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Wand AI

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Wand.ai is an AI platform that provides world-class analytics capabilities, including predictive analytics, to regular business users without deep technical knowledge.

FEATURES

  • 💬 Real-time chat: Wand.ai offers real-time chat functionality that allows users to communicate with each other instantly.
  • 📊 Analytics: The platform provides analytics tools that help users track and analyze their data to make informed decisions.
  • 🤖 AI-powered: Wand.ai is powered by artificial intelligence, which enables it to automate tasks and provide personalized recommendations to users.
  • 🌎 Multi-language support: The platform supports multiple languages, making it accessible to users from different parts of the world.
  • 🔒 Security: Wand.ai takes security seriously and provides features such as two-factor authentication and data encryption to ensure the safety of user data.

USE CASES

  • 💼 Business-Centric AI: Wand.ai is a no-code AI platform that enables businesses to leverage artificial intelligence without prior programming knowledge

ADDITIONAL INFO

Release
2022
Location
Israel
Employees
11 - 50
Tech Used
Radix UI, Tailwind CSS, shadcn/ui, React, Next.js, Node.js, Next.js

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FAQ

Wand.ai is a self-service AI platform that allows users to create chatbots, track machine learning experiments, and fine-tune models. It offers a range of pricing plans to suit different needs and budgets.
Wand.ai offers three pricing plans: Starter, Growth, and Scale. The Starter plan costs $29 per month and includes 3 chatbots, 1,000 chat queries per month, and 0.5M words or 500 web pages per chatbot. The Growth plan costs $99 per month and includes 6 chatbots, 5,000 chatbot queries per month, and 2M words or 2,000 web pages per chatbot. The Scale plan costs $499 per month and includes 10 chatbots, 20,000 chatbot queries per month, and 5M words or 5,000 web pages per chatbot.
To turn off Wandb in the trainer, you can call wandb.init(mode="disabled") or set os.environ"WANDB_DISABLED" = "true". Alternatively, you can disable the weights and biases (wandb) callback in the TrainingArguments directly by setting args = TrainingArguments(report_to=None, ...).
To upgrade Wandb, you can copy and paste the following command into your terminal: $ wandb server start --upgrade. Alternatively, you can upgrade your instance manually by copying and pasting the following code snippets into your terminal: $ docker pull wandb/local, $ docker stop wandb-local, $ docker run --rm -d -v wandb:/vol -p 8080:8080 --name wandb-local wandb/local.

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