Geospatial and GeoAI consulting
We help data and AI leaders decide where spatial context can improve their AI systems and business operations. We then define what data and technical work are needed to put that strategy into practice.
Services
Geospatial engineering and GeoAI strategy.
LakeGeo advises organizations on GeoAI strategy and builds production geospatial pipelines in their cloud environments.
What we do
Two ways to work with LakeGeo.
We help teams decide where spatial context belongs in their systems and build the production pipelines that put that strategy into operation.
Production pipeline delivery
We design and implement geospatial pipelines in your cloud environment. Your team receives the production code, operating documentation, and governed output tables.
Pipeline delivery process
From written scope to working pipeline.
For implementation work, we agree on the output and acceptance criteria before the build begins. The work is complete when the pipeline is running and your team can operate it.
01
Define the work
We identify the business decision the pipeline must support, confirm the available source data, and specify the output. The scope includes clear acceptance criteria before implementation begins.
02
Build the pipeline
We implement one end-to-end production pipeline in your cloud environment. Scheduling, checkpoints, and run reporting are part of the initial build.
03
Validate the output
We compare the results with an agreed source of truth. For an insurance risk pipeline, that may be your loss history for the same place and period. The pipeline is accepted when it meets the criteria set during scoping.
04
Transfer operations
The code is committed to your repository. We document how the pipeline runs, record known failure cases, and work with your engineers until they can operate it directly.
Data and operations
Your data stays in your environment.
The pipeline is built on your cloud platform and follows the controls already in place there.
Runs in your cloud account
The pipeline uses compute and storage in your environment. LakeGeo does not copy your source data or pipeline outputs into its own systems.
Produces governed outputs
The pipeline writes controlled, versioned tables with lineage. Reviewers can trace an output to the source data, imagery date, and model version that produced it.
Supports analysis and applications
Analysts and downstream applications use the same governed output tables. This keeps operational tools aligned with the data reviewed in SQL.
Reports operational performance
Each run records processing volume, runtime, rows written, and estimated cost. Checkpoints allow interrupted jobs to resume from completed work.
Engagement model
A project your team takes over.
Project delivery
Consulting and implementation work is scoped as a project. There is no LakeGeo platform subscription or per-seat licence.
Open architecture
The Geospatial Lakehouse Architecture is free to read and implement. Customers hire LakeGeo for advice, delivery experience, and technical execution.
Customer ownership
Your team receives the agreed project deliverables. Implementation code is committed to your repository, with the documentation needed to operate it.
Start a project
Talk to us about your geospatial or GeoAI work.
Tell us where geospatial work fits into your business. We can help set the strategy or take a pipeline into production.