Use Cases - Skim AI

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Saving hours of editorial time in news media

NITL – News In Three Lines partnered with Skim AI to build an AI model that helps aggregate daily news from over 500 sources and deliver it in three lines to readers across the globe. Their custom AI model saved their editorial team hours of manual work each week.

Cutting costs and shaving a week off post-production in photo & film

Sebring Revolution partnered with Skim Ai to automate a huge part of their multidimensional media post-production process—enabling the team to deliver work a week faster than before.

Helping acquire new users with smarter capabilities in crypto & blockchain

Grifin partnered with Skim Ai to build out AI models that enabled them to classify transactions, match transaction data to public companies, and identify subsidiary companies of public companies for more relevant investing.

Providing a more accurate news service spanning across languages in news media

NewsPrime partnered with Skim Ai to serve more specific content to users, as well as summarize and translate the news.

Understanding market sentiment faster and more accurately for crypto

Big Data Protocol partnered with Skim Ai to process social media data around crypto assets, NFTs, and more, across Twitter, Telegram, and Discord for a better understanding of market sentiment.

Upping online course engagement and completion rates in edTech

Ahura AI partnered with Skim AI to build out face mapping and browser scraping AI enabling them to provide AI EdTech solutions that increase Elearner productivity, engagement, and course completion rates.

Entrepreneurs, startups, and enterprises making the most of AI and ML with Skim AI

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What Skim AI customers have to say

<>10 Critical Infrastructure Decisions Every Enterprise Must Make Before Scaling AI

<>Beyond Single-Cloud AI: Enterprise Lessons from OpenAI Computing Problem

<>Calculating Your Enterprise AI Computing Infrastructure Costs: A 2024 Guide

<>The Executive’s Guide to Implementing OpenAI’s Canvas for Enhanced Productivity – AI&YOU #74

<>Google NotebookLM: How to create AI Powered Podcasts to Revolutionize Enterprise Communication

<>10 Enterprise Use Cases for Google NotebookLM

<>Google NotebookLM: Transforming Enterprise AI with Advanced Features

<>ChatGPT Canvas vs. Claude Artifacts: Which is Better for Enterprise AI Collaboration

<>10 Ways to use OpenAI’s Canvas to Boost Productivity in Your Enterprise Development Teams

<>The Executive’s Guide to Implementing OpenAI’s Canvas for Enhanced Productivity

<>How to Prevent OpenAI API Bans From Your End Users – AI&YOU #73

<>10 Best Practices for Managing User-Generated Content with OpenAI’s API

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<>How to Prompt OpenAI o1 + Should You Use It? – AI&YOU #72

<>Our Favorite 10 ElevenLabs AI Voices + How to Clone Your Own + Enterprise Use Cases – AI&YOU #71

<>How to Prompt OpenAI’s o1 Model

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<>10 Ways Your Enterprise Can Use ElevenLabs’ AI Voice Tech

<>How to Clone Your Voice with ElevenLabs: A Step-by-Step Guide

<>How Non-Technical & Technical People use Agent Zero to Create Autonomous AI Agents and Agentic Workflows – AI&YOU #70

<>What is Agent Zero? A Quick Start Guide

<>Building Custom AI Tools with Agent Zero: The Future of AI Development

<>Unlock the Power of AI with Agent Zero: 10 Ways It Outperforms Traditional Agents

<>Few-Shot Prompting, Learning, and Fine-Tuning for LLMs – AI&YOU #67 Few-Shot Prompting, Learning, and Fine-Tuning for LLMs – AI&YOU #67

<>Our Top 10 ElevenLabs AI Voices: Elevate your User Experience with AI Agents

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AI and ML

Frequently Asked Questions

What are some common AI use cases?

Text-based solutions often revolve around a few general themes that are often done by knowledge workers: (1) information classification/prediction problems/data labeling (labeling information, often to power a BI Dashboard or software solution) (2) information extraction: capturing specific types of information from larger text, like a news article, neatly in a database, (3) Sentiment understanding (4) Recommendation systems, clustering, and cohort analysis (5) Translations (5) Autocomplete, generating text.

What are AI use cases in daily life?

Daily AI use cases are: helping to tag and itemize your inbox, helping to organize your time and manage your team’s agendas, and streamlining daily tasks so you can focus on big-ticket items.

What are machine learning use cases in marketing?

Common machine learning use cases in marketing are helping sales and marketing teams to pre-qualify leads, automating sales and marketing flows, helping to identify user personas, and tailoring marketing materials to match persona problems or jobs-to-be-done.

What are some machine learning use cases in software development?

Common use cases for machine learning in software development are: predicting maintenance needs, detecting anomalies, analyzing sentiment, developing interfaces, analyzing images and videos, and detecting fraud.

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