How large organisations are putting generative AI to work on their own data, from the team building AsscherAi. 487 articles.
Automotive manufacturers can reduce costs by using AI to analyse production and supply chain data, identifying areas for improvement and optimising workflows, as seen in the example of a...
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Agentic workflows help a purchasing manager choose the best supplier by analyzing the purchase order table and supplier performance log, then comparing the results against their manual...
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Enterprise AI streamlines automotive production by identifying bottlenecks and optimizing supply chains, allowing a logistics manager to ask which shipments are delayed, why, and how it...
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AsscherAi helps energy and utilities companies answer financial questions in real time, such as current spend against a budget line or outstanding commitments for a project, by querying...
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A production planner checks the fabric inventory levels in the enterprise resource planning system, then asks AsscherAi what quantities are committed to existing orders, to determine the...
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AsscherAi reduces variance explanations that arrive after the period by analysing general ledgers and budgets in real time, enabling finance teams to identify root causes quickly, such as a...
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Procurement integration with AI systems requires careful handling of write paths to prevent errors in systems of record, such as the purchase order table or supplier contract database, and...
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Implementing enterprise AI governance in textiles and apparel requires a category manager to balance creative vision with commercial realities, while a shift supervisor adjusts production...
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Shadow mode allows a new system to run in parallel with the existing process, enabling testing and validation without disrupting the workflow, as seen when a category manager compares two...
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Supply chain managers can optimise AI costs by focusing on integration and data work, rather than the technology itself, and attributing spend to the process being supported, such as demand...
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A category manager uses AsscherAi to compare two suppliers and retrieve a list of similar products or services, which is made possible by a vector database that stores embeddings of the...
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Implementing AI in supply chain operations can take several weeks to show tangible results, as it requires setting up infrastructure, connecting data sources, and defining key performance...
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Implementing AI productivity solutions in textiles and apparel can be challenging due to the complexity of range planning and supplier fragmentation, but a category manager can use...
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AI for finance in e-commerce and retail streamlines decision-making by providing rapid access to financial data, enabling category managers to optimise inventory levels and shift...
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Enterprise AI systems like AsscherAi can help printing and packaging companies reduce substrate waste by providing real-time data on inventory levels and production schedules, allowing a...
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Generative AI reduces unplanned downtime by making the signals that precede a stoppage cheap to investigate, a production team can ask what deviated this shift, on which line, and how it...
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Integration of AI systems with operations involves reconciling definitions and establishing a common vocabulary to ensure accurate data interpretation, as seen when a production planner...
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Implementing enterprise AI governance in printing and packaging reduces setup and makeready losses by enabling a shift supervisor to ask what factors contribute to prolonged setup times on...
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Semantic search retrieves data based on query meaning, not keyword matching, by analysing the purchase order table, invoice log, and budget allocation spreadsheet to answer questions about...
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Implementing AI in customer service requires careful consideration of integration and data work costs, which can be substantial, and evaluating the run cost against query volume to optimise...
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Structured output enables a purchasing manager to query the purchase order table and get a list of suppliers in a format that can be easily consumed by the enterprise resource planning...
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Introducing AI to customer service reduces enquiry response times by analysing common questions and automating frequent responses, a customer service team can ask what types of enquiries...
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Implementing AI-powered tools in printing and packaging can help reduce setup and makeready losses by analysing production schedules and material availability, allowing shift supervisors to...
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AI process automation in textiles and apparel streamlines range planning by analysing sales data and forecasting demand, enabling category managers to make informed decisions and reduce...
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