Search Results for "ai data analyst"
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Showing 26 open source projects for "ai data analyst"
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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Dify
One API for plugins and datasets, one interface for prompt engineering
...Out-of-the-box web sites supporting form mode and chat conversation mode A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort Visual data analysis, log review, and annotation for applications -
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OpenClaude
Claude Code opened to any LLM
OpenClaude is an open-source alternative or extension inspired by Claude-style agent systems, designed to provide similar capabilities in a customizable and self-hosted environment. The project focuses on enabling users to run their own AI agents with full control over data, workflows, and integrations, reducing reliance on proprietary platforms. It likely includes support for executing tasks, managing context, and interacting with external tools, allowing agents to perform real-world actions beyond simple text generation. The architecture emphasizes flexibility, enabling developers to adapt the system to different use cases and integrate it with various models or APIs. ... -
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Langflow
Low-code app builder for RAG and multi-agent AI applications
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database. -
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Pluely
The Open Source Alternative to Cluely
...By providing a modular architecture for building AI pipelines, the platform enables developers to connect multiple processing steps such as data retrieval, prompt execution, analysis, and response generation. The project emphasizes flexibility, allowing developers to extend the platform with custom integrations and automation logic. This makes the framework suitable for building intelligent assistants, automated business workflows, and data-processing pipelines that rely on generative AI capabilities. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Quivr
Your Second Brain supercharged by Generative AI
Quivr, your second brain, utilizes the power of GenerativeAI to store and retrieve unstructured information. Think of it as Obsidian, but turbocharged with AI capabilities. -
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Eidos
An extensible framework for Personal Data Management
...Unlike cloud-based knowledge tools, Eidos runs entirely on the user’s machine, ensuring privacy and high performance through local storage. The platform integrates large language models to enable AI-assisted features such as summarizing documents, translating content, and interacting with stored data conversationally. It also includes an extension system that allows developers to create custom tools, scripts, and workflows using programming languages such as TypeScript or Python. -
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dataline
AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake
dataline is an open-source AI data analysis and visualization platform that allows users to interact with datasets using natural language. The system enables both technical and non-technical users to explore data by asking questions conversationally, which the platform translates into database queries and analytical operations. It supports connections to multiple structured data sources such as PostgreSQL, MySQL, Snowflake, SQLite, Excel files, CSV datasets, and other database systems. ... -
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Nanocoder
A beautiful local-first coding agent running in your terminal
Nanocoder is an open-source, local-first coding assistant that runs in the command line and allows developers to use AI models to assist with programming tasks directly from their terminal environment. The tool is designed as a privacy-focused alternative to proprietary AI coding assistants, allowing users to run local models or connect to external APIs while keeping full control over their data and development workflow. Built with TypeScript and distributed as a CLI application, nanocoder enables developers to interact with AI agents that can read files, modify code, execute commands, and assist with debugging tasks. ... -
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LangWatch
The platform for LLM evaluations and AI agent testing
...Through integration with popular AI development frameworks, LangWatch can be embedded directly into AI pipelines to provide continuous monitoring and evaluation. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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MCP Router
A Unified MCP Server Management App (MCP Manager)
MCP Router is an open-source management platform designed to simplify the deployment and coordination of Model Context Protocol (MCP) servers used by AI agents. MCP is an emerging standard that allows language models and AI assistants to connect to external tools, data sources, and services through a structured interface. The MCP Router project acts as a centralized manager that helps developers run, configure, and coordinate multiple MCP servers within a single environment. This enables AI applications to access multiple tools and knowledge sources through a unified interface rather than connecting to each service individually. ... -
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HyperAgent
AI Browser Automation
...Built on top of Playwright, the framework allows developers to automate complex browser interactions using natural language commands rather than fragile selectors or hard-coded scripts. Instead of manually writing logic for clicking elements, extracting data, or navigating web pages, developers can instruct the agent in plain language and allow the AI layer to interpret and execute the task. This approach reduces the brittleness commonly associated with traditional automation scripts that break when the DOM structure changes. HyperAgent includes APIs such as page.ai() and page.extract() that allow structured data extraction and dynamic task execution through AI reasoning. -
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BuildingAI
Build your own AI application system for free
BuildingAI is an open-source project focused on applying artificial intelligence techniques to architectural design and building information modeling workflows. The platform aims to bridge the gap between natural language interfaces and building design tools by allowing AI systems to interpret user instructions and convert them into structured architectural operations. By combining generative AI capabilities with building data models, the system can assist with tasks such as design generation, spatial reasoning, and building component creation. The project is intended for architects, engineers, and developers exploring how AI can automate or augment design workflows in the architecture, engineering, and construction industries. ... -
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DevDocs by CyberAGI
Completely free, private, UI based Tech Documentation MCP server
...This approach reduces token usage and improves the accuracy of responses generated by AI coding assistants. The platform is designed to integrate easily with modern developer tools and AI environments such as Cursor, Cline, and Claude-based workflows. It includes a user interface that allows developers to browse documentation repositories and connect them to AI systems while keeping the data private. -
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BrowserNode
Make websites accessible for AI agents. Automate tasks online
Browsernode is an open-source TypeScript framework that allows AI agents to interact directly with web browsers in order to automate tasks and gather information from websites. The project acts as a bridge between AI models and browser automation tools, enabling language models to control web pages programmatically. Built as an implementation compatible with the Browser-use ecosystem, Browsernode allows agents to perform actions such as navigating pages, extracting information, filling... -
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LLMChat
Unified interface for AI chat, Agentic workflows and more
...One of its primary goals is to support sophisticated research workflows that combine conversational AI with information retrieval and reasoning tools. The platform includes specialized interaction modes such as deep research analysis and enhanced search capabilities that help users explore complex topics more effectively. It also incorporates agent-style workflows that allow the system to orchestrate multiple steps of reasoning or data retrieval during a conversation. -
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TaxHacker
Self-hosted AI accounting app. LLM analyzer for receipts
...It integrates large language models to analyze these documents, extract relevant financial information, and categorize expenses or income based on configurable rules. Users can deploy the application on their own infrastructure, ensuring that financial data remains private and under their control rather than being processed by external services. The software provides tools for tracking income streams, monitoring expenses, and organizing financial records in a structured format. Because the system supports customizable prompts and categories, users can adapt the AI analysis to match their accounting workflows or tax requirements. -
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POML
Prompt Orchestration Markup Language
POML, or Prompt Orchestration Markup Language, is a structured markup language created to improve the organization and maintainability of prompts used in large language model applications. Traditional prompt engineering often relies on unstructured text, which can become difficult to manage as prompts grow more complex and incorporate dynamic data sources. POML addresses this issue by introducing an HTML-like syntax that allows developers to organize prompts into structured components such as roles, tasks, and examples. This structure enables prompts to be reused, modified, and versioned more easily within complex AI applications. The language also supports integration of multiple data types including documents, tables, and other external inputs that must be incorporated into prompts dynamically. ... -
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PasteGuard
Masks sensitive data and secrets before they reach AI
...PasteGuard supports two primary modes: mask mode, which anonymizes data and still uses external APIs; and route mode, which forwards sensitive requests to a local LLM inference engine while sending the rest to the cloud. It can be self-hosted via Docker, works with a wide range of SDKs and tools, and includes a browser extension for automatic protection in everyday AI chats. -
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Reader LLM
Convert any URL to an LLM-friendly input with a simple prefix
Reader LLM is an open-source tool designed to convert web content into formats that are easier for large language models to process. The system works by transforming a webpage into a clean text or Markdown representation that removes unnecessary formatting and highlights the core information within the page. Developers can use a simple URL prefix to retrieve a version of a webpage that has been optimized for machine consumption, making it suitable for use in AI agents or retrieval-augmented... -
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Flock
Flock is a workflow-based low-code platform for building chatbots
Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on... -
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wllama
WebAssembly binding for llama.cpp - Enabling on-browser LLM inference
...The library leverages WebAssembly SIMD capabilities to achieve efficient execution within modern browsers while maintaining compatibility across platforms. By running models locally on the user’s device, wllama enables privacy-preserving AI applications that do not require sending data to remote servers. The framework provides both high-level APIs for common tasks such as text generation and embeddings, as well as low-level APIs that expose tokenization, sampling controls, and model state management. -
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Token-Oriented Object Notation
Token-Oriented Object Notation (TOON)
Token-Oriented Object Notation is an open specification and toolkit for a data serialization format called Token-Oriented Object Notation (TOON), designed specifically to optimize how structured data is passed to large language models. The format aims to reduce token overhead compared with traditional formats like JSON while remaining human-readable and structurally expressive. TOON represents the same data model as JSON but removes unnecessary syntax such as braces and quotes, relying... -
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OmniRoute
OmniRoute is an AI gateway for multi-provider LLM
OmniRoute is a routing and orchestration framework designed to simplify the handling of requests, workflows, or data flows across multiple services or endpoints in a unified manner. It focuses on providing a flexible abstraction layer where developers can define routing logic that dynamically directs traffic based on conditions, context, or predefined rules. The project emphasizes modularity and extensibility, allowing users to plug in different services or handlers without tightly coupling... -
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TONL
TONL (Token-Optimized Notation Language)
TONL is a cutting-edge data platform built around a production-ready serialization format designed to be both compact and powerful, combining human readability with performance features that make it suitable for large-scale applications and AI workflows. It provides a serialization format that significantly reduces token usage compared with traditional JSON, which can result in lower costs and more efficient prompt size utilization in LLM-driven systems. -
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AWS GenAI LLM Chatbot
A modular and comprehensive solution to deploy a Multi-LLM
...A major part of the design is its RAG layer, which enables the chatbot to pull contextual knowledge from connected data sources so responses can be grounded in enterprise content rather than relying only on model memory.
