Anything

Automation & Agents , Developer Tools , Workflow

An open-source visual workflow builder for AI agents that prioritizes local execution and ease of use over the complex enterprise governance found in legacy automation tools.

Excellent for developers prototyping agentic workflows locally, weaker for teams requiring a massive library of pre-built third-party integrations.

Ai Agents Autonomous Agents Open-Source Workflow Automation No-Code Llm Api Developer Productivity

Analysis based on product data, pricing structure, traffic signals, and public user sentiment.

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Who Should Use Anything?

Typical users

Developers, technical product managers, and AI hobbyists who want to build autonomous workflows without writing boilerplate glue code.

Maturity fit

beginner to scaling

Choose this if…

You want to run agents locally to maintain data privacy
Your priority is a visual interface for mapping LLM logic
You need to switch between different LLM providers like OpenAI, Anthropic, or local models via Ollama

Skip this if…

You require thousands of niche SaaS integrations available in Zapier or Make
Your workflow requires complex state management that visual nodes struggle to represent
You need enterprise-grade SOC2 compliance and advanced user permissioning

About Anything

Anything is an open-source platform for building and deploying autonomous AI agents through a visual interface. It bridges the gap between raw LLM APIs and finished automation by providing a node-based environment where users can connect models to tools and data sources.

What it actually does

Users drag and drop nodes to define how an AI agent should think and act. It allows for the creation of 'skills'—reusable pieces of logic—and the deployment of these agents as standalone applications or integrated bots.

What makes it different

Unlike many cloud-only agent builders, Anything emphasizes a local-first approach and open-source transparency. It allows for a tighter feedback loop during development by letting users run the entire stack on their own hardware via Docker.

Visual node-based workflow editor Local model support via Ollama integration Multi-provider LLM support (OpenAI, Anthropic, Groq) Custom tool and skill creation Docker-based self-hosting Agent marketplace for pre-configured templates API-based agent triggering

Key Features

Visual Flow Builder

Simplifies the construction of multi-step agentic logic without writing Python scripts.

Local-First Architecture

Enables development and execution on local machines to ensure data never leaves your infrastructure.

Provider Agnostic

Allows swapping between GPT-4, Claude 3, and Llama 3 without rebuilding the entire workflow.

Skill System

Packages complex API calls or logic into reusable blocks that can be shared across different agents.

Marketplace Templates

Provides a starting point for common tasks like web scraping, document analysis, or social media automation.

One-Click Deployment

Moves agents from a local development environment to a hosted cloud instance with minimal configuration.

Pricing

Self-Hosted

Free

Full access to open-source code
Unlimited local agents
Local model support
Community support

Popular

Cloud Beta

Free

Hosted agent execution
Managed infrastructure
Early access to new features
Limited execution credits

Pricing checked 5 months ago

Pricing guidance

Best plan for most users: The Self-Hosted plan is the best choice for most users as it offers the full feature set without usage limits, provided you have the hardware to run it.

Free plan enough? Yes, the open-source version is fully functional and sufficient for anyone comfortable with Docker.

Upgrade when:

When you need 24/7 hosted execution without managing your own server
When you need to share agents with team members via a web URL
When you want to offload the compute costs of running local models

Watch out for:

Cloud beta may have unannounced rate limits on execution
Third-party LLM costs (OpenAI/Anthropic) are always separate
Self-hosting requires technical knowledge of Docker and networking

Aggressively open-source and free-to-start, following a classic 'open core' or 'hosted' monetization strategy.

Pros & Cons

Strengths

Low barrier to entry for complex agents
The visual interface makes it significantly easier to visualize how an agent processes information compared to managing long-form JSON or Python configurations.
Privacy-centric development
By supporting local LLMs and self-hosting, it caters to users who cannot use cloud-based AI tools due to strict data privacy requirements.
Flexible model routing
Users can use cheaper models for simple logic steps and reserve expensive models like GPT-4 for the final reasoning, optimizing operational costs.

Weaknesses

Limited integration ecosystem
Compared to established players like Zapier, the number of native third-party app connectors is small, often requiring manual API configuration.

Affects: Users looking for 'plug-and-play' connectivity with niche SaaS tools.
Early-stage stability issues
As an evolving open-source project, users report occasional UI bugs and breaking changes in the node configurations.

Affects: Production-critical workflows that require 99.9% uptime.
Steep learning curve for non-technical users
While visual, understanding concepts like 'system prompts', 'temperature', and 'API schemas' is still necessary to build anything useful.

Affects: Non-technical business users expecting a 'magic' solution.

Real User Sentiment

Generally positive among developers who appreciate the clean UI and local-first philosophy, though some find the feature set sparse compared to older automation tools.

Users tend to like

Clean and intuitive visual interface
Ease of setting up local models via Ollama
Open-source transparency
Quick deployment of agents as APIs

Users commonly complain about

Lack of deep integrations with common business apps
Occasional UI lag when handling complex flows
Documentation can be thin for advanced use cases

Recurring tradeoffs

Users trade the massive integration library of Zapier for the deep AI customization and privacy of a local-first tool.

Happiest users

Developers building custom AI internal tools who want to avoid high monthly SaaS fees and keep data local.

Often frustrated

Marketing or operations staff who expect a 'no-code' experience similar to Zapier but find themselves needing to understand API documentation.

Use Cases

Local Document Analysis

Building an agent that reads local PDFs and answers questions without uploading them to a cloud provider.

Automated Content Research

Creating a flow that scrapes specific websites, summarizes findings, and drafts a report.

Customer Support Triaging

An agent that monitors an API endpoint and categorizes incoming requests using an LLM.

Personal Assistant Bot

A locally hosted agent that manages personal tasks and integrates with a private calendar via API.

Developer Onboarding Tool

An agent trained on internal documentation to help new hires find code snippets and architectural info.

Frequently Asked Questions

Is Anything actually free?

Yes, the core platform is open-source and free to self-host using Docker. You only pay if you choose to use their managed Cloud service or if you use paid LLM APIs like OpenAI. If you use local models via Ollama, the entire stack can run at zero cost.

How does Anything compare to LangFlow or Flowise?

Anything focuses on a more streamlined, user-friendly experience with a focus on 'agents' rather than just 'chains'. While LangFlow and Flowise offer more granular control over every single LLM parameter, Anything is generally faster to set up for standard agentic workflows.

Can I use local models with Anything?

Yes, Anything has native support for Ollama. This allows you to run models like Llama 3 or Mistral entirely on your own machine, ensuring that your data never leaves your local environment, which is a major advantage for privacy-conscious users.

What are the main limitations of the platform?

The primary limitation is the integration library. Unlike Zapier, which has thousands of apps, Anything requires you to manually configure API nodes for many services. It also lacks advanced multi-user permissioning and enterprise audit logs in its current state.

Do I need to know how to code to use Anything?

While it is a visual 'no-code' builder, you still need a technical mindset. You will need to understand how APIs work, how to structure prompts, and how to manage JSON data. It is 'low-code' in practice rather than 'no-code' for beginners.

Can I deploy my agents as a standalone website?

Anything allows you to share agents via a public link or integrate them into other applications via an API. While it doesn't build a full custom website for you, it provides the backend infrastructure to power one.

Why trust this page?

This evaluation combines product positioning, pricing analysis, traffic and market signals, and public user sentiment into a single decision-support page. Content is generated editorially — not copied from the vendor's website.

Funding & Company

Founded

2021

Stage

Series a

Total Raised

$19.5M

Latest Round

Series A (Sep 2025)

Notable Investors

Footwork Ventures Bessemer Venture Partners M13 Uncork Capital Tobi Lütke

Anything has raised a total of $19.5 million over two rounds, including a recent $11 million Series A in September 2025. This funding, from notable investors like Bessemer Venture Partners and Footwork Ventures, is aimed at scaling its AI-powered app development platform and supporting rapid user growth.

Full funding report high confidence

Market Signals & Traffic

Estimated visits, global rank, geography, traffic sources, monthly visit trends, and organic search keywords (Similarweb)—on a dedicated page built for depth and search.

Estimated visits: 0
Global rank: —
Snapshot: Apr 2026
Traffic trend: —