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Autonomous Source-to-Pay (S2P)
S2P process solutions improve spend visibility and management, compliance, and supplier onboarding while mitigating supplier risk.
What is autonomous source-to-pay?
AIOPS.D™ autonomous source-to-pay delivers the targeted solutions to drive self-healing data, cross-enterprise data matching, and autonomous rule sets with human decision prompts across an organization’s sourcing life cycle to make them autonomous and touchless.
The AIOPS.D™ advantage
With AIOPS.D™ handling procurement and invoicing processes, human interaction is minimized and required only for exception handling. AI-driven solutions select the proper vendor and create purchase orders based on historical data and autonomous rule validation with real-time decisions regarding item availability and pricing. S2P solutions can automatically identify billing errors, fill in missing data for swift approvals, ensure payment in the proper currency, and provide intelligent guidance for exception handling.
Why AIOPS.D™
AIOPS.D™ S2P eliminates manual data processes and corrects incomplete data matching and inconsistent handling rules to positively affect sourcing accuracy and timeliness across the procurement life cycle.
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Autonomous Quote to Cash
Billing operations process solutions for all enable end-to-end revenue management for scalable, flexible, and autonomous billing and invoicing with real-time customer insights.
What is autonomous quote to cash?
AIOPS.D™ autonomous quote to cash spans the entire quote-to-cash cycle process, using AI and ML to analyze historical pricing constructs to create accurate quotes for increased customer acceptance rates. It enables end-to-end revenue and subscription management with scalable, flexible, and autonomous billing and invoicing with real-time customer insights.
The AIOPS.D™ advantage
With AIOPS.D™ managing revenues and subscriptions in real time, enterprises will achieve greater billing accuracy, improved financial results, and higher customer satisfaction.
AI-fueled solutions perform autonomous pricing and quote generation as well as curating subscription activations, invoicing, and management. Drive renewals and increase customer retention and satisfaction with personalized, flexible subscription packages.
Why AIOPS.D™
AIOPS.D™ autonomous quote to cash helps the workforce generate insights for better decision-making, using ML to enhance the procure-to-pay life cycle from historical pricing analysis to root-cause assessments—all in real time.
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Autonomous Data Operations
Data management process assets allow operational data to become an immutable record, bringing intelligent, trusted, and validated data governance to the organization.
What is autonomous data operations?
AIOPS.D™ autonomous data manages master data with minimal user inputs through AI/ML-powered corrections and self-healing algorithms, autonomously filling gaps in the attributes of supplier and material profiles referencing a unified master dataset. With autonomous data operations, operational data becomes an immutable record, bringing intelligent, trusted, and validated data governance to an organization.
The AIOPS.D™ advantage
With AIOPS.D™ performing autonomous data operations, the burden of entering, validating, and correcting supplier and material data shifts to AI/ML-based self-healing algorithms, driving data quality and accuracy across the enterprise with minimal user input in real time.
Eliminate redundant data-entry tasks and leverage historical and third-party data sources to improve data consistency and align with governance models. Give end users a better experience through a centralized data management console, conversational AI, and mobile-device adaptive screens to enable corrective actions from anywhere while maintaining data synchronization across the enterprise.
Why AIOPS.D™
AIOPS.D™ autonomous data operations solves for multiple data entry and integration points that yield inconsistent data quality, dramatically raising confidence in the data required to support business processes and enable real-time decision-making.
