Discover AI agents built for Research: Comprehensive directory of solutions verified by AI agency professionals focused on the Research sector.

AI Agents for Research | AI Agent Store

QuillBot is a comprehensive AI-driven writing platform designed to assist users in improving their writing through a suite of tools. Key features include a Paraphraser that rephrases text to enhance clarity and style, a Grammar Checker that identifies and corrects grammatical errors, a Summarizer that condenses lengthy texts, and an AI Detector that analyzes content for AI-generated text. QuillBot integrates seamlessly with various platforms, including browser extensions and word processors, making it a versatile tool for students, professionals, and content creators aiming to produce polished and effective written communication.

QuillBot

quillbot

An AI-powered writing assistant offering tools for paraphrasing, grammar checking, summarizing, and more to enhance writing quality and productivity.

ComfyUI is a free, open-source, node-based platform for generative AI. Creators assemble visual workflows to produce images, video, 3D, and audio, extend functionality with custom nodes, and run everything locally for speed, control, and cost savings. The Comfy Org ecosystem includes a desktop app, a registry for custom nodes, continuous-integration testing, and an announced Comfy Cloud beta to run workflows in the browser without setup.

ComfyUI (Comfy.org)

comfyui-comfy-org

Open-source, node-based generative AI platform to build image, video, 3D, and audio workflows locally or in the cloud.

Wan2.2 is an open-weights family of large-scale video generative models released by the Wan-Video team as the successor to Wan2.1. It introduces expanded training data and architecture upgrades, offering multiple variants for text-to-video, image-to-video, video-to-video, and even speech-to-video generation. The models produce cinematic, higher-resolution clips with stronger temporal consistency and motion control, and are available under an Apache-2.0 license with runnable repos and Hugging Face checkpoints.

Wan2.2

wan2-2

Open-source video generation model family (5B/14B) for text/image/video-to-video, delivering 1080p clips with improved motion and control.

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.

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.

The Unitree R1 is a lightweight (~25 kg), ultra‑affordable humanoid robot (~1.2 m tall) designed for research, education, and early agentic experimentation. It features 26 degrees of freedom for flexible mobility—running, cartwheels, and spin‑kicks—and includes binocular cameras, a 4‑mic array, speaker, 8‑core CPU/GPU, and LLM‑based voice and visual intelligence. While hands are not standard (optional in EDU version), the R1 is fully customizable and serves as a low‑cost introduction to embodied AI agents.

Unitree R1

unitree-r1

Ultra‑lightweight humanoid robot with 26 joints, multimodal AI, priced for research and education.

GLM‑4.5 is an open‑source, Mixture‑of‑Experts (MoE) large‑language model from Z.ai, designed for intelligent agent applications. It features 355 B parameters (32 B active) with an efficient ’thinking/non‑thinking’ hybrid reasoning mode and 128 K context length. A smaller variant, GLM‑4.5‑Air, offers 106 B parameters (12 B active) for more efficient deployments. GLM‑4.5 excels at reasoning, coding, and tool‑calling tasks and ranks among the top performers on benchmarks compared with models like o3, Grok‑4, Claude Sonnet, and GPT‑4.1.

GLM‑4.5

glm-4-5

Open-source hybrid‑reasoning MoE foundation model optimized for intelligent agent tasks with 128K context and tool use.

Amazon SageMaker Studio Lab is a free, browser‑based machine learning development environment powered by open‑source JupyterLab. It gives users access to T3.xlarge CPU and G4dn.xlarge GPU runtimes (with session and daily limits), along with 15 GB of persistent storage, Git integration, preinstalled ML frameworks, and the SageMaker Distribution environment for easy migration to SageMaker Studio. No AWS account or credit card is required. Ideal for students, educators, and developers looking to learn, prototype, or teach ML workflows without setup overhead.

Amazon SageMaker Studio Lab

amazon-sagemaker-studio-lab

Free browser‑based JupyterLab environment for ML experiments with CPU/GPU and persistent storage.

Amazon Bedrock AgentCore is a modular suite of AWS services providing secure, scalable deployment and operations for AI agents. It offers Runtime for serverless agent execution with session isolation and long-running support, Memory for context-aware agents, Identity for secure access, Gateway to convert APIs into agent-ready tools, Browser for managed web automation, Code Interpreter for sandboxed code execution, and Observability for tracing and debugging workflows. AgentCore supports any open-source framework and any foundation model, inside or outside Bedrock, enabling developers to accelerate agents into production with enterprise-grade flexibility, security, and monitoring.

Amazon Bedrock AgentCore

amazon-bedrock-agentcore

Modular AWS platform for deploying, enhancing, and monitoring AI agents securely at scale.

TEN Framework is an open-source modular system for building autonomous AI agents capable of reasoning, memory management, and tool usage. Designed to reflect real-world constraints, it incorporates a Thought-Emission-Norm (TEN) architecture, encouraging agents to think before acting. The framework supports open-ended planning, persistent memory storage, and tool augmentation. Developers can use TEN to experiment with agent autonomy and deploy agents that simulate complex decision-making workflows.

TEN Framework

ten-framework

An open-source framework for building autonomous AI agents that interact with the real world through tools and memory.

Trae Agent is an open-source, LLM-powered command-line assistant developed by ByteDance for software development workflows. It supports multi-LLM providers, file editing, bash execution, tool integration, trajectory logging, and a modular architecture—ideal for debugging, patching, documentation, and research.

Trae Agent

trae-agent

Open-source CLI LLM agent for automating software engineering tasks via natural-language commands.

Kiro is an agentic Integrated Development Environment from AWS that transforms user prompts into structured specs, designs, and tasks. It integrates multimodal input, agent hooks for automation, MCP tool access, real-time code diffs, and supports local/cloud execution to help developers move from prototype to production.

Kiro AI IDE

kiro-ai-ide

Agentic AI IDE by AWS for spec-driven coding, multimodal chat, and automated agent hooks.

AI Agents for "Research" Industry