Labviva announces AI-based inventory management for R&D pros

It’s long been a fact of life: Procurement tasks are a persistent burden for researchers, often demanding hours of manual effort each week and prone to errors. To counter that, the research-oriented procurement software company Labviva is launching an AI-enabled Inventory Management System (IMS) designed to automate tasks such as reordering and real-time stock monitoring. The IMS also offers AI-based purchase suggestions. IMS automates purchasing by suggesting orders, tracks inventory levels in real-time, and ensures compliance with safety regulations by automatically classifying chemicals. It can be used across multiple labs and teams, creating a centralized inventory management system. The system integrates with existing platforms like SAP Ariba, Oracle Procurement Cloud, and Microsoft Dynamics 365, and can either be used as a standalone solution or alongside existing systems. By automating reordering and providing immediate access to inventory data, the IMS aims to reduce costs, improve efficiency, and free up researchers’ time for scientific work.

In the following Q&A, Labviva co-founder and CTO Nick Rioux weighs in on the benefits and features of Labviva’s new Inventory Management System:

Can you provide a specific example of how Labviva’s IMS time-saving features have benefitted or could benefit a research team’s efficiency?

Rioux: In research laboratories, inventory management processes can differ from lab to lab, even within the same organization. This kind of decentralization leads to implementing multiple systems, duplicate investments, and even different staffing solutions, involving employees and third-party contractors. Labviva centralizes and automates inventory management for these labs so that different teams can perform various tasks, all within the same system. For example, Labviva’s IMS automatically replenishes stock for customers, eliminating tasks like comparing prices, navigating ecommerce solutions, worrying about POs/invoices, and dealing with other accounting requirements. It also automatically segments chemicals into safety storage classes while promoting safety and compliance – returning a significant amount of time back to researchers and lab operations.

Could you say more on the specific ways AI is used within the system and how it enhances inventory management beyond traditional approaches?

Rioux: We leverage AI to provide better solutions to common problems. For instance, we proactively monitor backorders and lead times to train our AI ordering agent to purchase from the right suppliers at the right times. We also use AI to monitor the frequency of product utilization and stock levels by location so the system can learn which areas need to be restocked or which are more prone to backorders. Overall, AI helps the IMS system guide humans toward tasks that are more additive versus comprehensive. Labviva has always applied AI technology to assist in generating scientific context and content, but it’s the workflow support activities that take our value to the next level for customers.

What are the key benefits for organizations already using procurement systems like SAP Ariba when integrating with Labviva’s IMS?

Rioux: Our goal is to provide organizations with immediate value without requiring many technical changes. By crafting integrations to major ERP and procurement solutions, and leveraging APIs, we can shorten the time for implementation. Companies with existing ERP solutions typically don’t leverage them for research inventory management, but instead, use them mainly for manufacturing bill of materials (BOM) and accounting operations. Any IMS needs to be able to monitor financial transactions to ensure an operational three-way match. Companies must know what was ordered, shipped, received, and billed to achieve financial discipline. Labviva’s deep integration with existing systems powers these capabilities.

Supply chain disruptions have been a major challenge in recent years. How does Labviva’s IMS help research organizations mitigate the impact of such  disruptions?

Rioux: Labviva’s IMS monitors orders, shipment times, and other data points to achieve forecasting capabilities to avoid disruptions and remain stocked. Our IMS directly integrates with Labviva’s purchasing platform, enabling customers to work with any number of suppliers they choose. If an organization wants to reduce supply chain disruptions, it can either work with more suppliers to have a more diverse set of sourcing options, leverage predictive forecasting to time stock levels, or partner with suppliers to achieve reserve stock programs. The IMS can aid with all of these options, helping to ensure customers take the right path for their supply chain strategy.

Looking ahead, what are Labviva’s future plans for the IMS and its broader AI procurement platform?

Rioux: Our roadmap is very exciting. We will continue to invest in AI-focused features to allow more visibility into common inventory actions and work on integrating with more applications within the laboratory. For example, we’re expanding our integrations with Electronic Laboratory Notebooks (ELN) to enable stock to be searched and requested based on our customers’ design protocols. Our AI “suggested supply” will make it quicker and easier for researchers to go from plan to action. Finally, we are investing a lot in expanding our IMS to provide additional downstream workflows in pharma and biotech, and optimizing the platform for scale-up facilities and manufacturing. Ultimately, we are committed to advancing life science supply chain and procurement processes and giving time back to researchers so they can focus on speeding the pace of research innovation.