Skan AI For Automation Discovery # Take control of your automation roadmap with a complete view of work Process interviews and documentation give you a roadmap built on guesswork. Skan AI observes how work actually happens, so you know where to automate, what to prioritize, and what it's worth. [Request a demo](/request-demo) Most transformation teams pick what to automate through workshops, interviews, and best guesses. The result is a roadmap shaped by recent memory, not by where the biggest opportunities are. Most transformation teams pick what to automate through workshops, interviews, and best guesses. The result is a roadmap shaped by recent memory, not by where the biggest opportunities are. ## Map your path to automation ROI with facts, not assumptions ![temp](https://cdn.sanity.io/images/3xg3qj5k/production/33847c5f9c5c737fb90706217d6a1c48983e7fa9-889x769.svg) Get a complete view of existing work Traditional process discovery and system logs show only 20% of work activity. Work observation captures how work gets done, across applications and teams. Establish baselines for performance Without standards in place, automation can scale broken processes and technical debt. Establish metrics for performance across all process variants to define success. Identify high-priority targets for automation With a complete view of work, identify high-volume tasks ripe for standardization. Then prioritize and execute automation based on projected business impact and ROI. Optimize tasks and deploy AI agents Continuously set new baselines for manual and automated work. Use insights to further optimize workflows, create operational context, and deploy AI agents. How Skan AI turns automation discovery into data-driven transformation ## How Skan AI turns automation discovery into data-driven transformation - Scan Work - Distill Insights - Deploy Agents Across mainframes, virtual desktops, and web apps, capture real work wherever it happens with zero integration and complete privacy. - [Discover Blueprint](/blueprint) ![Media Placeholder](https://cdn.sanity.io/images/3xg3qj5k/production/9e8c33cf6cad3e4b73e444fdd4a92fef519c90a5-984x504.svg) - Set your automation and AI posture to conservative, moderate, or aggressive. - Classify work: execution, comprehension, creation, decision, or communication. - Get a dollar-quantified roadmap of your automation opportunities. Understand all the process variants across your organization and match every automation opportunity to the best-fit approach. - [Explore Process Intelligence](/process-intelligence) - Run model-based complexity scoring of all your automation opportunities. - Score each task by automation fit, what to automate, augment, or keep human. - Analyze process variants to determine the best workflows to build, automate, and scale. Move from a prioritized automation roadmap to building production-ready AI, with agents trained on observed work. - [Deploy Agents](/agents) ![Media Placeholder](https://cdn.sanity.io/images/3xg3qj5k/production/ff7793abc9230d7987bef34d47028327e7f301ab-984x509.svg) - Begin executing your roadmap, starting with 90-day wins and working up to 12-month goals. - Prove transformation ROI with pre- and post-automation KPI tracking, backed by work observation data. - Continuously rescore your operations to establish new baselines and surface areas your AI agents can optimize. 37% 37% Average reduction in processing times 20% 20% Average decrease in manual errors 26% 26% Average increase in productivity ## The enterprises already scaling with proven ROI [See all stories](/case-studies) [ ![Definiti - Map the work. Then automate it | Client Success Story](https://cdn.sanity.io/images/3xg3qj5k/production/da847716989e8a92d985d7aeb057d4cc869e8c1b-984x549.jpg?q=80&fit=max&auto=format) 14,000+ 14,000+ hours/year of automation-ready effort Before, it was turn on AI and hope. Now we know exactly which processes to automate, what we'll save, and how to prove we got there. Jennifer Redden Head of Technology ![Definiti](https://cdn.sanity.io/images/3xg3qj5k/production/4bd9a3daea270bb97b789fc4d776f8a1d415d1e1-224x28.png?q=80&fit=max&auto=format) ](/case-studies/definiti-map-the-work-then-automate-it) ## More to Skan Operational excellence [ ![Next Up Placeholder](https://cdn.sanity.io/images/3xg3qj5k/production/61a428c900bfd7f84cb8f0f1c7aff0539e36822b-1072x928.png?q=80&fit=max&auto=format) ](/use-cases/operational-excellence) Reduce cycle time, exception rates, and the cost of getting work done. [Learn more](/use-cases/operational-excellence) Build, deploy, and scale enterprise AI agents trained on real work. [Learn more](/use-cases/enterprise-agentic) Measure and increase real productivity across your entire operation. [Learn more](/use-cases/productivity-optimization) Reduce cycle time, exception rates, and the cost of getting work done. [Learn more](/use-cases/operational-excellence) Frequently asked questions ## Frequently asked questions How is Skan AI’s approach to automation discovery different from process mining? Process mining reads system event logs, while Skan AI observes the actual work. This means the Skan AI platform captures everything happening outside of integrated systems, including the task switching and handoffs that are handled within and between Excel, email, and legacy mainframes. Can the Skan AI platform capture work data in legacy and mainframe systems? Yes, Skan AI uses computer vision to observe any application your team uses, without requiring APIs or any other integration methods. How fast can we get a prioritized automation roadmap? Most engagements produce dollar-quantified opportunities within 2-3 weeks, instead of in months with traditional methods.