Glossary # The A-Z of enterprise agentic AI and work context Search the glossary - A - B - C - D - E - F - G - H - I - K - L - M - N - O - P - R - S - T - U - V - W A ### Accounts Payable (AP) Accounts Payable (AP) is the business function managing payment obligations to suppliers, covering invoice processing, approvals, and payment execution. Skan AI observes how AP teams handle invoices, identifying the manual touchpoints and exception patterns with the greatest automation potential. ### Accounts Payable (AP) Accounts Payable (AP) is the business function managing payment obligations to suppliers, covering invoice processing, approvals, and payment execution. Skan observes how AP teams handle invoices to identify manual touchpoints and exception patterns. ### Action An action is the smallest observable unit of work captured by Skan AI, such as opening an application, entering data, or clicking a field. Skan's computer vision classifies actions automatically, transforming raw desktop activity into structured process data that makes previously invisible work measurable. ### Action The smallest observable unit of work captured by Skan, such as opening applications, entering data, or clicking fields. Computer vision classifies actions automatically, transforming desktop activity into structured process data. ### Activity A group of related actions completing a defined step in a business process. Skan identifies activities automatically from desktop observation, replacing manual process interviews. ### Agency Gap The divide between knowing what to do and being able to act autonomously. Gartner coined this to describe GenAI's limitation: informing but not acting. Skan closes this gap by grounding agents in operational ground truth. ### Agent An autonomous software system perceiving its environment, making decisions, and taking actions to reach goals without step-by-step instruction. Skan builds agents from operational ground truth and real observed work data. ### Agent Memory / Persistent Context The capability of AI agents to retain and build on information from previous interactions and tasks, improving performance over time. Skan's context graph provides persistent process memory. ### Agent Operating Procedures Structured, machine-readable process definitions governing AI agent task execution, including workflow steps, decision rules, escalation thresholds, and success criteria. Skan generates these from observed work data. ### Agent Washing The practice of rebranding existing automation tools as AI agents without implementing genuine agentic reasoning. Gartner coined this term to warn buyers about inflated vendor claims. ### Agent-to-Agent Protocol (A2A) An open standard enabling AI agents from different platforms to share context and coordinate tasks securely. Gartner pairs this with MCP as foundational enterprise agentic architecture standards. ### Agentic AI An autonomous form of artificial intelligence that independently makes decisions, learns in real-time, and adapts to dynamic environments with minimal human intervention, enabling a shift from human-driven processes to agile operations. ### Agentic Enterprise An organization where AI agents autonomously handle routine decisions and workflows, freeing human workers for judgment and strategy. Skan serves as its operational intelligence foundation. - [Read more](https://www.skan.ai/blogs/tag/agentic-enterprise) ### Agentic Ontology of Work (AOW) A standardized vocabulary developed by Skan for classifying human and AI work across enterprise environments. Launched February 2026, it provides a common language for actions, activities, processes, and agents. ### Agentic Orchestration The coordination of multiple AI agents, human workers, and enterprise systems to accomplish complex, multi-step goals. Skan's process intelligence provides the operational context orchestration requires. ### Agentic Orchestration Platform Enterprise infrastructure coordinating AI agents, human workers, and systems into a governed execution layer. Gartner identifies this as a $550 billion market and critical control plane. ### Agentic Process Automation (APA) Enterprise automation where AI agents independently plan, execute, and improve complex workflows without predefined scripts. Skan trains agents on operational ground truth for day-one accuracy. - [Read more](https://www.skan.ai/blogs/tag/agentic-process-automation-apa) ### Agentic Process Intelligence A discipline combining continuous process observation with AI agent deployment into a closed loop, where observed work data powers, governs, and improves agents executing enterprise workflows. ### Agentic Runtime Fabric The execution layer of an agentic orchestration platform, carrying out agent plans with speed and cost discipline. It allocates resources, selects optimal models per task, and ensures auditable actions. ### Agentic Training Data Structured, process-level operational data used to train AI agents to execute enterprise workflows accurately. Skan's continuous desktop observation produces comprehensive first-party agentic training data. ### AgentOps The operational practice of managing the full AI agent lifecycle, covering evaluation, testing, deployment, monitoring, drift detection, and improvement. Skan supports this with a work telemetry baseline and observation data. ### AI Agent Mining Continuous observation and analysis of how AI agents execute tasks within enterprises, producing behavioral intelligence used to audit performance, detect drift, and verify conformance. Skan delivers this through desktop observation. ### AI Agents Autonomous software systems perceiving their environment, making decisions, and taking actions to complete goals without step-by-step instructions. Skan builds enterprise agents grounded in operational ground truth. ### AI Governance The set of policies, controls, and accountability structures ensuring AI systems operate reliably and in compliance with regulations. Skan's framework ensures every agent action is bounded, traceable, and auditable. ### AI Operating Model The organizational structure, governance framework, and capabilities defining how an enterprise manages and scales its AI and automation initiatives. Skan supports this with accurate process baselines. - [Read more](https://www.skan.ai/blogs/tag/ai-operating-model) ### AI Process Automation The application of AI capabilities including machine learning and autonomous decision-making to automate complex business processes that rule-based tools cannot handle. Skan delivers this through agentic process automation. ### AI-driven Insights Actionable findings generated by analyzing data about how work is actually performed. Skan produces these by observing desktop interactions continuously, capturing patterns system logs miss. ### AI-Powered Process Discovery The use of artificial intelligence algorithms to automatically discover, document, and analyze business processes, accelerating identification of process variations, inefficiencies, and improvement opportunities. - [Read more](https://www.skan.ai/blogs/tag/ai-powered-process-discovery) ### Application Portfolio Rationalization The process of evaluating and optimizing the collection of software applications within an organization, eliminating redundancies, improving efficiency, and reducing costs by retaining only value-delivering applications. - [Read more](https://www.skan.ai/blogs/tag/application-portfolio-rationalization) ### As-Is Process Map Documentation of how a business process currently executes in practice, capturing actual steps, exceptions, and deviations rather than intended design. Skan generates these automatically from desktop observation. ### Attended vs. Unattended Automation Attended automation supports human users in real time; unattended automation executes complete processes independently. Skan's observation identifies which steps require human judgment. ### Automation Discovery The process of identifying which tasks and workflows are best suited for AI or automation deployment. Skan scores every candidate automatically by observing real work across all applications. - [Read more](https://www.skan.ai/blogs/tag/automation-discovery) ### Automation Maturity Model A framework defining the stages organizations progress through advancing from basic RPA toward autonomous AI-driven operations. Skan anchors maturity assessment in process intelligence. ### Automation Pipeline The end-to-end sequence for moving an automation opportunity from identification through deployment and monitoring. Skan compresses discovery and design phases by automatically observing and scoring candidates. ### Automation ROI The quantified return from an automation investment, comparing cost savings and productivity gains against implementation costs. Skan's Unit Cost of Work metric provides an accurate process baseline. - [Read more](https://www.skan.ai/blogs/tag/automation-roi) ### Autonomous Enterprise An organization where AI agents handle routine decisions and workflows autonomously, freeing the workforce for judgment and strategy. Skan supports this with accurate, observed process data. ### Autonomous Execution The ability of a system to perform tasks independently without human intervention. In business terms, it means automating repetitive tasks and workflows within processes. B ### Bottleneck Analysis The process of identifying stages in a workflow or system that slow down operations or create inefficiencies, helping organizations pinpoint and address obstacles hindering optimal performance. - [Read more](https://www.skan.ai/blogs/tag/bottleneck-analysis) ### BPMN (Business Process Model & Notation) A standardized visual language for modeling enterprise processes using defined symbols to represent steps, decisions, and handoffs. Skan can validate BPMN documentation against observed execution behavior. ### Business Process Automation Technology-enabled execution of recurring business processes with minimal human intervention, from simple rule-based scripts to AI agents handling complex decisions. Skan provides the process intelligence foundation. - [Read more](https://www.skan.ai/blogs/tag/business-process-automation) ### Business Process Intelligence The capability to analyze and generate insights from enterprise process data supporting operations decisions and transformation programs. Skan delivers this by combining desktop observation with AI analytics. ### Business Process Management (BPM) The discipline of designing, executing, monitoring, and continuously improving the operational processes that run an enterprise. Skan adds an observation layer replacing documented assumptions with real-time data. C ### Center of Excellence (CoE) A team that governs and scales an organization's automation and AI initiatives. Skan provides the operational ground truth CoEs need to prioritize investments with evidence. ### Compliance Process compliance is the verification that business processes are executed in line with regulatory requirements and internal policies. Skan monitors compliance in real time by observing actual work execution. ### Computer Vision AI technology that interprets visual information, including screen content. It is the foundational technology behind Skan's process intelligence platform, enabling observation of desktop activity. - [Read more](https://www.skan.ai/blogs/computer-vision-a-comprehensive-primer-skan) ### Confidence Threshold The minimum certainty level an AI agent must reach before acting autonomously without human review. Above threshold the agent acts; below threshold the workflow escalates to humans. ### Conformance Checking Comparison of how a business process actually executes against its intended design, identifying deviations and compliance gaps. Skan extends this beyond ERP event logs by observing desktop-level work. ### Context Engineering The discipline of designing and managing the information context that AI agents need to reason and act accurately. Skan automates this for process agents through work telemetry and context graphs. ### Context Graph of Work A real-time, structured representation of how work actually happens across an enterprise, capturing the flow of actions, decisions, and handoffs rather than just system events. Skan builds this from continuous desktop observation. - [Read more](https://www.skan.ai/blogs/tag/context-graph-of-work) ### Context Graphs Graphs that capture the directional flow of decisions, workflows, and actions across an organization, not just entities and relationships. AI agents use them to understand how work flows. Gartner predicts 50% adoption by 2028. ### Context Grounding The practice of providing AI agents with accurate, current information about a specific operational environment before they reason or act, preventing hallucinations. Skan provides this through its context graph. - [Read more](https://www.skan.ai/blogs/tag/context-grounding) ### Continuous Improvement The ongoing effort to enhance products, services, or processes incrementally. It involves gathering feedback, making adjustments, and striving for excellence over time. - [Read more](https://www.skan.ai/blogs/tag/continuous-improvement) ### Controls and Compliance Cockpit Skan's compliance monitoring feature applying an Identify-Map-Monitor-Report-Remediate methodology to regulated workflows and approval processes. It generates real-time alerts and audit evidence. - [Read more](https://www.skan.ai/blogs/tag/controls-and-compliance-cockpit) D ### Data Discovery The capture and analysis of data generated by how work is actually performed. Skan collects first-party data directly from the desktop, revealing manual workarounds system logs cannot surface. ### Days Payable Outstanding (DPO) Measures the average days an organization takes to pay suppliers after receiving goods or services. Skan identifies specific P2P workflow bottlenecks extending payment cycles. ### Days Sales Outstanding (DSO) Measures the average days to collect payment after a sale, reflecting order-to-cash process efficiency. Skan identifies specific collection workflow steps extending DSO. ### Decision Traces / Decision Lineage Records of the reasoning pathway through which an agent or human arrives at an action, including which data and logic contributed to the outcome. Skan captures this through process observation. ### Descriptive Analytics Answers the question: what actually happened? Skan delivers this by recording every process step in real time, producing an accurate picture of how work flows. ### Desktop Telemetry Real-time capture of user interaction data at the screen level, including application navigation, data entry, and task execution. Skan collects this through computer vision. ### Diagnostic Analytics Identifies the root cause of a performance problem or process deviation. Skan performs this by correlating observed work data across applications and roles. ### Digital Adoption Measures how effectively employees use the technology tools an organization has invested in. Skan quantifies this by observing actual application usage and identifying feature utilization. ### Digital Adoption Monitoring Continuously tracking how enterprise applications are actually used across the workforce, including detection of unsanctioned AI tools. Skan surfaces shadow AI inventory without requiring endpoint agents. ### Digital Transformation The shift to AI-powered, data-driven operations that let enterprises move faster and outperform competition. Skan provides the process intelligence foundation making transformation measurable. - [Read more](https://www.skan.ai/blogs/how-artificial-intelligence-can-accelerate-and-elevate-digital-transformation-skan) ### Digital Twin of Operations A continuously updated virtual model of how an enterprise actually operates, built from observed work data rather than assumed process maps. Skan constructs this from continuous action capture. - [Read more](https://www.skan.ai/blogs/tag/digital-twin-of-organization) ### Direct Modeling of Human Actions The practice of observing and structuring exactly how employees interact with enterprise applications as the primary input for process intelligence. Skan's computer vision is purpose-built for this. ### Domains Modeling Building structured representations of how work flows within a specific enterprise business domain, capturing processes, decision rules, entities, and relationships. Skan constructs these from continuously observed work data. E ### Enterprise AI The application of artificial intelligence technologies within organizational settings, including AI-driven solutions tailored to improve decision-making, operational efficiency, and customer experiences. - [Read more](https://www.skan.ai/blogs/how-to-find-the-right-enterprise-ai-solutions) ### Enterprise Transformation Strategic redesign of how an organization operates and creates value in the age of AI. Skan provides an accurate operational data baseline and evidence of where AI will deliver the highest return. - [Read more](https://www.skan.ai/blogs/unveiling-the-dynamics-of-enterprise-transformation) ### Event Log A structured record of timestamps and activities captured by enterprise systems, used as the primary input for process mining analysis. Event logs miss manual steps and decisions between system touchpoints. F ### Federated Center of Excellence Distributes AI governance across business units, with a central CoE setting standards while local teams execute. Skan supports this with a unified process intelligence platform. ### First-Party Process Data Work activity data captured directly from an organization's own operations through real-time desktop observation, not inferred from third-party system logs. Skan produces this continuously. - [Read more](https://www.skan.ai/blogs/tag/first-party-process-data) ### Future of Work Describes the shift to AI-augmented enterprise operations, where agents handle routine decisions and humans focus on judgment and strategy. Skan supports this transition through work telemetry. - [Read more](https://www.skan.ai/blogs/tag/future-of-work) G ### Generative AI A subset of artificial intelligence focusing on creating new content or data by learning patterns from existing data. It uses algorithms such as GANs and transformers with applications in various fields. ### Governed Autonomy The principle that AI agents operate independently within explicitly defined boundaries, escalating to human judgment when actions exceed authorized thresholds. Skan sets clear operational boundaries for agents. ### Guardian Agents Specialized AI agents that monitor, evaluate, and constrain the behavior of other agents, functioning as an autonomous oversight layer. Gartner predicts adoption by 2029. H ### Human-in-the-Loop (HITL) A design principle of embedding specific human review points within automated workflows, ensuring AI acts with oversight where judgment matters. Skan implements this through confidence thresholds. ### Hybrid Process Intelligence Combines system-based process mining from ERP event logs with desktop task mining from observed user activity, providing a complete operational picture. Skan delivers both natively. ### Hyper Automation A strategy combining RPA, AI, and process mining to automate as many business processes as possible. It has evolved toward agentic process automation where agents reason and adapt. I ### Intelligent Automation Combines AI with process automation to handle judgment-intensive tasks beyond the reach of traditional RPA. Skan provides the process intelligence foundation making intelligent automation genuinely intelligent. ### Intelligent Document Processing (IDP) Extracts, classifies, and validates information from unstructured documents such as invoices and claims forms without manual data entry. Skan identifies where IDP deployment will eliminate the highest-volume work. ### Intelligent Process Automation (IPA) Combines RPA with AI capabilities to handle complex, judgment-intensive tasks. It has evolved into agentic process automation. Skan bridges both stages by grounding automation in continuously observed data. - [Read more](https://www.skan.ai/blogs/tag/intelligent-process-automation-ipa) ### Invisible Work / Hidden Processes Enterprise activity occurring between system touchpoints and never captured in any system of record, including manual steps, data reconciliation, and exception handling. Skan makes this visible. - [Read more](https://www.skan.ai/blogs/tag/invisible-work-hidden-processes) K ### Knowledge Graph of Work A structured representation connecting people, processes, applications, decisions, and outcomes into a queryable model of how an organization performs its work. Skan's context graph extends this with real-time decision traces. L ### Large Action Models AI foundation models trained on human application interaction data to understand and execute complex multi-step tasks within graphical user interfaces without explicit scripting. Skan creates training data for these. ### Large Process Models AI foundation models trained on large-scale structured process data to understand and reason about enterprise workflows. Skan's observation creates first-party process datasets for robust LPM training. ### Lineage and Provenance Graph Records how each decision or output in an agentic system was produced, documenting the data, models, and reasoning that contributed to it. Skan's observation provides the foundational data. ### Living System of Record A continuously updated operational model reflecting how an organization actually functions today, not a static snapshot. Skan creates this by observing work at the desktop level. M ### Manual Process Discovery Maps business processes through workshops, interviews, and manual observation, capturing only idealized snapshots of how processes should run. Skan replaces this with continuous desktop observation. - [Read more](https://www.skan.ai/blogs/tag/manual-process-discovery) ### Model Context Protocol (MCP) An open standard for how AI agents securely access enterprise tools and systems through a standardized interface. Gartner endorses MCP as essential to avoid vendor lock-in. ### Multiagent Systems An architecture where multiple autonomous AI agents collaborate, each with a defined role, to accomplish goals too complex for a single agent. Skan's context graph provides shared operational knowledge. N ### Neurosymbolic AI Combines neural network pattern recognition with symbolic rule-based reasoning in a single architecture. Skan uses this approach to deliver accurate and auditable process intelligence. - [Read more](https://www.skan.ai/blogs/tag/neurosymbolic-ai) O ### Object-Centric Process Mining Analyzes how multiple business objects, such as orders, invoices, and customers, interact within a single process rather than following one linear case. Skan adds a desktop observation layer. ### Object-Centric Task Mining Captures how users interact with multiple business objects simultaneously in a single work session, reflecting the reality of knowledge worker multitasking. Skan's desktop observation captures this. ### Operational Data Layer Foundational infrastructure that captures and continuously updates an organization's real-time work activity, providing AI agents and analytics with an accurate operational picture. Skan constitutes this layer. ### Operational Excellence Continuous improvement of processes and systems to achieve sustainable business growth, efficiency, and customer satisfaction. It focuses on eliminating waste and optimizing resources. - [Read more](https://www.skan.ai/blogs/redefine-process-documentation-for-operational-excellence-with-skan-processdoc) ### Operational Ground Truth An accurate, real-time picture of how work is actually performed, captured from desktop observation rather than inferred from system logs or interviews. Skan establishes this continuously. - [Read more](https://www.skan.ai/blogs/tag/operational-ground-truth) ### Operational Intelligence Continuous, real-time visibility into how enterprise operations are actually performing. Skan delivers this by observing work at the desktop level, capturing telemetry system dashboards cannot. - [Read more](https://www.skan.ai/blogs/tag/operational-intelligence) ### Orchestration Control Plane Defines how work is structured, how agents interact, and which policies govern decisions across all automated workflows. It translates business intent into repeatable execution blueprints. ### Order-to-Cash (O2C) The end-to-end process from customer order through to payment receipt, covering order management, fulfillment, invoicing, and cash application. Skan's O2A platform takes its name from this transformation. P ### Predictive Analytics Uses data to forecast future process performance, such as when a bottleneck will form or an SLA will be breached. Skan applies predictive models to continuously captured work telemetry. - [Read more](https://www.skan.ai/blogs/tag/predictive-analytics) ### Prescriptive Analytics Recommends the specific actions that will produce the best operational outcome. In Skan, it identifies not just where a process underperforms but exactly what to change. ### Privacy-First AI Observation Captures process-level activity data without collecting personally identifiable information about individual employees. Skan masks all PII at the point of desktop capture. - [Read more](https://www.skan.ai/blogs/tag/privacy-first-ai-observation) ### Process Analysis Systematic examination of a business process to identify areas for improvement. It involves techniques like process mapping, process mining, and unit cost analysis. ### Process Analytics Applies data analysis to process performance data to identify inefficiencies, measure cycle times, and quantify improvement opportunities. Skan delivers this from first-party desktop observation. - [Read more](https://www.skan.ai/blogs/tag/process-analytics) ### Process Automation Uses technology to execute recurring tasks or processes in a business where manual effort can be replaced, increasing efficiency, reducing errors, and freeing workers for strategic activities. - [Read more](https://www.skan.ai/blogs/scaling-process-automation) ### Process Benchmarking Compares process performance within an organization against internal data across teams, industry standards, or peers. Skan enables benchmarking with observed performance data. ### Process Data Fabric Integrated infrastructure connecting, harmonizing, and continuously updating process-level operational data from across an enterprise's applications and workflows. Skan builds this through desktop observation. ### Process Definition Document (PDD) A structured specification of a business process including each step, decision points, application interactions, and exception paths, used as a reference for automation development. Skan generates these automatically. ### Process Digital Twin A virtual model of a business process that continuously mirrors real-world execution using live operational data. Skan builds these from desktop observation, capturing human activity and workarounds. - [Read more](https://www.skan.ai/blogs/tag/process-digital-twin) ### Process Discovery Identifying and mapping out business processes using data and analytics. It helps understand how customer orders are processed, identify bottlenecks, and optimize workflows. - [Read more](https://www.skan.ai/blogs/how-process-discovery-leads-to-precision-training-opportunities-skan) ### Process Drift The gradual deviation of a business process from its intended design, typically invisible until performance has already degraded. Skan detects process drift in real time by comparing observed patterns. - [Read more](https://www.skan.ai/blogs/tag/process-drift) ### Process Intelligence The use of AI and advanced analytics to monitor, visualize, and analyze business processes in real-time, helping organizations gain an end-to-end view, identify inefficiencies, and optimize workflows. - [Read more](https://www.skan.ai/whitepapers/process-intelligence-buyers-guide) ### Process Map A visual representation of a business process, outlining the sequence of activities, decisions, and agents involved. Often flowcharts or diagrams helping visualize and improve business processes. - [Read more](https://www.skan.ai/blogs/the-invisible-enterprise-the-missing-piece-in-process-maps-skan) ### Process Mapping Creates a visual representation of how a business process flows, documenting steps, decision points, and handoffs. Skan generates maps automatically from observed desktop activity. ### Process Mining An advanced process discovery technique that analyzes event logs to visualize and understand business processes in detail, identifying inefficiencies and improving customer experience. ### Process Mining Use Cases Operational scenarios where analyzing event logs delivers value, including conformance checking, bottleneck analysis, and automation discovery. Skan extends standard use cases with desktop observation. ### Process Model A more formal representation of a business process, often created using specific modeling languages or software tools. It can be more detailed than process maps and used for simulation and analysis. ### Process Optimization Improving business processes to achieve higher efficiency, lower costs, and better-quality outcomes. It encompasses redesigning workflows, eliminating redundancies, and adopting best practices. - [Read more](https://www.skan.ai/blogs/4-takeaways-from-fireside-chat-on-insurance-process-optimization) ### Process Orchestration Coordinates automated tasks, AI agents, human activities, and system interactions into an end-to-end workflow that delivers a defined business outcome. Skan identifies optimal orchestration design. ### Process Orchestration Software Coordinates automated tasks, agents, and human activities from a central control point across an end-to-end workflow. Skan's process intelligence complements orchestration platforms. ### Process Reasoning Engine Evaluates the current state of a business process, determines the next best action, and selects the appropriate agent to execute it. Skan functions as a process reasoning foundation. ### Process Simulation Models a business process digitally and runs scenario tests to predict how changes would affect performance before production implementation. Skan provides a simulation foundation grounded in real data. - [Read more](https://www.skan.ai/blogs/tag/process-simulation) ### Process Transparency Full, real-time visibility into how work actually happens across an enterprise, not just how it is documented. Skan achieves this through continuous desktop observation. - [Read more](https://www.skan.ai/blogs/building-process-transparency) ### Process Variants The different execution paths a business process takes in practice. Skan captures all variants, including those occurring entirely outside system logs, by observing work at the desktop level. - [Read more](https://www.skan.ai/blogs/tag/process-variants) ### Process-Native Agents AI agents trained on observed enterprise process data rather than generic instructions, understanding how work actually flows including exceptions and workarounds. Skan builds these from its context graph. - [Read more](https://www.skan.ai/blogs/tag/process-native-agents) ### ProcessGPT Skan's generative AI capability letting users query process intelligence data through natural language, with answers grounded in first-party observed process data. ### ProcessPilot Keeps process documentation and standard operating procedures (SOPs) readily available at your fingertips, improving efficiency and reducing errors by ensuring teams have the latest process information. ### Procure-to-Pay (P2P) Covers all activities from identifying a purchasing need through to supplier payment, including requisition, approval, purchase orders, goods receipt, and invoice processing. Skan observes the complete P2P workflow. R ### RPA (Robotic Process Automation) Uses software bots to execute repetitive, rule-based tasks by mimicking human interactions with digital systems. RPA breaks when processes change and cannot handle unstructured inputs. ### RPA Use Cases Specific processes suited for software bot automation, typically high-volume, rule-based, and stable. Skan eliminates guesswork by automatically scoring every observed process. S ### Self-Healing Automation Workflows and agents that automatically adapt when underlying applications or processes change, without requiring manual re-scripting. Skan detects process changes in real time. ### Skan Agents The agentic execution layer of the Skan AI platform, deploying AI agents built on process intelligence. Agents operate inside deterministic playbooks with embedded guardrails and a full audit trail. - [Read more](https://www.skan.ai/skan-ai-agents) ### Skan Blueprint The strategic discovery and assessment layer of the Skan AI platform, designed to give C-suite leaders a quantified business case for AI transformation. It produces a board-ready investment roadmap. - [Read more](https://www.skan.ai/blogs/tag/skan-blueprint) ### Skan Intelligence The operational intelligence layer of the Skan AI platform, providing CISOs and operations leaders with continuous visibility into how work is actually executing, capturing process variants and compliance adherence. - [Read more](https://www.skan.ai/blogs/tag/skan-intelligence) ### Standard Operating Procedure (SOP) A documented set of steps required to complete a task consistently and correctly. Skan automatically generates and updates SOPs from observed work data. ### Structured Observation Data Work activity data captured through real-time desktop observation and transformed into an analyzable format with defined schemas and classifications. Skan converts raw activity into labeled data. ### System of Action (SOA) A platform that actively directs work and executes decisions rather than just recording events. Gartner introduced this to distinguish agentic orchestration platforms. Skan's O2A is an SOA. T ### Task Mining Captures user interactions with software applications to analyze and identify patterns in task execution. It provides a narrow, task-level view of processes, ideal for low-complexity RPA. - [Read more](https://www.skan.ai/blogs/pros-and-cons-of-task-mining) ### Technology Insights Analytics derived from observing how employees actually interact with enterprise applications. Skan captures application usage at the desktop level, revealing system utilization patterns. ### Touchless Invoice Processing Handles supplier invoices from receipt to payment authorization entirely through automated systems without manual intervention. Skan identifies exception patterns preventing straight-through processing. ### Tribal Knowledge Undocumented process expertise held by experienced employees, including informal workarounds, unwritten decision rules, and expert shortcuts never appearing in official documentation. Skan captures this. - [Read more](https://www.skan.ai/blogs/tag/tribal-knowledge) ### Turnaround Time (TAT) The total elapsed time to complete a process from start to finish. Skan measures TAT from observed work data, identifying exactly which step or queue is responsible. U ### Unified Process View A single, end-to-end picture of how a business process flows across all applications, systems, and teams. Skan builds this through desktop observation, connecting every action. ### Unified Semantic Layer Ensures AI agents and applications share consistent definitions of business terms and process concepts across an enterprise. Skan provides the process-specific semantic layer. ### Unit Cost Analysis Determines the true cost of completing one unit of work within a business process. Skan enables precise measurement by observing actual time and steps at every stage. ### Unit Cost of Work (UCOW) A Skan metric calculating the observed cost of completing one unit of work, including labor time, application interactions, and process steps captured from the desktop, providing an accurate baseline. ### Unstructured Data Information that does not conform to a predefined schema, including documents, emails, and screen content. Skan's computer vision extracts structured process intelligence from unstructured activity. V ### Virtual Assistant Skan's desktop observation agent is a lightweight software component installed on a user's device using computer vision to observe workflow activity in real time. All PII is masked at capture. W ### What-If Analysis The ability to model the impact of a proposed process change before implementing it in production. Using Skan's digital twin of operations, leaders can simulate redesigned workflows. ### Work Intelligence Continuous capture and analysis of data about how human work is performed across an enterprise. Skan observes every action across every application, producing structured insights. ### Work Telemetry Continuous capture of data signals from how employees interact with applications and workflows. Skan collects this through desktop observation, transforming interactions into structured intelligence. - [Read more](https://www.skan.ai/blogs/tag/work-telemetry) ### Workflow Automation Automates repetitive tasks and workflows using technology, such as AI and robotic process automation, aiming to increase productivity, reduce errors, and accelerate execution. - [Read more](https://www.skan.ai/blogs/tag/workflow-automation) ### Workforce Insights Data-driven analytics derived from Skan's process intelligence platform, providing valuable information about how employees work, measured through key metrics. ### Workforce Productivity Intelligence Uses process observation data to understand how work is performed across teams and identify efficiency improvements. Skan takes a privacy-first approach with all PII masked.