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AI-native development platform / AI-first software stack

Ranking updated Jun 30, 2026

For a directory of ai native companies, the strongest matches are pewdiepie-archdaemon/odysseus (Odysseus is a self-hosted AI workspace and autonomous agent), hsliuping/tradingagents-cn (TradingAgents-CN is a multi-agent framework that uses LLMs for) and foundationagents/metagpt (MetaGPT is an AI-first multi-agent orchestration framework that automates). cloudwego/eino and run-llama/llama_index round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.

We curate open-source GitHub repositories matching “ai native companies”. Results are ranked by relevance to your query — pick filters below to narrow, or refine with AI.

Results for “a directory of ai native companies”

Find the best repos with AI.We'll search the best matching repositories with AI.
  • pewdiepie-archdaemon/odysseuspewdiepie-archdaemon avatar

    pewdiepie-archdaemon/odysseus

    72,184View on GitHub↗

    Odysseus is a self-hosted AI workspace and autonomous agent framework designed for deploying and managing large language models. It serves as a centralized platform for orchestrating agentic tasks, utilizing a model context protocol server to connect AI models to external system utilities, browser automation, and local hardware. The system distinguishes itself through a combination of retrieval-augmented generation and a RAG knowledge base, using vector stores and local embeddings to provide persistent semantic memory. It further integrates AI-driven communication management to triage email i

    Odysseus is a self-hosted AI workspace and autonomous agent framework that directly provides AI agent orchestration, retrieval-augmented generation with vector stores, model serving for LLMs, and API abstraction via a model context protocol server — squarely matching the AI-native development platform intent with comprehensive coverage of the requested features.

    PythonLarge Language Model ConnectorsModel ServingRetrieval Augmented Generation
    View on GitHub↗72,184
  • hsliuping/tradingagents-cnhsliuping avatar

    hsliuping/TradingAgents-CN

    17,494View on GitHub↗

    TradingAgents-CN is a multi-agent framework designed for autonomous financial market analysis and automated trading execution. It functions as a containerized orchestrator that leverages large language models to perform complex reasoning, research, and decision-making tasks within financial environments. The platform distinguishes itself through a modular architecture that integrates diverse artificial intelligence providers and financial data sources into a unified pipeline. It provides granular control over agent behavior through prompt-driven logic configuration and multi-model orchestrati

    TradingAgents-CN is a multi-agent framework that uses LLMs for autonomous trading, making it an AI-native platform with agent orchestration and model integration—it fits the search for AI-first software stacks, though it is specialized for financial markets rather than general-purpose AI development.

    PythonAI Agent OrchestratorsLarge Language Model ConnectorsLLM Provider Integrations
    View on GitHub↗17,494
  • foundationagents/metagptFoundationAgents avatar

    FoundationAgents/MetaGPT

    68,844View on GitHub↗

    MetaGPT is an agentic workflow engine and multi-agent orchestration framework designed to automate complex software engineering and data analysis tasks. It functions as an automated software factory that transforms high-level natural language requirements into functional web applications, technical documentation, and production-ready code. By utilizing a runtime environment that manages the lifecycle of specialized agents, the platform bridges the gap between user intent and finished software components. The system distinguishes itself through role-based agent orchestration and dynamic task d

    MetaGPT is an AI-first multi-agent orchestration framework that automates software engineering and data analysis tasks using role-based agents and LLM integration, making it a relevant AI-native development tool, though it focuses on agent orchestration rather than the full set of features like RAG or model serving.

    PythonAI AgentAI Agent Orchestrators
    View on GitHub↗68,844
  • cloudwego/einocloudwego avatar

    cloudwego/eino

    9,675View on GitHub↗

    Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

    Eino is an AI agent development kit and LLM application framework with graph-based orchestration, multi-agent coordination, and LangChain integration, making it a comprehensive AI-first infrastructure piece that AI-native companies rely on for building autonomous workflows.

    GoAI AgentAI Agent OrchestratorsMulti-Agent Systems
    View on GitHub↗9,675
  • run-llama/llama_indexrun-llama avatar

    run-llama/llama_index

    50,306View on GitHub↗

    LlamaIndex is a comprehensive development framework designed to connect private or external data sources to large language models. It functions as a data-centric toolkit that enables the construction of retrieval-augmented generation systems, allowing developers to build applications that provide context-aware answers based on specific organizational information. The project distinguishes itself through a robust agentic orchestration engine that supports the creation of autonomous agents capable of multi-step reasoning, memory management, and complex tool execution. Beyond simple retrieval, i

    LlamaIndex is a comprehensive AI-native framework that connects data to LLMs, enabling retrieval-augmented generation and agent orchestration, which directly serves the stack that AI-first companies build on.

    PythonMulti-Agent Systems
    View on GitHub↗50,306
  • nirdiamant/agents-towards-productionNirDiamant avatar

    NirDiamant/agents-towards-production

    17,375View on GitHub↗

    This project is a comprehensive framework for developing, orchestrating, and deploying autonomous agents. It provides a structured environment for building agents that utilize reasoning loops to perform multi-step tasks, manage state through graph-based workflows, and interact with external tools. By mapping unstructured model outputs into typed schemas, the framework ensures reliable integration with downstream application logic. The platform distinguishes itself through a focus on production-grade reliability and security. It incorporates hybrid memory systems that combine vector embeddings

    This is a focused open-source framework for developing, orchestrating, and deploying autonomous agents with production-grade reliability, fitting the AI-native platform category, but it primarily targets agent orchestration rather than encompassing the full stack of features like model serving and data pipelines.

    Jupyter NotebookAI AgentRetrieval Augmented GenerationRetrieval-Augmented Generation
    View on GitHub↗17,375
  • ed-donner/agentsed-donner avatar

    ed-donner/agents

    4,017View on GitHub↗

    This project is an LLM autonomous agent framework and orchestration tool designed to build goal-driven agents that automate complex workflows. It functions as a system for converting high-level objectives into a series of autonomous actions and managing the coordination of multiple specialized agents to solve multi-step problems. The framework features a tool integration layer that parses structured model outputs into executable functions and external API calls. It utilizes a non-blocking execution pipeline to manage task orchestration through recursive loops and asynchronous event handling.

    This repository is an autonomous agent orchestration framework that specializes in building goal-driven AI agents with tool integration and asynchronous task management, directly covering AI agent orchestration and LLM integration, but it does not include retrieval-augmented generation, model serving, or data pipeline features, so it is a genuine AI-first tool but not a comprehensive platform.

    Jupyter NotebookAI Agent OrchestratorsMulti-Agent Systems
    View on GitHub↗4,017
  • gsd-build/get-shit-donegsd-build avatar

    gsd-build/get-shit-done

    64,457View on GitHub↗

    This project is an autonomous software development assistant and project management tool that utilizes a multi-agent orchestrator to automate complex workflows. It functions as an agentic framework designed to research, plan, execute, and verify software development tasks by coordinating specialized agents that manage context windows and system performance. The system distinguishes itself through a structured, interview-based requirement engineering phase that clarifies project objectives before initiating automated work. It employs atomic task decomposition to break goals into independent un

    This project is an AI-native agentic framework that orchestrates multiple AI agents to automate software development workflows, making it a relevant tool for AI-first companies, though it focuses on agent orchestration rather than covering the full platform stack like model serving or data pipelines.

    JavaScriptAI Agent OrchestratorsMulti-Agent Systems
    View on GitHub↗64,457
  • alirezarezvani/claude-skillsalirezarezvani avatar

    alirezarezvani/claude-skills

    18,240View on GitHub↗

    This project is a framework for integrating modular instruction packages and domain-specific tools into large language model agents. It provides a system for managing agent context and extending coding assistants through a modular prompt library of persona-based instruction sets and skill trees. The framework distinguishes itself through a persistent memory layer that tracks architectural decisions and infrastructure patterns to prevent regressions during autonomous code modifications. It includes an orchestrator for managing multi-agent swarms and autonomous coding loops that cycle through g

    This repository is a framework for building modular, orchestrated AI agents with persistent memory and multi-agent swarms, squarely fitting the AI-native development platform category, though it is specialized for coding assistants and does not cover the full stack of model serving or data pipelines.

    PythonAI Agent OrchestratorsMulti-Agent Systems
    View on GitHub↗18,240
  • kilo-org/kilocodeKilo-Org avatar

    Kilo-Org/kilocode

    15,616View on GitHub↗

    Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

    Kilocode is an open-source autonomous engineering platform purpose-built for orchestrating AI agents on complex development tasks—it directly matches the AI-first tooling and LLM orchestration you're looking for, even though it does not emphasise retrieval-augmented generation or a dedicated feature store.

    TypeScriptAI Agent Orchestrators
    View on GitHub↗15,616
  • all-hands-ai/openhandsAll-Hands-AI avatar

    All-Hands-AI/OpenHands

    77,468View on GitHub↗

    OpenHands is an autonomous AI software engineer and coding assistant designed to execute software engineering tasks by interacting directly with codebases and development environments. It functions as a platform for running AI agents that can write code and manage files to automate complex development workflows. The system distinguishes itself through a container-based execution environment that isolates agent actions within a sandboxed Linux environment. It employs an autonomous agent loop of observation, planning, and action, supported by a standardized communication protocol that allows it

    OpenHands is an AI-native autonomous coding agent platform with agent orchestration and LLM integration, fitting the AI-first development tool category despite focusing on software engineering rather than a broader AI stack.

    PythonAI Agent OrchestratorsLLM Model Integrations
    View on GitHub↗77,468
  • microsoft/semantic-kernelmicrosoft avatar

    microsoft/semantic-kernel

    27,262View on GitHub↗

    Semantic Kernel is an artificial intelligence orchestration framework designed to integrate large language models with existing codebases. It functions as an agentic workflow engine, providing a standardized interface that connects generative models to traditional application logic, data sources, and external tools to automate complex, multi-step business tasks. The platform distinguishes itself through a modular plugin architecture and a planner-based reasoning engine that decomposes high-level goals into executable sequences of functions. By utilizing a connector-based abstraction layer, it

    Semantic Kernel is an AI-first orchestration framework that directly supports AI agent orchestration, RAG through vector retrieval, and LLM integration via a modular plugin architecture — making it a comprehensive platform for building AI-native applications.

    C#Agent Orchestration FrameworksAI Orchestration FrameworksModel Abstraction Layers
    View on GitHub↗27,262
  • langchain-ai/langchainlangchain-ai avatar

    langchain-ai/langchain

    139,458View on GitHub↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

    LangChain is a battle-tested orchestration framework for LLM-powered applications, directly covering agent orchestration, RAG, model serving integrations, and LLM API abstraction — the key pieces of an AI-native development stack.

    PythonAgent Orchestration FrameworksLLM Application OrchestrationLLM Integration Layers
    View on GitHub↗139,458
  • fetchai/innovation-lab-examplesfetchai avatar

    fetchai/innovation-lab-examples

    1,028View on GitHub↗

    This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a decentralized network. It serves as a collection of patterns and examples for developing intelligent software entities capable of performing complex tasks, making decisions, and interacting with other agents to achieve shared goals. The framework distinguishes itself through its focus on multi-agent orchestration and decentralized communication. It enables the coordination of specialized agent teams that collaborate on workflows through structured messaging protocols, allowing

    This repository provides a framework and examples for building and orchestrating autonomous AI agents in a decentralized network, which fits the AI-native agent orchestration part of the stack—but it does not cover the other required capabilities like RAG, model serving, or LLM abstraction, making it a partial rather than comprehensive answer.

    PythonLarge Language Model ConnectorsRetrieval Augmented GenerationMulti-Agent Systems
    View on GitHub↗1,028
  • hkuds/deepcodeHKUDS avatar

    HKUDS/DeepCode

    14,539View on GitHub↗

    DeepCode is an agentic development framework designed to orchestrate autonomous AI agents for software engineering tasks. It functions as a multi-agent workflow orchestrator that translates natural language requirements into functional codebases by coordinating specialized agents for architectural planning, intent analysis, and implementation. The platform integrates multiple language models to power these automated routines, providing a unified environment for complex development projects. The system distinguishes itself through its ability to transform academic research papers into executab

    DeepCode is an agentic development framework orchestrating autonomous AI agents with LLM integration for software tasks, squarely an AI-first platform, though it focuses on agent orchestration and code generation rather than covering all listed features like RAG or model serving.

    PythonAI Agent OrchestratorsLarge Language Model Connectors
    View on GitHub↗14,539
  • katanemo/planokatanemo avatar

    katanemo/plano

    5,120View on GitHub↗

    Plano is an AI agent orchestrator and LLM gateway proxy that unifies access to multiple AI providers through a single interoperable interface. It functions as a model routing engine that decouples applications from specific vendors using semantic aliases, allowing traffic to be shifted between providers without modifying application code. The system distinguishes itself with intent-based agent routing, which directs prompts to specialized agents based on semantic analysis. It features an interceptor-based filter chain system that acts as guardrail middleware to enforce safety policies, rewrit

    Plano is an AI agent orchestrator and LLM gateway that routes prompts across providers with intent-based agent selection and guardrail middleware, making it a focused AI-native tool for orchestration and API abstraction, though it omits built-in RAG and data pipeline features.

    RustAgent OrchestrationAI Agent Orchestrators
    View on GitHub↗5,120
  • langroid/langroidlangroid avatar

    langroid/langroid

    3,894View on GitHub↗

    Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist

    Langroid is a multi-agent orchestration framework with built-in retrieval-augmented generation and LLM integration, fitting the AI-native platform category by providing core tools for building AI-first applications.

    PythonAgent OrchestrationAI Agent OrchestratorsRetrieval Augmented Generation
    View on GitHub↗3,894
  • camel-ai/camelcamel-ai avatar

    camel-ai/camel

    17,253View on GitHub↗

    This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

    camel-ai/camel is a framework built AI-first for orchestrating multi-agent systems with LLM integration and tool abstraction, which squarely fits the requested category of AI-native development platforms, though it focuses on agent orchestration rather than covering every listed feature like RAG and model serving.

    PythonLLM Provider IntegrationsMulti-Agent SystemsMulti-Agent Systems
    View on GitHub↗17,253
  • letta-ai/lettaletta-ai avatar

    letta-ai/letta

    21,168View on GitHub↗

    Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

    Letta is an open-source framework for building and deploying autonomous AI agents with persistent memory and retrieval-augmented generation, directly addressing the AI-native stack with agent orchestration and LLM integration, though it does not cover the full data pipeline and feature store aspects of the query.

    PythonAI AgentLLM Provider IntegrationsRetrieval Augmented Generation
    View on GitHub↗21,168
  • crmne/ruby_llmcrmne avatar

    crmne/ruby_llm

    3,566View on GitHub↗

    ruby_llm is an LLM integration framework and AI agent orchestrator designed to connect applications to multiple large language model providers through a unified interface. It serves as a toolkit for building autonomous assistants with custom personas, managing structured output via JSON schemas, and implementing vector embedding engines for semantic search. The project distinguishes itself as an observability suite and multimodal toolkit. It provides specialized capabilities for tracking token usage, calculating model costs, and tracing workflows via OpenTelemetry, while supporting the proces

    ruby_llm is an LLM integration framework and AI agent orchestrator with unified API abstraction, embeddings for RAG, and observability — it covers several of the requested features as an AI-first toolkit, though it does not include model serving or a dedicated feature store.

    RubyLLM Integration Frameworks
    View on GitHub↗3,566
  • livekit/agentslivekit avatar

    livekit/agents

    9,379View on GitHub↗

    This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu

    livekit/agents is a framework for building real-time multimodal AI agents that see, hear, and speak, directly matching the search for AI-first tools with agent orchestration and LLM integration, though it lacks explicit RAG and feature store capabilities.

    PythonLarge Language Model ConnectorsLLM Provider Integrations
    View on GitHub↗9,379
  • ibm/mcp-context-forgeIBM avatar

    IBM/mcp-context-forge

    3,310View on GitHub↗

    mcp-context-forge is a Model Context Protocol federation gateway that unifies diverse AI tool servers and APIs into a single consistent interface for discovery and execution. It acts as a centralized proxy that aggregates multiple servers and APIs, allowing AI agents to access and invoke a unified set of tools, prompts, and resources. The project distinguishes itself through a multi-protocol translation bridge that converts communication between standard I/O, SSE, gRPC, and REST to enable interoperability between disparate tool servers. It includes a comprehensive LLM evaluation framework for

    ibm/mcp-context-forge is an AI-first gateway that unifies diverse AI tool servers and APIs via the Model Context Protocol, providing the kind of agent orchestration and LLM integration infrastructure native AI companies rely on.

    PythonAI Agent OrchestratorsLLM Provider Integrations
    View on GitHub↗3,310
  • stanfordnlp/dspystanfordnlp avatar

    stanfordnlp/dspy

    35,325View on GitHub↗

    DSPy is a declarative programming framework designed for building complex language model applications. It treats model interactions as modular, composable programs, allowing developers to define task logic through typed class schemas rather than relying on manually written prompts. By organizing workflows into hierarchical, reusable Python objects, the framework enables the construction of sophisticated AI systems that manage state and execution flow independently. The framework distinguishes itself through an automated optimization engine that iteratively refines prompt instructions and few-

    DSPy is a declarative programming framework for building language model applications with composable programs and automated optimization, fitting the AI-native development platform category by providing LLM integration and agent orchestration, though it does not directly include model serving or data pipeline features.

    PythonDeclarative AI FrameworksAgentic Orchestration FrameworksAI Signature Definitions
    View on GitHub↗35,325
  • cloudflare/vibesdkcloudflare avatar

    cloudflare/vibesdk

    5,094View on GitHub↗

    vibesdk is an agentic software development platform and framework designed to coordinate autonomous agents that write, debug, and refine full-stack applications from natural language. It serves as a cloud-native application orchestrator and an LLM-powered code generation framework that converts prompts into functional code through iterative conversations and multi-phase agent behaviors. The project distinguishes itself by providing a complete toolchain for building AI development platforms. This includes the ability to integrate various model providers, construct custom LLM toolkits, and mana

    VibeSDK is an agentic software development platform that coordinates autonomous AI agents to write and debug full-stack applications from natural language, directly matching the need for an AI-native platform with LLM integration and agent orchestration.

    TypeScriptAI Web Application BuildersFull-Stack Code GeneratorsSoftware Development Agents
    View on GitHub↗5,094
  • fosowl/agenticseekFosowl avatar

    Fosowl/agenticSeek

    26,529View on GitHub↗

    AgenticSeek is a multi-agent orchestration system designed to decompose complex user objectives into granular, actionable tasks. By coordinating a team of specialized autonomous workers, the platform manages end-to-end workflows, ensuring that each component of a project is assigned to the most capable agent for execution. The system operates as a local-first runtime, executing all artificial intelligence models directly on user hardware to maintain data sovereignty and privacy. It integrates a browser automation engine for autonomous web research and interaction, alongside a sandboxed enviro

    AgenticSeek is a local-first multi-agent orchestration system that decomposes tasks and coordinates LLM-powered agents, making it a fitting AI-native development platform—it covers agent orchestration and model serving well, though it does not explicitly address retrieval-augmented generation or feature stores.

    PythonAgentic Task OrchestratorsAutonomous Agent OrchestratorsBrowser Automation Engines
    View on GitHub↗26,529
  • insforge/insforgeInsForge avatar

    InsForge/InsForge

    11,794View on GitHub↗

    InsForge is a backend-as-a-service platform that provides an integrated suite of tools for managing relational databases, identity provision, object storage, and serverless compute. It functions as an open-source identity provider and a PostgreSQL database manager featuring integrated vector storage and row-level security. The platform serves as an LLM orchestration gateway, offering a unified endpoint to route requests across various AI providers through an OpenAI-compatible interface. It enables AI-driven application generation and connects AI agents to backend resources using a standardize

    InsForge is an open-source backend-as-a-service platform with an integrated LLM orchestration gateway, vector storage, and AI agent connectivity, making it a solid fit for building AI-native applications even though it may not cover every feature like a dedicated feature store.

    TypeScriptBackend-as-a-Service PlatformsDatabase ManagersRelational Data Storage
    View on GitHub↗11,794
  • microsoft/guidancemicrosoft avatar

    microsoft/guidance

    21,502View on GitHub↗

    Guidance is a control framework and generation orchestrator for large language models. It provides a programming layer to steer model outputs through structured templates, schema enforcement, and logical flow management. The framework distinguishes itself by interleaving model generation with local code execution, enabling the use of loops and conditional branching within a single session. It employs grammar-based token constraints and regular expressions to force models to sample only from tokens that satisfy a specific structural format, ensuring strict adherence to predefined data models.

    Guidance is an AI-first control framework and generation orchestrator for LLMs, providing structured output enforcement and logical flow management that fits the AI-native development stack, though it focuses on LLM integration rather than covering the full range of features like retrieval-augmented generation or data pipelines.

    Jupyter NotebookInterleaved Logic ExecutionGeneration Flow OrchestratorsGenerator-Based Flow Control
    View on GitHub↗21,502
  • langchain-ai/open-agent-platformlangchain-ai avatar

    langchain-ai/open-agent-platform

    1,859View on GitHub↗

    The Open Agent Platform is an orchestration environment for building, deploying, and managing autonomous AI agents. It provides a framework for constructing both single-task performers and complex multi-agent systems, utilizing a central supervisor pattern to coordinate collaborative workflows and task delegation. The platform distinguishes itself through a graph-based execution model that defines the sequence of logic and tool calls, paired with a visual configuration interface that allows for the creation of agent workflows without manual coding. It incorporates enterprise-grade security by

    This is an open-source, no-code agent building platform from the LangChain ecosystem, which directly provides AI agent orchestration and LLM integration—core to the AI-native development category, though it may not fully cover retrieval-augmented generation or dedicated data pipeline features.

    TypeScriptLLM Orchestration PlatformsAutonomous Agent OrchestrationMulti-Agent Coordination Systems
    View on GitHub↗1,859
  • dabit3/react-native-aidabit3 avatar

    dabit3/react-native-ai

    1,277View on GitHub↗

    This project is a full-stack development framework designed for building cross-platform mobile applications that integrate generative language and image models. It provides a pre-configured boilerplate and a collection of tools to accelerate the creation of intelligent software, including support for interactive chat interfaces and visual content generation. The framework distinguishes itself by incorporating a server-side proxy layer that centralizes authentication and authorization, ensuring secure communication when interacting with external AI services. It also features a modular styling

    This React Native framework is built AI-first for cross-platform mobile AI apps, integrating LLMs and streaming, which fits the category of an AI-native development platform; however, it lacks the broader enterprise features like agent orchestration, RAG, and model serving that the query's feature list specifies.

    TypeScriptCross-Platform FrameworksAPI Access SecurityAPI Proxy Layers
    View on GitHub↗1,277
  • first-fluke/oh-my-agentfirst-fluke avatar

    first-fluke/oh-my-agent

    1,086View on GitHub↗

    Oh-my-agent is a vendor-agnostic orchestration framework designed to manage autonomous agent teams and automate complex engineering workflows. It functions as a multi-agent development tool that synchronizes agent behavior, skills, and project-specific rules across diverse development environments and command-line interfaces. The platform distinguishes itself through configuration-based projection, which maintains a single source of truth for agent definitions that are mapped into various vendor-specific runtime formats. By utilizing cross-platform symlink bridging and a vendor-agnostic skill

    This repository is a portable, vendor-agnostic agent harness for orchestrating AI agent workflows and teams, making it a fitting tool for AI-native development platforms—though it focuses on agent orchestration rather than covering every feature like RAG or data pipelines.

    TypeScriptMulti-Agent OrchestratorsAgent Skill FrameworksAgentic Workflow Automation
    View on GitHub↗1,086
Compare the top 10 at a glance
RepositoryStarsLanguageLicenseLast push
pewdiepie-archdaemon/odysseus72.2KPythonAGPL-3.0Jun 16, 2026
hsliuping/tradingagents-cn17.5KPythonotherFeb 14, 2026
foundationagents/metagpt68.8KPythonMITJan 21, 2026
cloudwego/eino9.7KGoapache-2.0Feb 19, 2026
run-llama/llama_index50.3KPythonMITJun 20, 2026
nirdiamant/agents-towards-production17.4KJupyter NotebookotherFeb 17, 2026
ed-donner/agents4KJupyter NotebookmitFeb 15, 2026
gsd-build/get-shit-done64.5KJavaScriptMITMay 31, 2026
alirezarezvani/claude-skills18.2KPythonMITJun 12, 2026
kilo-org/kilocode15.6KTypeScriptapache-2.0Feb 19, 2026

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