Onepoint AI Ecosystem for Boomi Press Release

Examples of the growing list of AI agents demonstrate their usefulness for diverse business use cases:

• The AWS Resource Spinner agent designs and deploys scalable AWS infrastructure tailored to specific needs. It can spin up resources like EC2, RDS, S3, and Load Balancers, enabling smart setups and moving from specifications to cloud infrastructure instantly. It can even spin up a Boomi atom on AWS. For example, the AWS Resource Spinner agent would allow an IT professional to quickly provision infrastructure for a new project or environment through conversational interaction.

• The ServiceNow Incident Management agent enables users to create, update, list, and summarise incidents through natural conversations. It allows users to search for incidents by filtering on different criteria, get details for a particular incident, create new incidents with title, description, and priority, update existing incidents, and add comments. For example, an IT support agent managing incidents can create, update, list, and summarise incidents using natural language, making the process faster and more intuitive, and improving the customer experience.

• The Hotel Matcher agent harnesses the full potential of OP Intelligence and OP Database connectors to deliver dynamic RAG-based matching from a hotel knowledge base. This agent aims to find entities like hotels using smart AI and vector search, without needing SQL or fuzzy logic. It uses vector cosine similarity for searching and generates embeddings. It supports identifying hotel names from text input, searching the knowledge base, finding the best match with high confidence, and even smartly identifying the correct hotel despite misspellings in the query.

• The SAP Low Stock Purchase Recommendation agent detects low stock and recommends purchase orders based on sales, vendor lead time, and minimum safe stock. It functions as a “smart” tool for reorder recommendations. It can retrieve material, vendor, and plant IDs by name, and then generate intelligent purchase order suggestions based on real-time analysis. It can also recalculate when to reorder based on a specified minimum stock level. For example, a procurement manager can automatically identify materials that are low in stock and generate purchase recommendations. The agent’s ability to detect low stock and recommend orders based on factors like sales and lead time is a concrete example of AI automating and optimising core business processes.

These agents can be run as standalone applications, enhanced, or embedded within the Boomi AI Designer, Boomi Flow, or a company’s stack.