AI agents directory for data scientists: Access solutions verified by top AI agency partners and automation specialists.

AI Agents for data scientists | AI Agent Store

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.

AutoML-Agent is an open-source multi-agent framework that uses LLMs to automate the full ML pipeline—from data ingestion to model deployment. Designed for diverse data modalities, it decomposes tasks across specialized agents (e.g. prompt, data, model, operation), with retrieval‑augmented planning and multi-stage verification to ensure robust and deployable model solutions.

AutoML-Agent

automl-agent

Open-source multi-agent LLM framework for end-to-end automated machine learning pipelines.

Jina AI is an open‑source platform (founded 2020) offering modular AI tools for building neural search, RAG and agentic applications. Its Search Foundation includes embeddings, rerankers, Reader, DeepSearch, classifiers, segmenters, and AgentChain orchestration to support complex multimodal retrieval and reasoning.

Jina AI

jina-ai

A multimodal search foundation platform powering embeddings, rerank, classification & RAG workflows.

MiniMax‑M1 is an open‑weight, hybrid Mixture‑of‑Experts large language model offering natively a 1 million token context window. It uses lightning attention and efficient RL training (CISPO) to excel at long-context reasoning, tool-use, coding, and mathematics. Released under Apache 2.0, it supports structured function calling and is deployable via vLLM, Transformers, or API.

MiniMax‑M1

minimax-m1

Open‑source large‑scale reasoning model with 1 million token context and hybrid Mixture‑of‑Experts architecture.

Perplexity Labs is an AI-powered project engine available to Pro subscribers. It handles complex tasks—like research, code execution, chart/image generation, dashboards, and mini web apps—by performing self‑supervised workflows (~10 min) that combine deep browsing, code, and assets tailored to user prompts.

Perplexity Labs

perplexity-labs

A productivity engine that builds full projects—reports, dashboards, code, mini‑apps—through AI‑powered autonomous workflows.

Chroma is an open-source, AI-native vector database built for storing and querying embeddings alongside metadata. It supports full‑text and multimodal search, scalable retrieval, and powers retrieval‑augmented generation workflows. Available as both a local SDK and a private‑preview managed cloud, Chroma offers strong developer ergonomics and extensible integrations for building production‑grade LLM applications.

Chroma

chroma

An open‑source vector database and embeddings engine for building retrieval‑augmented AI applications.

Pinecone is a fully managed vector database designed to support high-performance AI applications by enabling real-time semantic search and retrieval. It provides a serverless infrastructure that scales automatically, allowing developers to build and deploy AI-powered solutions without managing complex infrastructure. Pinecone supports features like hybrid search, metadata filtering, and real-time indexing, making it ideal for applications such as recommendation systems, chatbots, and knowledge bases. Its integration capabilities with various cloud providers and AI frameworks streamline the development of intelligent, context-aware applications.

Pinecone

pinecone

A fully managed vector database enabling scalable, real-time semantic search for AI applications.

EasyFin AI is an advanced financial analysis platform that leverages artificial intelligence to automate investment research. It processes complex financial data, including U.S. market financials, earnings calls, and economic indicators, transforming them into actionable insights. With features like interactive dashboards, customizable charts, and backtesting tools, EasyFin enables investors to make data-driven decisions efficiently. The platform also provides curated research from top investment banks and tracks institutional activities, offering a comprehensive suite for portfolio optimization and risk management.

EasyFin AI

easyfin-ai

AI platform for automating financial research, offering real-time analysis and predictive insights for smarter investments.

AlphaEvolve is an evolutionary AI coding agent developed by Google DeepMind, designed to autonomously discover and optimize complex algorithms across various domains. Leveraging the capabilities of Gemini 2.5 Flash and Pro models, AlphaEvolve employs an ensemble approach that balances computational throughput with solution quality. It utilizes an evolutionary framework where large language models generate candidate algorithms, which are then evaluated and refined through automated processes. This system has achieved notable successes, including surpassing the 56-year-old Strassen algorithm for matrix multiplication and optimizing data center scheduling, leading to significant efficiency gains. AlphaEvolve's ability to generate provably novel and correct algorithms marks a significant advancement in AI-driven scientific discovery.

AlphaEvolve

alphaevolve

A Gemini-powered AI coding agent that autonomously discovers and optimizes complex algorithms.

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.

Agent Network Protocol (ANP) is an open-source communication protocol designed to facilitate secure, decentralized interactions among AI agents. It aims to become the 'HTTP of the Agentic Web Era' by providing a standardized framework that enables agents to connect, communicate, and collaborate efficiently. ANP's architecture comprises three layers: the Identity Layer for decentralized authentication using W3C DID standards, the Meta-Protocol Layer for dynamic protocol negotiation, and the Application Layer for semantic-based capability descriptions. This structure ensures interoperability, scalability, and secure communication across diverse AI systems.

Agent Network Protocol

agent-network-protocol

An open-source protocol enabling secure, decentralized communication among AI agents.