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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Flowise is an open-source agentic development platform designed to help teams build AI agents and LLM-powered applications using a visual workflow interface. The platform allows users to design intelligent workflows through modular components that can be combined to create chatbots, automation systems, and autonomous AI agents. Developers can build both single-agent chat assistants and multi-agent systems that collaborate to complete complex tasks. Flowise integrates with more than 100 large language models, embedding models, and vector databases, providing flexibility in selecting AI technologies. The platform also supports retrieval-augmented generation (RAG), enabling applications to retrieve knowledge from documents and data sources. Built-in features such as human-in-the-loop workflows allow users to review and validate agent actions before execution. Observability tools provide detailed execution traces and compatibility with monitoring systems like Prometheus and OpenTelemetry. Developers can integrate Flowise with existing applications using APIs, SDKs, or embedded chat widgets. The platform supports both cloud and on-premises deployment environments for enterprise scalability. By providing visual tools and flexible integrations, Flowise accelerates the development and deployment of advanced AI-driven applications.

Description

Laminar is a comprehensive open-source platform designed to facilitate the creation of top-tier LLM products. The quality of your LLM application is heavily dependent on the data you manage. With Laminar, you can efficiently gather, analyze, and leverage this data. By tracing your LLM application, you gain insight into each execution phase while simultaneously gathering critical information. This data can be utilized to enhance evaluations through the use of dynamic few-shot examples and for the purpose of fine-tuning your models. Tracing occurs seamlessly in the background via gRPC, ensuring minimal impact on performance. Currently, both text and image models can be traced, with audio model tracing expected to be available soon. You have the option to implement LLM-as-a-judge or Python script evaluators that operate on each data span received. These evaluators provide labeling for spans, offering a more scalable solution than relying solely on human labeling, which is particularly beneficial for smaller teams. Laminar empowers users to go beyond the constraints of a single prompt, allowing for the creation and hosting of intricate chains that may include various agents or self-reflective LLM pipelines, thus enhancing overall functionality and versatility. This capability opens up new avenues for experimentation and innovation in LLM development.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Arize AI
Chroma
Claude Opus 4.6
Claude Opus 4.7
Claude Sonnet 4.6
Docker
GPT-5.4 mini
GPT-5.4 nano
GPT-5.5
GPT-5.5 Pro
Gemini 3.1 Pro
GitHub
Hugging Face
LangChain
Langfuse
Mazaal AI
Node.js
OpenAI
Opik
n8n

Integrations

Arize AI
Chroma
Claude Opus 4.6
Claude Opus 4.7
Claude Sonnet 4.6
Docker
GPT-5.4 mini
GPT-5.4 nano
GPT-5.5
GPT-5.5 Pro
Gemini 3.1 Pro
GitHub
Hugging Face
LangChain
Langfuse
Mazaal AI
Node.js
OpenAI
Opik
n8n

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$25 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Flowise AI

Founded

2023

Country

United States

Website

flowiseai.com

Vendor Details

Company Name

Laminar

Country

United States

Website

www.lmnr.ai/

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