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What is Lilac?

Lilac serves as an open-source platform tailored for data and AI experts aiming to improve their products through superior data management techniques. It provides users with the ability to extract insights from their data by utilizing sophisticated search and filtering options. The platform promotes teamwork by offering a consolidated dataset, ensuring that all team members can access the same information seamlessly. By adopting best practices for data curation, including the removal of duplicates and personally identifiable information (PII), users can optimize their datasets, which leads to decreased training expenses and time. Moreover, the tool incorporates a diff viewer that enables users to visualize the impact of modifications in their data pipeline. Clustering techniques are applied to automatically classify documents by analyzing their text, thereby grouping similar items and revealing the hidden structure within the dataset. Lilac employs state-of-the-art algorithms and large language models (LLMs) to execute clustering and assign relevant titles to the contents of the dataset. Furthermore, users can perform immediate keyword searches by entering specific terms into the search bar, which facilitates more advanced searches, such as concept or semantic searches, in the future. This ultimately enhances the decision-making process, allowing users to harness data insights with greater efficiency and effectiveness. In a landscape where data is abundant, Lilac provides the tools needed to navigate it successfully.

What is KeywordOrbit?

KeywordOrbit is a multifunctional desktop application tailored for keyword exploration on both Windows and Mac systems, significantly enhancing Google Autocomplete through the generation of thousands of authentic search queries. It effortlessly integrates information from a user's free Google Ads account, such as monthly search volume, CPC, and a 24-month trend history, all at no extra charge or via an optional pay-as-you-go API model. Featuring a robust one-click clustering capability, it categorizes numerous keywords into topic clusters based on search intent, offering a thorough overview of monthly demand for each cluster and converting a basic keyword list into a strategic content roadmap. Additionally, the application incorporates Google Trends analytics, providing insights like interest over time, leading countries, and related queries, while also supporting multi-tab project management, advanced filtering options, favorites, tri-state filters, and the capability to export data to CSV format, all optimized for managing datasets that exceed 50,000 keywords. Users can conveniently save their projects locally, helping to keep their research data secure on their devices. Pricing begins at an appealing $19 per month for founding members, with a one-time lifetime license priced at $199, and a risk-free $1 trial allowing full access for a week. Moreover, the Windows versions come with code-signing for added security, while macOS versions are notarized to ensure reliability, making the application a trustworthy choice for users. The combination of these features makes KeywordOrbit a valuable tool for anyone looking to enhance their keyword research efforts.

Media

Media

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Integrations Supported

Cohere
Docker
Hugging Face
OpenAI
Python

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

$19/month (or $199 lifetime)
Free Trial Offered?

Supported Platforms

Linux

Supported Platforms

Windows
Mac

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Lilac

Company Location

United States

Company Website

www.lilacml.com

Company Facts

Organization Name

KeywordOrbit

Date Founded

2026

Company Location

Canada

Company Website

keywordorbit.com

Categories and Features

AI Development

Not specified

Categories and Features

Keyword Research

Not specified

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