Epicor has unveiled its new Epicor Grow portfolio, an integrated set of Artificial Intelligence (AI) and Business Intelligence (BI) capabilities powered by an industry-focused data platform tuned specifically for the requirements of the make, move, and sell industries.
The new portfolio, introduced at the Epicor Insights 2024 user conference held this week in Nashville, reimagines how AI-powered ERP software can and should serve the supply chain industries and their workers. Guided by the company’s cognitive ERP vision to transform traditional ERP from a system of record to a system of action, the Epicor Grow portfolio leverages many types of AI — generative, machine learning, natural language processing, predictive analytics and more — to deliver more than 200 highly specific industry use cases that adapt to workers in their contextual environment or workflow, giving them the insights and efficiencies they need to drive more value.
“We know the keys to realising the full power of AI revolve around two important things: applying AI to a well-defined, practical business issue, and leveraging high-quality data,” said Epicor Chief Product & Technology Officer Vaibhav Vohra. “Our new Epicor Grow portfolio delivers on both fronts, putting workers at the centre of the intelligence ecosystem. We’re delivering deep AI integration across real-world industry workflows – unlike ‘one size fits all’ industry-agnostic ERPs – to surface actionable insights and drive efficiencies. And we’re empowering users with a rich, industry-centric data platform and no-code tools to create purpose-built data pipelines to help solve specific challenges.”
By design, ERP technology sits at the core of an organisation, coordinating and managing mission-critical processes across business functions. At Epicor, we see incredible opportunity for the supply chain industries to tap into the vast ERP data sets at the hearts of their businesses to leverage AI not just to automate tasks but enable systems to think, learn, and empower workers with the right intelligence to make decisions in ways that were previously unimaginable.
The Epicor Grow portfolio is built to take advantage of these opportunities, unlocking new levels of efficiency, innovation, and competitiveness for companies across the supply chain. This helps workers reduce the complexity and friction in how they have traditionally extracted and used intelligence from their financial and operational data, machines, and external supplier communities.
Core elements of the integrated portfolio include:
Epicor Prism – Epicor Prism is a patent-pending generative AI service embedded across the Epicor Industry ERP Cloud that empowers workers to access the right insights, in the right context, at the right time to make smarter decisions. Epicor Prism is specifically fine-tuned to the Epicor data structure, which has been developed over decades of experience innovating across the manufacturing, distribution, and retail industries. Users engage with Epicor Prism in the context of their native Epicor ERP platform, while behind the scenes task-specific agents collaborate to surface insights or execute actions as prompted.
For example, users can leverage Epicor Prism as a code assistant to create automated business processes more quickly, or use conversational ERP to access production and purchasing insights without the need to know where files are located. Epicor Prism can also automate supplier communications to speed purchasing, enabling users to automatically send RFQs to their supplier network and parse and translate quotes to determine the best price and fastest delivery.
Epicor Grow AI – Epicor Grow AI transforms the ERP experience with AI that is easy-to-use, practical, and outcomes-focused. Epicor Grow AI surfaces insights with high speed and accuracy to solve industry-focused challenges in the familiar context of a customer’s Epicor solutions. Example capabilities and workflows include:
- AI-driven predictive analytics to help generate, analyse, and act on multiple forecasts related to inventory, demand, and sales.
- AI-generated sales orders created from natural language email inquiries, speeding fulfillment and reducing customer service effort while increasing conversion and customer satisfaction.
- Perosnalised, AI-generated product suggestions based on past order history to help optimise inventory levels, reduce costs, and drive greater revenue.
- AI-powered predictive maintenance suggestions and notifications for fleet vehicles, reducing unscheduled vehicle downtime, delivery delays, and maintenance costs.
- Accelerated access and knowledge sharing across the Epicor library of product and support resources, giving users fast, accurate answers to their questions with curated, AI-driven responses.
Epicor Grow Inventory Forecasting – From Epicor’s recent acquisition of Smart Software, users can leverage predictive analytics and model “what-if” scenarios to better manage inventories with embedded, purpose-built, machine-learning forecasting engines.
Epicor FP&A – Deeply embedded Financial Planning and Analysis capabilities for easy, accurate, and thorough financial reporting.
Epicor Grow BI – Easy-to-use no-code technology joins and transforms data with elegant visuals, metrics, and dashboards. Users can get alerts and even externalise data blueprints to pair with other BI tools for maximum flexibility. In addition, Epicor recently expanded data centre availability for Epicor Grow BI in AWS U.K., supporting international organisations.
Epicor Grow Data Platform – A powerful way to manage enterprise data in one place with a full-stack, no-code data platform that delivers fast time to insight with deeper visibility. The platform allows users to bring their data to one central location to feed Epicor AI and BI applications, and uniquely includes a no-code, interactive Pipeline Canvas to move or modify prebuilt data pipelines or enable users to build their own. This lets users selectively combine, clean, normalise, and analyse only the data they need, saving time, cost, and delivering a higher quality, more accurate output.
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