Examples of using Placepoint AI

The reports below were made with Placepoint AI by our users, from a single prompt each. They show the range: from a lookup on one property to analyses of entire streets and portfolios. If you want to start with something short, go straight to the example prompts at the bottom of the page.

Area analysis: a whole street in one prompt

The prompt "Check the whole of John Colletts allé, where can you build new, make a report" produced a 15-page report: all 72 land properties in the street reviewed, with a map and an assessment for each address.

The report found that the street is in practice three different planning realities, and that four addresses in the middle of the street are not covered by the building ban that stops all the neighbours. That exception is not in any map database: Claude found it by reading the planning documents and the decision on the extended building ban. The requirements are in the provisions, not in the colours on the zoning map. The method section lists which planning documents were actually read, and separates a documented gap in coverage from missing analysis. The same plans are in the zoning map layers in Placepoint Fusion.

Front page	Summary	Zoning map

The full report can be downloaded: John Colletts allé - zoning analysis (PDF, 15 pages).

More reports and analyses

• A 25-page sustainability report for a well-known head office in Oslo: matrikkel, BREEAM certification, ownership structure, all 25 tenants with a company dossier, registered ownership history, maps and a travel time isochrone.
• An 11-page due diligence report with legal, technical and financial screening, which clearly marks what is covered and what is not.
• A climate risk report as a PDF magazine with physical risk, transition risk and biodiversity, built on the same sources as the risk map layers, and a credit report for a bank made the same way.
• A buyer assessment where Claude, from a completely neutral prompt, concluded that the risk was high because the buying company was in an ongoing court case.
• A mass scan of land registers for a whole facility: Claude found all the matrikkel numbers itself, retrieved the extracts together and summarised the encumbrances that could block development.
• A lead list for a roofing contractor: 1,517 properties identified and filtered on year of construction and building type, linked to the owning company and combined with visual roof analysis of buildings from aerial photos. The same kind of selection that Filter gives you in Placepoint Fusion.

Plot subdivision: which plots are large enough

The question "Which plots in Bergsalléen in Oslo are large enough to be subdivided?" gives the answer in two parts: the rules that govern subdivision right now (area requirement per dwelling unit, %-BYA and the temporary ban with exceptions), and a table of the properties in the street that meet the area requirement, with matrikkel number and plot area. The answer is clear about what must be checked in detail with Plan- og bygningsetaten (the city planning and building authority) before an actual subdivision application.

This answer is from the Agent in Placepoint Fusion, which uses the same engine as Placepoint AI in Claude. The questions below work in both places:

• "Check the whole of John Colletts allé, where can you build new, make a report."
• "Which plots in Bergsalléen in Oslo are large enough to be subdivided?"
• "Has any planning work been announced near Bergsalléen?"

Short example prompts

Placepoint AI takes both short questions and complex tasks: one lookup on an address, or a whole street with a report at the end. The examples below are easy to write and still use a lot of Placepoint at once: the registers, the map layers and the analyses in the same answer. Feel free to start with "Use Placepoint MCP", write in the language you use yourself, and replace the square brackets with a real address, a matrikkel number or an organisation number:

• "Retrieve the land register extract for [matrikkel number] and summarise which encumbrances are on the property."
• "Check whether the property [matrikkel number] is in a flood or landslide exposed area, and show it on a map."
• "Which zoning plans and municipal plans apply to the property [matrikkel number]?"
• "Check the whole of [street]: where can you build new? Make a report."
• "Which plots in [street] are large enough to be subdivided?"
• "Has any planning work been announced near [address]?"
• "Retrieve the provisions and the planning description for the plan that applies to [matrikkel number], and summarise what is allowed in terms of land use ratio, heights and purpose."
• "Show all historical aerial photos around the property [matrikkel number], set up neatly with metadata."
• "Find the best places to set up a new grocery store near [place]."
• "Make a risk report for [address]."
• "Make a risk assessment of organisation number [orgnr] as the buyer of the property [matrikkel number]."
• "Make a portfolio report on all the properties [company] (organisation number [orgnr]) owns in [place/area]."
• "Make a full portfolio overview for organisation number [orgnr]: all properties with geography and a map of the main cluster, ownership structure from the ultimate owner down to the SPVs with flags for deleted companies and companies with negative equity, all tenants per building with how long each tenant has been registered, and an ESG profile per building."
• "Find the 10 best premises for a distribution centre for a company that has to make deliveries physically in [area], ranked by driving time."
• "How many active properties are there in [kommune]?"
• "Which properties does Equinor rent in [kommune]?"
• "Show detached house density in [kommune] as a map."
• "Export all properties with tenants in [kommune] to a spreadsheet."
• "Make a ranked list of commercial properties in [kommune] with only one tenant, where the tenant has weak finances."

With Placepoint Dataset MCP, which works with the datasets in your projects:

• "Make a dataset in the project [project] with all commercial properties over 5,000 m² in [kommune], with owner and year of construction."
• "Upload our tenant list, link the rows to the matrikkel on address and show which ones got no match."
• "Add kommune and grunnkrets (basic statistical unit) to each row in [dataset], and count rows per kommune."
• "Which properties in [dataset] have a new title holder or a new mortgage in the past year?"
• "Find the shortest route that visits all the points in [dataset] by car from [address]."
• "Set the colour on [dataset] by year of construction, and hide the columns we do not use."

Three of the prompts only work in Claude Desktop, Claude Code and Cowork: historical aerial photos, density maps and export to a spreadsheet. The Agent makes neither images nor files, so there the answer comes as text and map links. The reports and maps are built on the same sources as the rest of Placepoint Fusion: see Data and sources and Placepoint in numbers.