Machine Learning Operations
Improve Machine Learning Project Value
Machine Learning (ML) provides businesses powerful information to make decisions and optimize their performance. Teams accelerate time-to-value when they empower their decision-makers to interact with, provide data, and identify ML models’ weaknesses. The interactions result in improved accuracy and reliability. However, according to Gartner, 85% of data science and machine learning projects fail. Two of the most common reasons these projects aren’t delivering include technical skill shortages and recurring issues with deployment and operationalization.
Skill shortages are twofold. Data scientists can build and tune models but lack operational skills to ensure models are utilized across the enterprise. Enterprise employees lack data science skills and find it difficult to provide data to use existing models.
"Over 85% of ML projects fail." - Gartner
Krista Automates Machine Learning Projects
Successfully transitioning from nascent ML models to intelligent automation requires connecting people and systems. Systems must be sufficiently competent to understand people. People must be able to interact with, provide data, and identify model weaknesses to teach the model how to improve its output.
Krista makes machine learning as simple as “Ask Krista.” Krista AI integrates directly with your existing collaboration and automation tools. Integrating people and systems means businesses can operationalize machine learning projects and realize more value from machine learning and data science projects by removing technical barriers.
Increase Your Data Science ROI
Using Krista as an ML interface broadens your data scientists’ reach and operationalizes AI. Your data science teams are no longer mired with manually manipulating training data nor managing project schedules. Enterprise employees are provided better information from existing datasets by interacting with ML via an easy-to-understand conversation.
Utilizing and training your ML models with Krista enables your organization to operationalize intelligent automation. Intelligent automation orchestrates numerous business routines and operations, such as sales forecasting, customer relationship management, customer support, and IT delivery and security. Furthermore, as more data flows through your various systems during routine business operations, Krista automatically captures new training data, enabling your AI to constantly learn and become more intelligent.
Successful machine learning is a highly collaborative, continuous training and validation loop whereby people and systems work together to augment one another’s capabilities.
Other available resources
How to Decrease the Cost of AI Projects
To understand the true cost of AI, it’s essential to break it down into its parts. This article provides some of the most common cost elements associated with AI systems and how to reduce your overall expenses without sacrificing value.
How to Successfully Operationalize Machine Learning
Businesses can reap innumerable benefits by integrating ML into their workflows and core strengths, but that can only happen when they operationalize or deploy ML models in production.
Investment Broker Uses Document Understanding and AI to Maximize Merger and Acquisition ROI
Krista is saving Horatius Group hundreds of labor hours with intelligent document understanding. Krista reduced an investment analyst’s time reviewing and validating CIMs from ten hours to less than one hour.
