
Apify
Apollo.io
Outscraper
Octoparse
import.io
Expandi.io
Waalaxy
A marketplace of simple to use no-code APIs

ChatGPT
AllChat AI
Poe
Perplexity.ai
AlphaCorp AI
All-In-One-AI.co
Gemini
Experience the power of advanced AI models with MultipleChat. Get a text chat interface for Claude, Gemini and ChatGPT.

Which is more popular?
Based on our record, Phantombuster seems to be a lot more popular than MultipleChat. While we know about 19 links to Phantombuster, we've tracked only 1 mention of MultipleChat.
Website, pricing, platforms and company facts side by side.
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|---|---|---|
| Website | phantombuster.com | multiple.chat |
| Pricing | — | |
| Company | — | Startup from Switzerland · 1 - 9 employees · 2024 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of Phantombuster yet.
MultipleChat is an advanced AI collaboration platform that brings together leading AI models such as ChatGPT, Claude, Gemini, Grok, and Perplexity into a single unified workspace. Instead of relying on a single AI, MultipleChat allows users to run multiple models simultaneously, compare outputs...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
📈 Lead Generation 2020 📈 | How To Scrape Emails In Minutes | PhantomBuster Webcrawler Review
More videos
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Phantombuster and MultipleChat.
MultipleChat's answer:
MultipleChat is designed for professionals and teams who rely on AI for high-quality output and decision-making. This includes content creators, marketers, researchers, students, business teams, and analysts.
It is especially valuable for users who need accuracy, structured outputs, and multi-perspective insights rather than relying on a single AI response.
MultipleChat's answer:
MultipleChat is unique because it enables true AI collaboration instead of relying on a single model. It allows multiple AI systems like ChatGPT, Claude, and Gemini to work together in one workspace, compare outputs side by side, and verify responses for higher accuracy.
The platform introduces collaborative AI processing, where models refine and validate each other’s outputs, reducing errors and improving reliability. Combined with built-in tools like Document, Presentation, Data, and Image Studios, MultipleChat goes beyond a chatbot and becomes a complete AI workspace.
MultipleChat's answer:
Most AI tools rely on a single model, which can lead to inconsistent or unverified results. MultipleChat solves this by allowing users to run multiple AI models simultaneously, compare responses, and generate more accurate outputs through cross-verification.
Users do not need to switch between tools or subscriptions. Everything is available in one platform, including content creation, data analysis, presentations, and image generation. This makes MultipleChat more reliable, efficient, and cost-effective compared to traditional AI tools.
MultipleChat's answer:
MultipleChat was created to solve a key limitation in AI usage: relying on a single model for important tasks. Different AI models often produce different answers, and users were forced to manually compare and verify them.
The platform was built to bring multiple AI systems into one workspace, allowing them to collaborate, validate, and improve outputs together. This shift from single AI usage to collaborative AI processing is at the core of MultipleChat’s vision.
MultipleChat's answer:
MultipleChat is built using advanced AI integration and orchestration technologies that connect multiple large language models such as ChatGPT, Claude, Gemini, and Grok into a unified system.
It combines cloud-based infrastructure, real-time processing, prompt optimization, and API-based model integration to enable collaborative AI workflows, output comparison, and verification within a single platform.
MultipleChat's answer:
MultipleChat is currently used by a growing base of individual professionals, creators, researchers, and teams across different industries.
Due to privacy and confidentiality, specific customer names are not publicly disclosed. However, the platform is actively used for content creation, research, business workflows, and data analysis.
Share your experience with using Phantombuster and MultipleChat. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


A LinkedIn automation tool performs outreach actions such as connection requests and messages, while a scraper extracts data from LinkedIn profiles and searches into a list. PhantomBuster and Evaboot both extract...
PhantomBuster is more of an automation and data extraction toolkit than a traditional LinkedIn outreach platform. Instead of focusing on structured drip campaigns, it allows you to scrape data and automate actions...
We have no reviews of MultipleChat yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


Some teams use Phantombuster to automate LinkedIn outreach to unresolved users. I don't recommend this — it violates LinkedIn's ToS and creates legal exposure faster than it creates pipeline. - Source: dev.to / 6 months ago
Make.com is a valid alternative to n8n. Make's pre-built modules for Apollo, Hunter.io, and Phantombuster are more polished out of the box. n8n's self-hosted version is cheaper at scale and supports arbitrary HTTP calls without needing a... - Source: dev.to / 7 months ago
This is the core problem with scraping-adjacent APIs: you often can't audit their collection methods. When Phantombuster runs automations using your LinkedIn session cookie, your account is the one LinkedIn's fraud detection sees. When... - Source: dev.to / 7 months ago
So our team built MultipleChat — and I want to share why and how it works, because the idea is more interesting than the "we made a wrapper" framing makes it sound. - Source: dev.to / 6 months ago
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