Custom Machine Learning Models Built Just For You
Process data with AI models with limited ML knowledge/expertise/experience
Custom Machine Learning Models Built Just For You
Process data with AI models with limited ML knowledge/expertise/experience
Custom Machine Learning Models Built Just For You
Process data with AI models with limited ML knowledge/expertise/experience
Custom Machine Learning Models Built Just For You
Process data with AI models with limited ML knowledge/expertise/experience
Why Skim AI?
Over 80% of data science projects fail to go beyond testing and into production. Our mission is to knock down those roadblocks to democratize machine learning. Our team builds, deploys, and maintains custom machine learning models that helps your team optimize performance.
Benefits
Discover how you can capitalize on ML and AI to scale your business and improve efficiencies
• Work closely with our experts to identify opportunities to improve your current operations. Whether you have a team of experienced data scientists or you’re brand new to the potentials of ML, a full consulting evaluation will help you pinpoint which processes to automate.
Leave it to us to plan, develop, train, and deploy the model so no resources are taken from your team
• Find or generate the needed data
• Perform the necessary Risk Assessments
• Choose the right model to run
• Define a model-validation methodology
• Production rollout
• Updates and continuous model validation
Rely on Skim AI for maintenance or receive training from our team if you want to take it on yourself
• Don’t let your model deteriorate, keep them up to date to reflect current dynamics
Common Use Cases
Classification & Tagging of Data: Predict the sentiment, tag, or label that fits your methodology. Any manual labels you are using to classify sentences, articles, tweets.
Turn part of your manual tagging and classification needs over to automation
• Media Measurement and Analysis, Public Relations, Journalism, Research Departments, Researchers, Analysts
• Operations: use automated tagging to sort data or extract needed data into your database, visualize it, make it searchable, or trigger an alert to elevate the issue to a human.
Entity Extraction: Understand which institutions, people, companies, locations, dates, amounts, and more are involved in the media (news, social media, research) you are consuming at a massive scale. Often used to gather high-level statistics and aggregate data at a massive scale and power data visualizations.
• Media, Public Relations, Macro-economic research
Sentiment Classification: Predict the sentiment, tag, or label that fits your methodology. Any manual labels you are using to classify sentences, articles, tweets.
Turn part of your manual tagging and classification needs over to automation
• Media Measurement and Analysis, Public Relations, Journalism, Research Departments, Researchers, Analysts
Recommendation Models: Find similar media (from the web, or your own database), articles, products in seconds
Semantic Search: Search your media or our news database, academic paper database with natural language and retrieve results that are relevant but not an exact match to the text used in your search term.
