Skan AI for Enterprise Agentic AI # Your agents are only as good as the context they run on Skan AI captures the operational context agents need to deliver productivity gains, cost savings, and business transformation at scale. [Request a demo](/request-demo) ![Enterprise Agentic](https://cdn.sanity.io/images/3xg3qj5k/production/5d0c4e30cc5e9b845e73128db691bf374e386d5d-1296x1322.jpg?q=80&fit=max&auto=format) Most enterprises have an AI mandate. But 80% of agentic AI pilots stall, not for lack of capability, but for lack of process context. Most enterprises have an AI mandate. But 80% of agentic AI pilots stall, not for lack of capability, but for lack of process context. ## What successful AI deployment looks like ![Opportunity Analysis Breakdown](https://cdn.sanity.io/images/3xg3qj5k/production/135d45adaa9f802c30bf7c817fcc38e35074f3ac-759x656.svg) Identify the right opportunities Focus AI investment on the workflows where it can create the greatest business impact. Build on operational reality Give agents the verified context they need to handle exceptions, adapt to real workflows, and perform reliably, without wasting capacity on unstructured data. Deploy with confidence Launch agents with the context, controls, and enterprise security your environment demands, including governance, audit trails, and data that stays inside your network. Measure AI impact Track adoption, productivity gains, and business outcomes across every deployment. What it takes to deploy enterprise agentic AI that actually works ## What it takes to deploy enterprise agentic AI that actually works - Observe - Strategize - Deploy - Measure Before you deploy agents, you need to understand how critical workflows actually run. Skan AI captures the steps, decisions, exceptions, and rework driving cost and complexity across the enterprise. - [Discover Process Intelligence](/process-intelligence) ![Media Placeholder](https://cdn.sanity.io/images/3xg3qj5k/production/0d813652e5913fb0e895946f36ae6923b41454cd-1968x1018.avif?q=80&fit=max&auto=format) - Observe work across applications, teams, and systems - Map end-to-end workflows, including exceptions and rework - Maintain a continuously updated view of operations Prioritize the workflows where agents can deliver the greatest productivity gains, cost reduction, and business impact. - [Explore Blueprint](/blueprint) - ![Classify work](https://cdn.sanity.io/images/3xg3qj5k/production/d7c2b94d18a2c2a5567309b1cb3bade6768b8d63-296x238.svg) Classify work based on its nature and complexity - ![Rank AI](https://cdn.sanity.io/images/3xg3qj5k/production/742f6c8d418b4157aebfbacaa7a7a47f971747d3-294x268.svg) Rank AI opportunities by business impact - ![roadmap](https://cdn.sanity.io/images/3xg3qj5k/production/4ef65868371a7206ace4de36cd8dce0e1872e91b-303x299.svg) Build a roadmap with measurable ROI at every stage Move beyond simple pilots and deploy agents into the complex, cross-functional workflows that drive real business outcomes. - [Deploy Agents](/agents) ![Building agent](https://cdn.sanity.io/images/3xg3qj5k/production/ff7793abc9230d7987bef34d47028327e7f301ab-984x509.svg) - Create Agents from real workflows, not generic templates - Deploy and govern agents on a shared operational model - Keep humans involved where judgement and oversight matter Skan AI measures every agent’s impact against the business KPIs that matter most, helping teams prove value, optimize performance, and scale adoption with confidence. - ![Track agent](https://cdn.sanity.io/images/3xg3qj5k/production/9c8b7644ea13dada88aaff6b6fae43428eaafc53-328x294.svg) Track agent performance against operational KPIs - ![Measure productivity](https://cdn.sanity.io/images/3xg3qj5k/production/d0c0a19ee7a07bf532893f701ec0ed5a7d179228-296x294.svg) Measure productivity, quality and business impact over time - ![Continuously improve agents](https://cdn.sanity.io/images/3xg3qj5k/production/676ee763e606b96f5a003a7cf8200ee11f7672ed-271x294.svg) Continuously improve agents through observed outcomes [ $30M $30M savings through beneficiary maintenance process standardization and automation ](/case-studies/global-banking-leader-partners-with-skan-to-improve-beneficiary-maintenance-process)[ $15M $15M savings realized across claims and contact center operations ](/case-studies/improving-first-call-resolution-at-a-leading-healthcare-payer) ## What enterprise leaders
say about Skan AI [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) ## One platform. More to Skan. Enterprise agentic [ ![Enterprise agentic Slider Image](https://cdn.sanity.io/images/3xg3qj5k/production/d82faeb50e3f61f74f52ac292517d282e605f259-1072x928.png?q=80&fit=max&auto=format) ](/use-cases/enterprise-agentic) Once the process is optimized, your Agents have a proven model to learn from. Process improvement and Agents run on the same Context Graph. [Learn more](/use-cases/enterprise-agentic) Reduce cycle time, exception rates and the cost of getting work done. [Learn more](/use-cases/operational-excellence) Reduce cycle time, exception rates and the cost of getting work done. [Learn more](/use-cases/automation-discovery) Once the process is optimized, your Agents have a proven model to learn from. Process improvement and Agents run on the same Context Graph. [Learn more](/use-cases/enterprise-agentic) Frequently asked questions ## Frequently asked questions Why do enterprise AI initiatives struggle to scale? Enterprise AI initiatives often struggle to scale because they lack process context. Without visibility into how work is performed across systems, teams, and workflows, AI agents find it hard to handle exceptions, adapt to operational complexity, and deliver consistent business outcomes. How are AI agents deployed successfully in enterprise environments? Successful enterprise AI deployments begin with an accurate understanding of how work is performed. Agents need operational context to make decisions, navigate exceptions, and operate effectively across complex, cross-functional workflows. Do AI agents need to be built from scratch? Not always. Many organizations start by identifying high-value workflows and then configuring or adapting agents to those processes. The most effective deployments are grounded in observed operational reality rather than assumptions, static documentation, or generic templates. How can enterprises govern and oversee AI agents? AI governance requires visibility into how agents perform, where they create value, and how decisions are made. Effective oversight combines performance monitoring, business outcome tracking, auditability, and human review where appropriate.