Pi by Placer.ai
Placer.ai v1.0.1
Publisher description
From the marketplace listing
Placer.ai Pi answers business questions that turn on measured real-world behavior. Ask a full analytical question in plain language and Pi runs a complete Placer.ai analysis - foot traffic trends, visitor demographics and journeys, trade areas, cross-shopping, and sales and spend - then returns a written answer with data-honesty caveats, any web sources it used, and a deep link that opens the same analysis, with its interactive map, in Pi. A full analysis normally takes several minutes: ask_pi starts it and returns a handle, and get_pi_result collects the answer, reporting progress while the work runs. Typical workflows include store and portfolio performance, trade-area and site analysis, competitive benchmarking, tenant mix and co-tenancy review, market feasibility, and category or market-share tracking. Follow-up questions can reuse a previous analysis so the numbers stay consistent across a conversation. Access requires a Placer.ai account with Pi and the MCP access entitlement; Pi returns only the data the signed-in Placer user is entitled to see.
Language: English · Automatically detected from descriptions.
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Publisher description
Placer.ai Pi answers business questions that turn on measured real-world behavior. Ask a full analytical question in plain language and Pi runs a complete Placer.ai analysis - foot traffic trends, visitor demographics and journeys, trade areas, cross-shopping, and sales and spend - then returns a written answer with data-honesty caveats, any web sources it used, and a deep link that opens the same analysis, with its interactive map, in Pi. A full analysis normally takes several minutes: ask_pi starts it and returns a handle, and get_pi_result collects the answer, reporting progress while the work runs. Typical workflows include store and portfolio performance, trade-area and site analysis, competitive benchmarking, tenant mix and co-tenancy review, market feasibility, and category or market-share tracking. Follow-up questions can reuse a previous analysis so the numbers stay consistent across a conversation. Access requires a Placer.ai account with Pi and the MCP access entitlement; Pi returns only the data the signed-in Placer user is entitled to see.
Files & skills
File archives
Package details
Publisher declarations from the archived package. These are separate from our research and the live service's terms.
- Package author
- Placer.ai
Package observed Oct 5, 2026.
Technical details
- First seen
- Sep 30, 2026 · 22:02 UTC
- Last seen
- Oct 6, 2026 · 12:00 UTC
- Collection status
- Collected
plugin_asdk_app_6a7b5a0c6f5c8191978777f40f445540
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