decision-making process and enhancing product development strategies.

Helpfull

helpfull

An AI-driven platform providing rapid market research insights through human panelists and customizable AI personas.

THEUS is Aigora’s enterprise AI research infrastructure for transforming proprietary sensory and consumer research into audit-ready insights. It uses a multimodal pipeline to extract and validate atomic facts from documents and provides page-level citations and Fact IDs for traceability. THEUS supports cross-study synthesis, research design assistance, and stakeholder-ready visualizations, and it emphasizes isolation between projects, no training on customer data, and time-limited data retention. The product also presents domain-expert AI “avatars” (e.g., an AI analyst or AI moderator) to guide exploration and insight generation from institutional research memory.

THEUS (Aigora)

theus-aigora

Enterprise AI research system that turns proprietary studies into traceable insights with fact IDs, citations, and expert avatars for synthesis.

Bright Data Web MCP is an open-source Model Context Protocol (MCP) server that connects AI assistants to the live public web with built-in unblocking to avoid CAPTCHAs and rate limits. It provides tools for real-time web search, page fetching and scraping (including via Bright Data’s web unlocker), and optional browser automation for navigating and interacting with dynamic sites. It supports a free “Rapid” tier (limited toolset and monthly request allowance) and paid usage-based modes that unlock additional tool groups such as browser control and broader web data tooling. It can be used via Bright Data’s hosted MCP endpoint or run locally via an npm package.

Bright Data Web MCP

bright-data-web-mcp

MCP server that gives AI agents reliable web search, scraping, and browser automation with 5,000 free monthly requests.

Atelier Ruixen is a web-based AI knowledge companion focused on generative knowledge management (GKM). It is positioned as a “librarian” style agent that helps users move from vague questions to clearer, higher-signal queries, then curates and organizes an actionable reading list to support deeper understanding. The experience emphasizes turning exploration into structured insights by guiding query refinement, helping users discover relevant resources, and keeping an evolving knowledge flow for ongoing learning and research.

Atelier Ruixen

atelier-ruixen

AI knowledge companion that refines questions and curates reading lists to turn scattered info into actionable insights.

GLM-4.6V is a next-generation multimodal large language model series from Z.ai (Zhipu AI), designed for high-fidelity visual understanding and long-context reasoning across images, video, documents, and text. It comes in two main variants: the 106B-parameter GLM-4.6V foundation model for cloud and cluster deployment, and the lightweight GLM-4.6V-Flash (9B) optimized for local and low-latency applications. With a 128k token context window, GLM-4.6V can read large PDFs, slide decks, and multi-page mixed-media documents in a single pass. Native multimodal function calling lets it use tools directly from visual inputs, closing the loop from perception to executable actions and enabling powerful agent-style workflows. Typical use cases include visual document QA, chart and layout understanding, multimodal search and analysis, converting UI screenshots into production-ready code, and generating image-rich content. The models are released with open weights under a permissive open-source license, making them suitable for research, self-hosted deployments, and integration into production systems.

GLM-4.6V

glm-4-6v

Open-source multimodal GLM from Z.ai unifying vision, text, and tool calling for long-context reasoning, search, coding, and UI-to-code.

Kosmos is an autonomous AI scientist that automates data-driven discovery across domains like neuroscience, metabolomics, materials science, and genetics. Given an open-ended research objective and one or more datasets, Kosmos runs long research campaigns of up to ~12 hours, iterating between data analysis, literature search, and hypothesis generation. It uses a structured world model to coordinate agents and maintain coherence over hundreds of rollouts, typically executing tens of thousands of lines of code and reading around 1,500 papers per run before synthesizing a fully cited scientific report whose statements are traceable to code cells or primary literature. Independent scientists have estimated that a 20-cycle Kosmos run can compress roughly six months of PhD-level work into a single day, with most statements judged accurate and reproducible. Researchers can access Kosmos via the Edison Scientific platform with a credit-based pricing model, while an open-source implementation on GitHub allows teams to self-host and extend the system using multiple model providers.

Kosmos

kosmos

Autonomous AI scientist for long research campaigns that analyzes data and literature to produce fully cited scientific reports.

Cell2Sentence (C2S) is an open-source framework from the van Dijk Lab that represents single-cell RNA-seq profiles as textual “cell sentences” (genes ordered by expression), enabling large language models to natively model biology. The project includes code, docs, and open models (C2S-Scale) released with Google Research/DeepMind for state-of-the-art single-cell tasks like cell typing, perturbation prediction, and virtual cell generation.

Cell2Sentence

cell2sentence

Open-source framework that turns single-cell gene expression into 'cell sentences' so LLMs can analyze and generate biology insights.

Lila Sciences is building what it calls “Scientific Superintelligence”: AI-driven platforms plus autonomous labs (AI Science Factories) that design, run, observe, and refine experiments across life sciences, chemistry, and materials. Founded in 2023 by Flagship Pioneering, it uses generative AI, robotics, and automation to accelerate R&D (e.g. novel therapeutics, catalysts, new materials) at a scale beyond traditional lab workflows.

Lila Sciences

lila-sciences

Platform combining autonomous labs & AI to accelerate discovery in life, chemical, and materials sciences.

AlphaSense is a market intelligence and search platform that leverages AI agents—including Generative Search, Deep Research, and Agent Interviewer—to autonomously source, analyze, and synthesize insights from over 500 million business documents and investor interview transcripts, accelerating decision-ready research workflows.

AlphaSense

alphasense

An AI-powered market intelligence platform that autonomously sources expert insights and delivers analyst-level research at scale.

Isomorphic Labs is an AI-driven drug discovery company founded by Demis Hassabis in 2021 as a spin-off from DeepMind. The company utilizes advanced AI models, including AlphaFold, to predict protein structures and interactions, aiming to revolutionize the drug discovery process. By modeling complex biological systems, Isomorphic Labs seeks to design novel therapeutics more efficiently. The company has established partnerships with pharmaceutical giants like Eli Lilly and Novartis and secured $600 million in funding to advance its mission of accelerating therapeutic development.

Isomorphic Labs

isomorphic-labs

An AI-driven drug discovery company leveraging AlphaFold to accelerate therapeutic development.

AMIE (Articulate Medical Intelligence Explorer) is a research AI system developed by Google Research and DeepMind, designed to engage in diagnostic medical conversations. Built upon the Gemini 2.0 Flash model, AMIE integrates a state-aware reasoning framework that allows it to adapt its responses based on the evolving context of a clinical dialogue. This enables AMIE to intelligently request, interpret, and reason about visual medical information, such as skin photos, ECGs, and lab results, enhancing its diagnostic capabilities. In evaluations using Objective Structured Clinical Examinations (OSCEs), AMIE demonstrated performance comparable to or exceeding that of primary care physicians in areas like diagnostic accuracy, multimodal data interpretation, and communication skills. While AMIE shows promise in augmenting clinical decision-making, further research and validation are required before real-world deployment.

AMIE

amie

A multimodal AI diagnostic agent that conducts clinical conversations and interprets medical images for accurate diagnoses.

Google's AI Co-Scientist is a multi-agent system built on Gemini 2.0, designed to function as a virtual scientific collaborator. It assists researchers by generating novel hypotheses, designing experiments, and analyzing complex datasets. The system employs specialized agents that mimic the scientific method through processes like generation, reflection, and ranking. In collaboration with institutions like Stanford University and Imperial College London, the AI Co-Scientist has demonstrated its ability to identify novel biological mechanisms and potential therapeutic targets, showcasing its potential to accelerate scientific and biomedical discoveries.

Google AI Co-Scientist

google-ai-co-scientist

A multi-agent AI system that collaborates with scientists to generate hypotheses and accelerate biomedical research.

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