Platform in active development

Geospatial work, redesigned for the AI era.

Sprouti is building a cloud platform where teams can discover spatial data, ask questions in natural language, construct reproducible workflows, run Python, and publish interactive outputs from a secure workspace that can be deployed in the cloud, a private network or the customer’s own environment.

AI workflow readySpatial intelligence workflow
Spatial sandboxPython · PostGIS · MapLibre
AI-firstNatural-language spatial workflows
Deployment choiceCloud, private cloud or local environments
Open stackPython, PostGIS and MapLibre
Built for impactGovernment, research and industry
Why Sprouti

One environment from data to decision.

Geospatial teams often move between desktop GIS, notebooks, databases, cloud services and custom applications. Sprouti is designed to connect those stages without removing expert control.

Understand data faster

Profile layers, enrich metadata and let users explore datasets through maps, filters and natural-language questions.

Build repeatable workflows

Combine approved tools, SQL, geoprocessing and custom Python into inspectable workflows that can be reused and shared.

Publish useful outputs

Turn results into maps, dashboards, APIs and applications without rebuilding the infrastructure for every project.

Interactive preview

See how the workflow fits together.

Select a stage to preview Sprouti’s intended user journey.

Data intelligence

Connect spatial data with context

Register files, APIs and spatial databases. Sprouti profiles schema, geometry, CRS, fields and analytical capabilities so people and AI tools can use the data safely.

Source: Operational asset dataset
Geometry: Mixed spatial features
Coverage: Regional
Fields: category, condition, priority, status
Status: approved for analysis
AI assistant

Translate intent into a reviewable plan

Users describe an outcome. The assistant identifies suitable layers, proposes filters and tools, and produces a workflow for approval before execution.

User: Identify priority assets near critical infrastructure

Plan:
1. Filter assets by condition and priority
2. Define the relevant proximity zone
3. Intersect candidate features
4. Visualise results by priority
Controlled execution

Run geospatial analysis in secure sandboxes

Execute approved workflows using database operations, platform tools or custom Python, with resource tracking, logs and reproducible outputs.

def analyse(assets, infrastructure):
  priority = assets[assets.priority == "high"]
  nearby = spatial_join(priority, proximity(infrastructure))
  return nearby.sort_values("condition")
Delivery

Move from result to application

Publish outputs to an interactive map, dashboard, API or scheduled workflow while retaining provenance and access controls.

Output: Prioritised spatial insights
Delivery: Interactive map + data API
Refresh: Configurable
Audience: Authorised project users
Provenance: Versioned workflow
Private GeoAI

Use AI without surrendering control of your spatial data.

Sprouti is being designed for organisations that cannot send sensitive geospatial information to uncontrolled public AI services.

Deploy where your data lives

Run Sprouti in a managed cloud environment, private cloud, on-premises infrastructure or a restricted local network. Local deployments can keep data and model processing inside the organisation’s security boundary.

No training on customer data

Customer datasets, prompts, workflows and outputs will not be used to train shared Sprouti models or sold to third parties. Model providers can be selected to support private or zero-retention processing.

Controlled and auditable

Role-based access, project isolation, encrypted connections, approval-led execution, audit logs, resource controls and configurable retention support governed GeoAI workflows.

Build with us

We are seeking pilot organisations, grant partners and early supporters.

Engage now to help validate priority workflows, contribute expertise, support development or explore future investment.