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Spranic is developing a persistent spatial record for changing physical spaces. The company says its alpha app turns a walk through a building into a living 3D map, keeps recognizable objects linked across visits, answers questions in plain language and reports what moved, appeared or disappeared. That could give people and robots a shared memory of a place instead of forcing each visit to start with an outdated map.
What is Spranic?
Spranic describes itself as “the data layer for physical AI.” Its central idea is a spatial record that can be revisited and updated as a real location changes. Conventional plans, inventories and robot maps can become stale or remain isolated in separate systems. Spranic’s proposed layer is intended to preserve the identity and location of objects over time, then show differences between captures.
The product is currently presented as an alpha rather than a broadly available commercial platform. Spranic’s homepage invites alpha users, pilots and partnerships. Its about page identifies Jordi Spranger as founder and describes an early rover that mapped an apartment, followed by a goal of reaching first pilot sites.
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1. Capture a space
Spranic says a user can walk through a location with a phone or a depth camera. The company’s demonstration uses a handheld depth camera, but its product description also names a phone as an option and does not specify a mandatory device model.
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2. Build a 3D map
The captured data is processed into a map that represents the space and recognized objects. Spranic states “72 s from walk to finished map” for its demonstrated capture. That is a company-provided demonstration figure, not an independently measured benchmark or a guaranteed processing time for every device, building or visit.
3. Revisit and compare
On later visits, new captures can be compared with the persistent record. Spranic says objects retain stable identities across visits, allowing the system to indicate what moved, appeared or disappeared rather than treating every scan as an unrelated map.
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4. Ask questions and receive a change report
The alpha app is described as supporting natural-language questions about the mapped space. Spranic also says it produces a change report after each visit, turning the spatial record into an operational view of what changed.
Can robots use Spranic’s spatial memory?
Robots are one of Spranic’s stated longer-term applications. The company describes a future in which robots retain bearings in changing spaces and fleets use a common spatial record. In practical terms, a robot could potentially consult the latest shared map instead of relying only on a one-time survey or a map stored on a single machine.
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That capability should be treated as a proposed direction, not a proven deployment. Spranic says it starts with buildings and lists robot fleet use as a subsequent direction. The official pages reviewed do not establish a customer robot deployment, an integration method, supported robot platforms, navigation accuracy or an independently validated performance result.
Where Spranic says the system could be used
| Area | Stated or proposed use |
|---|---|
| Construction | Track site conditions and document changes between visits. |
| Logistics | Maintain a current view of inventory and facility layout. |
| Manufacturing | Monitor equipment and spatial changes on a production floor. |
| Facilities | Support handovers, inspections and recurring building checks. |
| Service robotics | Help robots retain bearings as environments change. |
| Agriculture | Record changing physical conditions across repeated captures. |
| Retail | Track merchandise, fixtures and store-layout changes. |
Spranic summarizes these scenarios with examples such as inventory that counts itself, inspections that flag differences and handovers with proof. These are intended or proposed applications described by the company, not independently verified outcomes.
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What you need to capture a space
| Capture option | What is established | What is not stated |
|---|---|---|
| Phone | Spranic says a phone can be used to capture a space. | No supported phone models, operating-system versions or minimum sensor requirements are identified. |
| Depth camera | The homepage demonstrates a walk with a handheld depth camera. | No required brand, model, range, accuracy specification or purchase requirement is given. |
A dedicated depth camera is therefore optional according to the company’s description, not a documented prerequisite.
How mature is Spranic?
The available company material supports describing Spranic as an alpha- and pilot-stage effort. It does not establish general commercial availability, customer deployments, pricing, service-level commitments or independent performance validation. The pages also do not specify data-retention rules, privacy terms, detailed technical specifications or availability by country.
Those omissions matter because a persistent map of a building can contain sensitive information about rooms, equipment, stock and routines. Anyone evaluating a pilot should request written answers about storage location, retention and deletion, access controls, export formats, object-recognition errors, update frequency and how changes are handled when a capture is incomplete.
What to verify before a pilot
- Which phones and depth cameras are supported, and whether processing happens on the device or in a hosted service.
- How long a map remains usable and how the system resolves conflicting captures.
- Whether users can correct an object identity or remove sensitive areas.
- What robot interfaces, mapping formats or APIs are available.
- How the reported 72-second demonstration time changes with larger or more cluttered sites.
- What evidence exists from the first pilot locations, including error rates and operational recovery procedures.
The practical takeaway
Spranic’s distinctive proposition is not simply another one-time 3D scan. It is a persistent, shared spatial memory that is meant to connect people, software and eventually robots as a place changes. The alpha app reportedly captures a space with a phone or depth camera, creates a 3D map, supports plain-language questions and produces visit-to-visit change reports. Whether that becomes dependable infrastructure for physical AI will depend on device support, privacy controls, integrations and results from real pilot sites—details the company has not yet publicly established.
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