--- title: "Example Scenario: Choosing Charging Station Locations | x101" url: https://www.x101.ai/case-studies/charging-station-placement description: "How x101 turns EV charging site selection from a quarterly study into a conversation: demand, grid capacity, traffic, planning rules and cost read together, with ranked locations and the reasoning behind each." --- # Where to put the next charging station Example scenario · Energy · EV infrastructure > **This is an example scenario, not a customer deployment.** It shows how x101 capabilities apply to this kind of work. There are no customer-attributed figures on this page; outcome numbers are published only once they are measured in a live deployment. For deployments running today, see the [production case studies](https://www.x101.ai/case-studies#telecom). **Site selection answered in a conversation instead of a quarterly study.** x101 reads demand, grid capacity, traffic patterns, planning rules and cost data together, then ranks candidate locations and shows the reasoning behind each one. - **Function**: Network planning and capital allocation - **Systems**: Grid data, traffic and demand data, planning records, finance - **Deployment**: Any cloud, private cloud or on-premises - **Output**: Ranked sites with evidence, re-runnable on demand Last updated: 22 September 2026 ## The challenge Deciding where to build next means combining data that lives in different places and different formats. The analysis is expensive enough that it happens quarterly, which means the answer is often built on assumptions that have already moved. - **The analysis is a project, not a question**: Bringing grid, traffic, demographic, planning and cost data together takes weeks of specialist effort, so it happens on a fixed cycle rather than when a decision is needed. - **Assumptions age before the decision lands**: By the time a study is finished, grid upgrade schedules, competitor sites and demand patterns have shifted, and re-running the work is not practical. - **Reasoning is hard to interrogate**: An investment committee sees a ranked list, but tracing why one site outranks another means asking the analyst who built the model. - **Local rules are easy to miss**: Planning constraints, grid connection limits and site-specific restrictions live in documents that no spreadsheet reads. ## What x101 does The same platform capabilities that run in production elsewhere, applied to this work. Each step below is standard platform behaviour, not custom development. 1. **Every input in one place**. Grid capacity, traffic and demand data, demographics, existing and competitor sites, planning records and cost data are read together rather than merged by hand. 2. **Asked in plain language**. A planner asks the actual question, such as which five locations in a region give the best return within the current grid constraints, and x101 works out what to gather. 3. **Candidates ranked, with reasons**. Locations come back ranked, each with the factors that drove its position, the forecast utilisation behind it, and any constraints that would still need to be resolved. 4. **Local rules read, not assumed**. Planning documents, connection policies and site restrictions are read directly, and any blocking clause surfaces with the passage that says so. 5. **Re-run when anything moves**. A changed grid upgrade date or a new competitor site is a follow-up question, not a new study, and the ranking updates with the reasoning refreshed. 6. **Ready for the committee**. The output is an investment-grade summary with its sources cited, so the decision and its evidence travel together. > **Governance runs across every step.** Each request carries the permissions of the person asking, actions follow the policies you set, high-impact steps wait for human approval, and every decision is written to a signed, replayable record. ## What gets measured These are the measures a deployment of this scenario is held to. Figures are published on this page once a live deployment has produced them. ### Baseline and target Agreed before the first week - Elapsed time from question asked to ranked recommendation - Number of scenarios evaluated per investment decision - Utilisation of new sites against the forecast that justified them - Analyst effort per site evaluated ### How rollout works A first use case live in weeks - **Inside your perimeter.** Your cloud, your access controls and your data, from day one. - **Works with what you run.** x101 reads the systems you already have, as they are today. - **Paired with a solutions engineer.** Someone who has deployed this before works alongside your team. - **Measured against your baseline.** The numbers that matter are agreed up front and reported against. ## The parts of x101 this uses Every capability below already runs in production. This scenario applies them to a different kind of work. - **Unify**: Grid, traffic, demographic, planning and finance data read as one picture instead of five exports. [Explore](https://www.x101.ai/#unify) - **Agentic Orchestration**: Specialist agents work each source in parallel and converge on one ranked answer. [Explore](https://www.x101.ai/#orchestrate) - **Instant Analytics**: Demand and utilisation questions answered straight from live data, charted and explained. [Explore](https://www.x101.ai/#analytics) - **Deep Research**: Planning documents, market data and site records pulled together into a citable deliverable. [Explore](https://www.x101.ai/#research) - **AI Explainability**: Every ranking carries the factors that produced it and the sources behind them. [Explore](https://www.x101.ai/#explainability) - **No Vendor Lock-in**: Runs wherever the data is allowed to live, on any cloud or entirely on-premises. [Explore](https://www.x101.ai/#no-lock-in) ## Keep reading - [Zero-touch provisioning for radio sites](https://www.x101.ai/case-studies/ran-zero-touch-provisioning): New sites from installation to live traffic, configured and commissioned under approval. - [Payroll reconciled before it pays](https://www.x101.ai/case-studies/payroll-processing): Every run reconciled ahead of close, with the policy clause behind each deduction. - [Deployments running today](https://www.x101.ai/case-studies): Two Tier-1 telecom deployments with measured outcomes, and the rest of the scenario library. ## Make siting decisions on current data. Ranked locations with the reasoning shown, re-runnable the moment an assumption changes, built on the data you already hold. - [Book a demo](https://www.x101.ai/contact) - [Explore the Platform →](https://www.x101.ai/platform)