Integrating a large language model (LLM) with StockTrim opens up powerful new ways for users to interact with and extract insights from their inventory data. This advanced technology allows for natural language interactions, enabling non-technical users to quickly access complex information and customized reports without needing deep technical knowledge. From querying data in everyday language to generating bespoke reports, purchase orders, and even analyzing market trends, an LLM integration offers a suite of tools designed to streamline operations and provide real-time insights. Here’s a breakdown of the transformative features an LLM could bring to StockTrim.
1. Natural Language Queries
An LLM integration would allow users to interact with StockTrim using natural language, making the tool more user-friendly for non-technical users:
- Users can ask complex inventory questions in plain language, like “What stock items will likely run out in the next month?” or “what is my expected spend with supplier A” and get actionable answers without needing to know how to query data manually.
- It reduces friction by allowing users to find insights and extend the functionality of the app beyond just the main UI, allowing any customized query of the data
2 Custom reports
Custom Reports in Any Format
With an LLM, users could:
- Request custom reports in any format, with specific columns and data points. For example, users might ask for a report that includes "historical sales, current stock levels, supplier lead times, and projected demand" in a table or graph format.
- Dynamically generate ad-hoc reports based on changing business needs, such as "sales over the last quarter filtered by region and category."
- Create multi-format reports (e.g., Excel, CSV, or PDF) by simply asking the LLM, improving user control over how they receive and use the data.
- Include advanced filtering options where users can use natural language to specify custom conditions like, "Show all products where stock is below 50 and sales have increased by 20% in the last month."
3. Custom Purchase Orders (POs) with Business Logos
- LLMs could automate the generation of purchase orders (POs) that are fully customized:
- Users can design the layout of POs, including placement of business logos, terms, conditions, and even color schemes or branding elements, all by simply describing it in natural language.
- Generate POs in different formats (e.g., PDF, Word) with all the required fields and formatting specific to the business’s requirements.
- Include custom content, such as supplier-specific details, itemized lists with special notes, or adjustments based on past purchase history, making it easier for businesses to ensure the POs meet exact specifications.
4. Enhanced Customer Support
LLM-powered chatbots could offer immediate assistance to users:
- Answer common queries about how to use StockTrim features.
- Troubleshoot issues and guide users through the software’s functions.
- Provide real-time insights and training on advanced features, creating a smoother onboarding experience
5. Sentiment and Market Impact Analysis
LLMs can analyze text data from the broader market (e.g., supplier emails, news articles, social media posts):
- It could inform users how global events, such as supply chain disruptions or market sentiment shifts, could affect inventory needs.
- This can help StockTrim’s users better anticipate risks and adjust inventory strategies accordingly.
- Using an LLM to assess both publicly available data with the customer’s proprietary confidential data would give them market advantage compared to their competitors.
If you would like to see the benefits of using AI in your inventory forecasting, start a FREE trial today with StockTrim.
