> For the complete documentation index, see [llms.txt](https://docs.lleverage.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lleverage.ai/understand-lleverage/operational-examples.md). # Operational examples Representative examples of recurring operational work in the language used by the companies Lleverage is built for. These examples show the kinds of recurring back-office work Lleverage can be configured to take on. They are intentionally non-exhaustive: the point is to use the language and process shapes our customers recognise, not to define a fixed capability catalogue. For the product model underneath these examples, see [What Lleverage is](/understand-lleverage/readme.md). ## Quote and sell Operational work around incoming commercial requests, quotations, tenders, pricing and order intake. Examples: * Read an incoming RFQ or RFP, identify requested products and prepare the information needed to price or respond. * Check customer-specific pricing or volume agreements before preparing a quote. * Turn an emailed purchase order into a structured sales order, asking a person when customer, product or pricing information cannot be resolved confidently. * Follow up quotations that have been open longer than expected. This work often combines interpretation, company-specific commercial context and system actions. Flexible cases may suit the [Agent](/run-operations/agent.md); repeatable intake paths may move into [Workflows](/build-and-improve/automate.md). ## Procure and receive Operational work between deciding what is needed and having the right goods available. Examples: * Forecast purchase requirements or prepare the next ordering decision. * Follow up suppliers for missing confirmations or delivery dates. * Compare a supplier confirmation with the purchase order and identify quantity, price or date differences. * Update expected delivery information when a supplier changes its commitment. * Match received goods against the purchase order and surface discrepancies that need attention. If the process needs a person to resolve an exception, that may surface as a [Request](/run-operations/request-inbox.md). ## Plan and produce Operational work involved in turning demand, material availability, engineering information and capacity into an executable plan. Examples: * Bring supplier delivery changes into a planning decision. * Identify orders or materials that threaten the current production plan. * Fit work into the available lines, shifts or weeks and surface conflicts. * Prepare the information a planner needs to replan around a disruption. * Consolidate spreadsheets and system data into a repeatable planning view. * Prepare work-preparation or engineering information for production. Planning is a useful example of where the right answer may be assisted or supervised rather than fully autonomous. See [From manual to autonomous](/understand-lleverage/readme/from-manual-to-autonomous.md). ## Store and ship Operational work around warehouse handoffs, freight, shipping, proof of delivery and trade documentation. Examples: * Prepare pick or shipment information from open orders. * Book freight or prepare carrier information from ERP and order data. * Generate transport or customs documents from information already available across systems. * Retrieve tracking or proof-of-delivery information and communicate shipment status. * Detect a delivery exception and route the right follow-up to a person or downstream system. A structured operator entry point into this work may be exposed as a [Workflow app](/run-operations/workflow-apps.md). ## Pay and collect Operational work around supplier invoices, matching, self-billing, cost allocation, payment preparation, receivables and dunning. Examples: * Extract an incoming invoice and compare it with the purchase order and goods receipt. * Route a price or quantity difference to the person who needs to decide it. * Allocate costs to the right order, project or account. * Prepare self-billing or payment-supporting information. * Identify overdue receivables and prepare or send the context needed for follow-up. A straightforward case may be handled automatically while exceptions remain supervised through [Requests](/run-operations/request-inbox.md). ## Support and enable Operational work that keeps the rest of the business moving but often depends on a small number of experienced people. Examples: * Handle requests to create or update customer, supplier or product master data. * Verify requested changes against available evidence before updating a system. * Answer internal operational questions using company knowledge and current system data. * Collect the information required for customer or supplier onboarding. * Maintain or retrieve procedural knowledge for people doing the work. These processes often combine [Skills](/build-and-improve/intelligence/skills.md), [Knowledge](/build-and-improve/intelligence/knowledge.md), [Tables](/build-and-improve/intelligence/tables.md), [Files](/build-and-improve/intelligence/files.md) and external [Connections](/administer-and-govern/control/connections.md). ## The same operation can be implemented differently Two companies may have the same operational job but need very different implementations. One may have clean ERP data and a highly repeatable path that suits a Workflow. Another may receive inconsistent documents, rely on experienced judgement and need an Agent with deliberate human handoffs. A third may use both. The starting point is the work the business needs to get done. The platform constructs are how that work is executed. ## Where to go next * To understand the execution model, see [Humans, Agent and Workflows](/understand-lleverage/readme/humans-agent-and-workflows.md). * To use existing operational capabilities, go to [Run operations](/run-operations/overview.md). * To build repeatable execution, go to [Automate](/build-and-improve/automate.md). * To configure reusable context and methods, go to [Intelligence](/build-and-improve/intelligence.md). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.lleverage.ai/understand-lleverage/operational-examples.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.