Customer Engagement unlocks data insights with the power of AI and ML to improve ROI by improving CX through relevant, timely engagement. Influence customer decision journeys at scale across micro-segments, and enhance customer experience by predicting customer needs, improving recommendations, and mitigating churn.
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Dynamic data-driven optimal pricing using market share, profitability, revenue, inventory, and demand to solve circular dependency of pricing and demand. Increase top-line and bottom-line while pricing within the consumer acceptance threshold.
Drive call center productivity and improve customer experience with ML-powered solutions that reduce the number of calls, increase first-call resolutions, and reduce the average call time. Mitigate churn, increase cross and up-sell, and improve agent productivity and onboarding timelines.
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Manage AR and DSO through AI-enabled predictions, knowing when and who will pay what amount. Make informed capital allocation and cash management decisions. Prepare for adverse market conditions and proactively avert defaults by improving collections. Increase shareholder confidence over time with excellence in cash flow management.
Visualize spend including off-PO/maverick spend. ML-driven business relevant taxonomy and as high as 98%+ spend categorization, unique vendor determination for greater negotiating leverage, actionable savings insights based on tail spend and unit price optimization and outsized vendor risk identification.
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Maximize free cash flow by improving sales and reducing slow-moving inventory. Power your market predictions by leveraging highly accurate attribute-based forecasting using regional market trends, past data, expected price points, and dependencies in sourcing for the short term. Leverage long-term demand forecasting to optimize the business plan.
Streamline inventory management process with machine learning to prevent overstocking and eliminate backlogs while maintaining required service levels. Predict customer behavior, buying patterns, and market dynamics to ensure optimal inventory level and maintain sustainable profit.
State-of-the-art Dynamic Optimization algorithm-driven efficiencies in freight and logistics costs, warehouse site selection, and SKU configuration. Improve stock availability and warehouse mapping optimization. Optimize freight and logistics turnaround timeframe to enhance inventory throughput.
Identify risks, and improve decisions by reading, analyzing, and comparing contracts using AI, ML and NLP to deliver business-critical insights. Ensure better vendor performance and drive cost savings. Stop analyzing contracts by paying lawyers or waiting on resources in faraway countries to analyze contracts for you.
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Identifying, processing, and collecting healthcare service revenue is increasingly complex, with new clinical advancements and complex payer-provider contracts. The traditional rule-based Revenue Cycle Optimization (RCO) solutions cannot deal with the complexity of today's healthcare. AI and ML can find patterns to predict, identify missed revenue, and learn with user inputs continuously, eliminating the need to define rules.
Learn MoreSimplifying AI and ML DevOps through automation significantly boosts data science team productivity. Automation also enables seamless integration of critical tools such as monitoring, alerting, data governance, data security, workflow, and orchestration while eliminating the need for expensive data and ML platforms.
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