Best AI tools for< Research Cells >

Deepcell is a company that develops technology for single-cell analysis. Their REM-I platform combines label-free imaging, deep learning, and gentle sorting to leverage single cell morphology as a high-dimensional quantitative readout. This allows researchers to gain insights into cells' phenotype and function to address important research questions across biology.

Formula Wizard is an AI-powered software designed to assist users in writing Excel, Airtable, and Notion formulas effortlessly. By leveraging artificial intelligence, the application automates the process of formula creation, allowing users to save time and focus on more critical tasks. With features like automating tedious tasks, unlocking insights from data, and customizing templates, Formula Wizard streamlines the formula-writing process for various spreadsheet applications.

Reportify is an AI platform for investment research that provides detailed analysis and insights on various companies, filings, transcripts, reports, and news. Users can explore financial data, performance metrics, and market trends to make informed investment decisions. The platform offers a comprehensive view of the investment landscape, including company histories, financial reports, and industry analysis.

Looppanel is an AI-powered research assistant that revolutionizes the way research data is managed. It automatically records calls, transcribes them, and centralizes all research data in one place. Looppanel's highly accurate transcripts support multiple languages and accents, enabling users to focus on interviews while AI takes notes. The platform simplifies analysis, allows for time-stamped note-taking, and facilitates collaboration among team members. Looppanel ensures data security and compliance with high standards, making it a valuable tool for researchers and professionals.

Recontact is an AI-powered tool designed to help users analyze and gain insights from user calls efficiently. By leveraging AI technology, Recontact can process and extract valuable information from user conversations, enabling users to understand customer needs, identify trends, and generate detailed reports in a matter of minutes. The tool streamlines the process of listening to call transcripts, making affinity diagrams, and understanding customer requirements, saving users valuable time and effort. Recontact is best suited for early-stage founders, user research teams, and customer support teams looking to analyze user interviews, validate startup ideas, and improve customer interactions.

EarningsCall.ai is an AI-powered application that provides stock earnings call summaries and insights, helping users save time and increase equity research productivity. It summarizes earnings call insights into Guidance, Strategic Updates, Risk, and Tweet, and offers a personalized Q&A section. Users can quickly discern key facts and strategic highlights from company earnings, making it easier to monitor multiple companies at once.

CustomerIQ is an AI platform designed to drive revenue and retention by automating administrative tasks and extracting actionable insights for sales teams, customer success, marketing, and product departments. It seamlessly integrates with CRM, help desk, and messaging apps to capture and sync CRM fields, automate research, meeting briefs, and handoffs, and quantify insights for product, marketing, and customer experience. CustomerIQ prioritizes enterprise-grade security and scalability, ensuring data privacy and encryption. The platform aims to empower teams with automation and insights, allowing them to focus on building rapport while the AI handles the rest.

AlphaSense is a market intelligence and search platform that provides access to a comprehensive universe of content, including company filings, broker research, expert calls, regulatory documents, press releases, and internal content. It utilizes AI and NLP technology to surface relevant insights, monitor market trends, and collaborate on research. AlphaSense is trusted by thousands of organizations, including 85% of the S&P 100, 80% of the top asset management firms, and 80% of the top consultancies.

The website focuses on groundbreaking research in various scientific fields, including quantum communication, semiconductor dynamics, mental health support, dietary interventions, computer vision, autonomous systems safety, movie recommendations, fake cell tower detection, electron-boson interactions, solar observations, network efficiency, galaxy formation, asteroseismology, protein biosynthesis, and high-temperature semiconductor diodes.

Limeline is an AI-powered meeting assistant application that revolutionizes communication by enabling users to create, conduct, and conclude meetings seamlessly. It offers automated AI agents for meetings and calls, real-time transcripts and summaries, AI-curated meetings, and branded call experiences. Limeline enhances team productivity across various industries such as Sales, Customer Success, Research, Recruiting, Marketing, IT, and Education by automating routine communications and increasing attendance. With Limeline, users can let AI do the talking, dive into insights, and focus on the important parts of meetings without worrying about taking notes.

Boba Boba is an AI co-pilot for generative ideation, designed to assist users in researching signals and trends by searching the web for articles and news to answer qualitative research questions. It can quickly analyze and summarize articles, earnings calls, etc., brainstorm possible futures based on strategic prompts, ideate future scenarios, brainstorm strategies using the Playing to Win framework, and help build storyboards for current or future state scenarios.

QRev is an AI-powered sales tool designed to revolutionize the sales process by automating mundane tasks and allowing salespeople to focus on closing deals. It offers features such as researching prospects, scaling outreach, competitive research, and personalized email campaigns. QRev aims to save time and increase efficiency for sales teams, providing modern CRM capabilities and insights into sales calls. With QRev, users can access leads from a massive database, run research 24/7, and personalize campaign sequences at scale.

Insitro is a drug discovery and development company that uses machine learning and data to identify and develop new medicines. The company's platform integrates in vitro cellular data produced in its labs with human clinical data to help redefine disease. Insitro's pipeline includes wholly-owned and partnered therapeutic programs in metabolism, oncology, and neuroscience.

Salieri is a multi-agent LLM home multiverse platform that offers an efficient, trustworthy, and automated AI workflow. The innovative Multiverse Factory allows developers to elevate their projects by generating personalized AI applications through an intuitive interface. The platform aims to optimize user queries via LLM API calls, reduce expenses, and enhance the cognitive functions of AI agents. Salieri's team comprises experts from top AI institutes like MIT and Google, focusing on generative AI, neural knowledge graph, and composite AI models.

Decode Investing is an AI tool designed to help users discover and analyze businesses for investment purposes. The platform offers a range of features such as an AI Chat assistant, stock screener, and analysis of SEC filings and earnings calls. Users can access a leaderboard to track performance and insights on various projects. Decode Investing is a comprehensive tool that aims to simplify the investment process by providing valuable data and insights to users.

UserCall is an AI-powered platform that enables users to conduct high-quality user interviews using custom AI interviewers. The platform offers deep insights through 1:1 voice calls with users, providing smart follow-up questions to uncover customer needs. UserCall saves time and effort by extracting key actionable insights from conversations, offering branded interview links, and facilitating continuous feedback, market research, participant screening, usability testing, and customer satisfaction analysis.

Monexa is a professional-grade financial analysis platform that offers institutional-grade market insights, news, and data analysis in one powerful platform. It provides comprehensive market analysis, AI-powered insights, rich data visualizations, research and analysis tools, advanced screener, rich financial history, automated SWOT analysis, comprehensive reports, interactive performance analytics, institutional investment tracking, company intelligence, dividend analysis, earnings call analysis, portfolio analytics, strategy explorer, real-time market intelligence, and more. Monexa is designed to help users make data-driven investment decisions with a comprehensive suite of analytical capabilities.

Respell is an advanced Agentic AI Workflow platform that offers automation for powerful workflows. It leverages cutting-edge AI models from various providers such as OpenAI, Anthropic, and Cohere. Respell provides custom-built agents for research, phone calls, integrations, and more. Users can connect Respell with popular platforms like Gmail, Notion, Slack, and Salesforce to leverage AI for data analysis, understanding, and decision-making. The platform ensures enterprise security with SOC II compliance and offers features like human in the loop functionality, API integration, and cross-team collaboration.

Byterat is a cloud-based platform that provides battery data management, visualization, and analytics. It offers an end-to-end data pipeline that automatically synchronizes, processes, and visualizes materials, manufacturing, and test data from all labs. Byterat also provides 24/7 access to experiments from anywhere in the world and integrates seamlessly with current workflows. It is customizable to specific cell chemistries and allows users to build custom visualizations, dashboards, and analyses. Byterat's AI-powered battery research has been published in leading journals, and its team has pioneered a new class of models that extract tell-tale signals of battery health from electrical signals to forecast future performance.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

cellseg-models.pytorch is a Python library built upon PyTorch for 2D cell/nuclei instance segmentation models. It provides multi-task encoder-decoder architectures and post-processing methods for segmenting cell/nuclei instances. The library offers high-level API to define segmentation models, open-source datasets for training, flexibility to modify model components, sliding window inference, multi-GPU inference, benchmarking utilities, regularization techniques, and example notebooks for training and finetuning models with different backbones.

DeepSeek is a new experimental architecture for a large language model (LLM) powered internet-scale retrieval engine. Unlike current research agents designed as answer engines, DeepSeek aims to process a vast amount of sources to collect a comprehensive list of entities and enrich them with additional relevant data. The end result is a table with retrieved entities and enriched columns, providing a comprehensive overview of the topic. DeepSeek utilizes both standard keyword search and neural search to find relevant content, and employs an LLM to extract specific entities and their associated contents. It also includes a smaller answer agent to enrich the retrieved data, ensuring thoroughness. DeepSeek has the potential to revolutionize research and information gathering by providing a comprehensive and structured way to access information from the vastness of the internet.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

This repository contains a student training series focusing on AI-driven science on supercomputers. It covers topics such as ALCF systems overview, AI on supercomputers, neural networks, LLMs, and parallel training techniques. The content is organized into subdirectories with prefixed indexes for easy navigation. The series aims to provide hands-on experience and knowledge in utilizing AI on supercomputers for scientific research.

LLM Engineering is an 8-week course designed to help learners master AI and LLMs through a series of projects that gradually increase in complexity. The course covers setting up the environment, working with APIs, using Google Colab for GPU processing, and building an autonomous Agentic AI solution. Learners are encouraged to actively participate, run code cells, tweak code, and share their progress with the community. The emphasis is on practical, educational projects that teach valuable business skills.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

AITom is an open-source platform for AI-driven cellular electron cryo-tomography analysis. It is developed to process large amounts of Cryo-ET data, reconstruct, detect, classify, recover, and spatially model different cellular components using state-of-the-art machine learning approaches. The platform aims to automate cellular structure discovery and provide new insights into molecular biology and medical applications.

Cellm is an Excel extension that allows users to leverage Large Language Models (LLMs) like ChatGPT within cell formulas. It enables users to extract AI responses to text ranges, making it useful for automating repetitive tasks that involve data processing and analysis. Cellm supports various models from Anthropic, Mistral, OpenAI, and Google, as well as locally hosted models via Llamafiles, Ollama, or vLLM. The tool is designed to simplify the integration of AI capabilities into Excel for tasks such as text classification, data cleaning, content summarization, entity extraction, and more.

DNAnalyzer is a nonprofit organization dedicated to revolutionizing DNA analysis through AI-powered tools. It aims to democratize access to DNA analysis for a deeper understanding of human health and disease. The tool provides innovative AI-powered analysis and interpretive tools to empower geneticists, physicians, and researchers to gain deep insights into DNA sequences, revolutionizing how we understand human health and disease.

BIA `bob` is a Jupyter-based assistant for interacting with data using large language models to generate Python code. It can utilize OpenAI's chatGPT, Google's Gemini, Helmholtz' blablador, and Ollama. Users need respective accounts to access these services. Bob can assist in code generation, bug fixing, code documentation, GPU-acceleration, and offers a no-code custom Jupyter Kernel. It provides example notebooks for various tasks like bio-image analysis, model selection, and bug fixing. Installation is recommended via conda/mamba environment. Custom endpoints like blablador and ollama can be used. Google Cloud AI API integration is also supported. The tool is extensible for Python libraries to enhance Bob's functionality.

HuggingFaceGuidedTourForMac is a guided tour on how to install optimized pytorch and optionally Apple's new MLX, JAX, and TensorFlow on Apple Silicon Macs. The repository provides steps to install homebrew, pytorch with MPS support, MLX, JAX, TensorFlow, and Jupyter lab. It also includes instructions on running large language models using HuggingFace transformers. The repository aims to help users set up their Macs for deep learning experiments with optimized performance.

Aligner is a model-agnostic alignment tool designed to efficiently correct responses from large language models. It redistributes initial answers to align with human intentions, improving performance across various LLMs. The tool can be applied with minimal training, enhancing upstream models and reducing hallucination. Aligner's 'copy and correct' method preserves the base structure while enhancing responses. It achieves significant performance improvements in helpfulness, harmlessness, and honesty dimensions, with notable success in boosting Win Rates on evaluation leaderboards.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Vertex AI is a platform for end-to-end model development. It consist of core components that make the processes of MLOps possible for design patterns of all types.

ShortGPT is a powerful framework for automating content creation, simplifying video creation, footage sourcing, voiceover synthesis, and editing tasks. It offers features like automated editing framework, scripts and prompts, voiceover support in multiple languages, caption generation, asset sourcing, and persistency of editing variables. The tool is designed for youtube automation, Tiktok creativity program automation, and offers customization options for efficient and creative content creation.

Text2Text is a comprehensive language modeling toolkit that offers a wide range of functionalities for text processing and generation. It provides tools for tokenization, embedding, TF-IDF calculations, BM25 scoring, indexing, translation, data augmentation, distance measurement, training/finetuning models, language identification, and serving models via a web server. The toolkit is designed to be user-friendly and efficient, offering a variety of features for natural language processing tasks.

The Open MatSci ML Toolkit is a flexible framework for machine learning in materials science. It provides a unified interface to a variety of materials science datasets, as well as a set of tools for data preprocessing, model training, and evaluation. The toolkit is designed to be easy to use for both beginners and experienced researchers, and it can be used to train models for a wide range of tasks, including property prediction, materials discovery, and materials design.

CopilotKit is an open-source framework for building, deploying, and operating fully custom AI Copilots, including in-app AI chatbots, AI agents, and AI Textareas. It provides a set of components and entry points that allow developers to easily integrate AI capabilities into their applications. CopilotKit is designed to be flexible and extensible, so developers can tailor it to their specific needs. It supports a variety of use cases, including providing app-aware AI chatbots that can interact with the application state and take action, drop-in replacements for textareas with AI-assisted text generation, and in-app agents that can access real-time application context and take action within the application.

Expert in biology, always ready to clarify new stem cell treatments.biomedical research, clinical trials. Learn about different stem cell types, current/future uses, and the latest in research.

Expert in all aspects of spectral flow cytometry.

A world-class immunologist aiding students in understanding immunology.

An GPT that can generate cellular automata processes

Expert in SCLC research, focused on a specific paper and broader SCLC knowledge.

Expert on hydrogen production systems and the hydrogen economy.

生物化学领域的知识型助手，避免提供医学建议。

Analyzes participants from page 1 of Zoom .pdfs

24年3月期・第2四半期決算説明会に関するご質問に、第三者視点で回答いたします（ex.要点を教えて、新規事業の状況は？等々）。AIによる回答のため、あくまで目安としてご参照ください。より正確な情報はIRサイトより引用元資料をご参照ください。 https://writeup.jp/ir/

Everything about water-fuelled car

General Information Gatherer

Explains Arxiv papers with examples, analogies, and direct PDF links.

Your AI research aide for the latest in ML.

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Your go-to source for well-researched information!

Spot emerging trends in the latest social science research ( (also see, just "Research Radar" for all disciplines))

Teaches and analyzes research methods with in-depth, academic insights.

Expert AI research question assistant.

Faster, smarter scientific advancement.

Designed to Provide Comprehensive Insights from the AI industry from Reputable Sources.