Agents ![Ai Agents Icon](https://cdn.sanity.io/images/3xg3qj5k/production/76a201a10fed38d4ef6f9930e40657a4be7d3e18-31x30.svg) # Turn real work into AI that works Skan AI observes how your teams actually work, identifies the ideal path through every process, and deploys agents built to run it at mission-critical scale. [Request a demo](/request-demo) Most AI agents are trained on generic data or manually written playbooks. The result is an agent that knows the happy path and nothing else. ## Skan AI Agents are built on reality, not assumptions ![Icon Box 1](https://cdn.sanity.io/images/3xg3qj5k/production/e8605089e46c0bd0fdd99f3db3ab303bc9e316e6-45x46.svg) ### The ideal path, identified from real work Skan AI observes how your best teams handle decisions, exceptions and complex workflows. From that evidence, it identifies the ideal path for an agent to execute and builds the agent around it. ![Icon Box 2](https://cdn.sanity.io/images/3xg3qj5k/production/e8605089e46c0bd0fdd99f3db3ab303bc9e316e6-45x46.svg) ### You control the agent Define where humans review, approve or take over. Set policies, guardrails and system access, all through configuration that stays under your control. ![Icon Box 3](https://cdn.sanity.io/images/3xg3qj5k/production/e8605089e46c0bd0fdd99f3db3ab303bc9e316e6-45x46.svg) ### Built and tested for mission-critical scale Skan AI agents execute repeatable work deterministically, with governed reasoning applied only where judgement is required. Durable execution keeps workflows resilient as they scale. ## From real work to working agents ![people](https://cdn.sanity.io/images/3xg3qj5k/production/2f4f038c02ac1881a465345c5511462e935ff647-1518x1400.jpg?q=80&fit=max&auto=format) Observe A lightweight sensor captures real human work across every app. The shortcuts, the exceptions, the judgement that never makes it into an SOP. 1. Observe A lightweight sensor captures real human work across every app. The shortcuts, the exceptions, the judgement that never makes it into an SOP. 2. Model Skan turns thousands of observed cases into an Agent Operating Procedure. The decision logic, exception handling and ideal execution path, built from evidence rather than workshops. 3. Deploy Build agents from observed patterns, business rules and pre-trained skills. Define approvals, guardrails and system access through configuration, not code. 4. Run and improve Agents execute on a durable workflow engine built for production scale. Every action is traceable to the work it was modeled on, and improves as observation continues. Insurance Financial Services Healthcare Deploy agents for Claims Adjudication Contact Center Policy Underwriting Compliance Claims FNOL From observation to automation ## From observation to automation ## Observe how work gets done across systems, teams and exception paths [Learn more](/process-intelligence) Lightweight sensor captures screens Every app, every exception path No integrations required ![Observe how work actually happens across systems, teams and exception paths](https://cdn.sanity.io/images/3xg3qj5k/production/687ae6052cb020c613acf662d12faa5560cc09c2-759x621.svg) ## Turn observed work into the ideal path for an agent to execute ![Ideal Path](https://cdn.sanity.io/images/3xg3qj5k/production/46953bfd50110639391c8f6d20e9781564969162-660x415.svg) The ideal path, encoded Process-specific detail Decision logic and exceptions ## Deploy agents with controls you define ![Deploy agents](https://cdn.sanity.io/images/3xg3qj5k/production/bf08b4ab22050c6cdcfa87fc7fb2ffd4a8b4c686-660x413.svg) Human in the loop Policies and guardrails Scoped enterprise access ## Monitor every agent action, escalation and decision path Every action traceable to evidence Real-time monitoring Compliance controls built in ![person](https://cdn.sanity.io/images/3xg3qj5k/production/b32e72658d34549b43cde9558915b44b7e085a11-1518x1242.jpg?q=80&fit=max&auto=format) ## Built and tested for workflows the business cannot afford to drop Deterministic-first execution Governed reasoning, only where it's needed Durable, fault-tolerant workflows ![Built and tested for workflows the business cannot afford to drop](https://cdn.sanity.io/images/3xg3qj5k/production/b207e36e91218b282c58521faafc9f78cf96bf88-759x621.svg) Agents, purpose-built for regulated industries ## Agents, purpose-built for regulated industries ![AICPA SOC 2](https://cdn.sanity.io/images/3xg3qj5k/production/e9dfe1696393993e1bdc9b8f30700cd0797ccce5-120x120.svg) ![AICPA SOC 2](https://cdn.sanity.io/images/3xg3qj5k/production/e9dfe1696393993e1bdc9b8f30700cd0797ccce5-120x120.svg) ![ISO Logo](https://cdn.sanity.io/images/3xg3qj5k/production/d62d105ab784e91f1801a1ab9f82dcfedb9c70c7-118x120.svg) ![ISO Logo](https://cdn.sanity.io/images/3xg3qj5k/production/d62d105ab784e91f1801a1ab9f82dcfedb9c70c7-118x120.svg) ## Meet the Context Graph of Work. A structured, living model of how your enterprise actually operates, built from real observation. [How the Context Graph works](/context-graph-of-work) ## The enterprises already building tomorrow [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 We needed to understand what we were automating before we automated it. 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. Blueprint [ ![Your AI masterplan](https://cdn.sanity.io/images/3xg3qj5k/production/33ba832e4a26326626c548e23e88a16d205e6896-536x464.svg) ](/blueprint) Your AI masterplan Recommendations, roadmaps and ROI. [Learn more](/blueprint) See where engineering value is built Signals, patterns and productivity, across the full developer day. [Learn more](https://skanai.bytogether.agency/tbc) Observe how work really works Maps, metrics and opportunities, built from
real work. [Learn more](/process-intelligence) Your AI masterplan Recommendations, roadmaps and ROI. [Learn more](/blueprint) Frequently asked questions ## Frequently asked questions What makes an enterprise AI agent successful? Successful enterprise AI agents are built on a deep understanding of real operational workflows, business rules, decision paths, and exception handling. Agents perform best when they are grounded in how work actually happens rather than relying solely on documentation or predefined process maps. What is an Agent Operating Procedure? An Agent Operating Procedure is a structured model of how an AI agent should perform a workflow, including the steps, decisions, rules, and exception paths required to complete work safely and effectively. It serves as the operational blueprint for agent execution. How should organizations govern AI agents? AI governance typically includes human oversight, approval workflows, access controls, auditability, policy enforcement, and operational guardrails. Effective governance ensures agents operate safely while remaining accountable to business and compliance requirements. What is human-in-the-loop AI? Human-in-the-loop AI is an approach where people remain involved at key decision points, approvals, or exception scenarios. Rather than fully replacing human expertise, it combines automation with oversight to improve accuracy, trust, and operational control.