Salesforce
Canvas Category Software : Information Technology : Customer Relationship Management
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Assembly Line
BACA Systems doubles productivity with Einstein 1 Sales
The company manages its entire sales cycle, including opportunities in Sales Cloud. In addition to giving reps easy access to their sales pipeline, Einstein 1 Sales also includes powerful AI tools to help them boost their productivity. If a rep is unsure how to progress an opportunity, Einstein recommends the next best step.
To make this possible, first BACA Systems will unlock and consolidate all of its data using Data Cloud. Then it will connect its data to Einstein 1 Sales that is used for monitoring and tracking performance for its sales reps.
Einstein Copilot will then use this data to give reps AI-driven recommendations in a trusted, secure environment. This will provide truly personalized guidance and allow the company to pull in data from cases and email conversations to ground custom prompts in Prompt Builder. For instance, a rep will be able to ask Copilot to “help me draft an email to Polly Prospect at the ABC Company.” Einstein will then reference all of the emails that have been sent to the prospect, service case notes, opportunity data, and other relevant data in Data Cloud to craft a personalized email, grounded in the context of that account.
The company set up a complete delivery management system by integrating AppExchange apps Bringg and Rootstock ERP with Salesforce. Now, BACA Systems has better control over its delivery operations with fewer errors and increased automation on previously manual tasks, such as creating and printing shipping labels, as well as tracking of all shipping records. The team implemented this new solution in less than 24 hours without disruption of the day’s ongoing deliveries. As a result, the company has saved 5–8 minutes per order and all shipping activities have an accuracy rate of 99.9%. The time savings is equivalent to 15 workdays per month, or the workload of a full-time employee. The flexibility of the solution also permits BACA Systems to support expansion in the future.
Unified Training of Universal Time Series Forecasting Transformers
Deep learning for time series forecasting has traditionally operated within a one-model-per-dataset framework, limiting its potential to leverage the game-changing impact of large pre-trained models. The concept of universal forecasting, emerging from pre-training on a vast collection of time series datasets, envisions a single Large Time Series Model capable of addressing diverse downstream forecasting tasks. However, constructing such a model poses unique challenges specific to time series data: i) cross-frequency learning, ii) accommodating an arbitrary number of variates for multivariate time series, and iii) addressing the varying distributional properties inherent in large-scale data. To address these challenges, we present novel enhancements to the conventional time series Transformer architecture, resulting in our proposed Masked Encoder-based Universal Time Series Forecasting Transformer (Moirai). Trained on our newly introduced Large-scale Open Time Series Archive (LOTSA) featuring over 27B observations across nine domains, Moirai achieves competitive or superior performance as a zero-shot forecaster when compared to full-shot models.
Rootstock Debuts AIRS™: Cutting-Edge AI for Manufacturers
Rootstock Software, a recognized leader in the Manufacturing ERP space, is thrilled to announce the launch of AIRS. Short for “Artificial Intelligence (AI) from Rootstock (RS).” Built on Salesforce Einstein 1 Platform, AIRS leverages Rootstock’s unique ERP dataset—including order, supply, financial, and production data. This dataset is collected from across the Signal Chain—from CRM, SCM, PLM, IoT platforms and other systems. As a result, AIRS enables a complete Signal Chain Decisioning Platform, as it bridges the physical and digital worlds and enables smart, autonomous decisions that will redefine manufacturing innovation.