Custom Geospatial Software Development

While it varies based on complexity, a typical custom geospatial application from us ranges from $75,000 to $250,000. This is a one-time investment. Unlike off-the-shelf software with recurring annual fees of $20k-$100k+, you own the final product. We find most clients achieve a full return on their investment within 18-24 months through reduced licensing costs and significant operational efficiency gains, making it a more financially sound long-term decision.

Our typical development lifecycle for a production-ready custom GIS application is 12-20 weeks. We prioritize delivering a Minimum Viable Product (MVP) quickly, often within the first 8-10 weeks, so you can start getting value and providing feedback. This agile approach, focused on your core needs, means you get a working solution much faster than you would with a traditional, large-scale enterprise implementation that can take over a year to configure and customize.

Both. We are tool-agnostic and choose the right technology for the job. We have deep expertise in building solutions on top of the Esri stack (using ArcGIS Enterprise, ArcPy, and the JS API) for clients heavily invested in that ecosystem. However, we also have extensive experience building highly scalable, cost-effective solutions using open-source technologies like PostGIS, GeoServer, and OpenLayers. Often, the best solution is a hybrid approach, and we'll help you determine the most effective and efficient technology stack for your specific budget and goals.

Absolutely. This is one of our core strengths. We believe the true power of geospatial data is unlocked when it's connected to your core business operations. We build robust, two-way integrations between your geospatial platforms and systems like ERPs (SAP, Oracle), CRMs (Salesforce), and Enterprise Asset Management (EAM) systems (Maximo). This ensures data consistency and allows you to build powerful, cross-functional workflows, such as automatically triggering a maintenance work order in your EAM from a GIS-based inspection app.

Yes. We recognize that clean data is the foundation of any successful GIS. A common first step in our engagements is a data audit and the creation of automated 'Spatial ETL' (Extract, Transform, Load) pipelines. We build scripts to clean, validate, and standardize your disparate datasets into a single, analysis-ready format. This often involves migrating data from legacy formats (like shapefiles or CAD) into a modern, robust spatial database like PostGIS. We fix the data problem first, so your new tools can deliver reliable insights.

We specialize in automating the 'field-to-finish' workflow for surveyors. We can build custom mobile apps for field data capture that enforce your firm's standards, and backend automation to process instrument data, perform adjustments, and generate draft survey plans and reports automatically. Our goal is to free up your licensed surveyors from tedious data wrangling and drafting, allowing them to focus on high-value QA and client management. We've helped firms reduce plan preparation time by over 80%.

Surveying is the precise science of measuring and recording the positions of points on the Earth's surface. It's about creating highly accurate data. GIS (Geographic Information System) is the system used to capture, store, analyze, manage, and visualize that data, often in the context of other information. Think of it this way: a surveyor creates the foundational, high-accuracy data, and a GIS is the powerful platform to analyze that data and reveal deeper patterns, relationships, and trends.

AI and ML are revolutionizing geospatial analysis. We use these technologies to automate tasks that were previously impossible to do at scale. For example, we can train a model to automatically detect and classify objects (like swimming pools, solar panels, or specific tree species) from aerial or satellite imagery. We can use ML for predictive modeling, such as identifying areas at high risk for landslides or forecasting crop yields based on historical data. This turns massive datasets into proactive, intelligent insights.

A geospatial Digital Twin is a dynamic, virtual 3D model of a physical asset, area, or system that is updated with real-time data. It's more than just a static 3D model; it's a living replica. For example, a digital twin of a city could integrate real-time traffic flow, weather data, and utility sensor readings. This allows you to simulate the impact of a new development, model emergency response scenarios, or predict maintenance needs on infrastructure. We build these twins by fusing together BIM, CAD, LiDAR, and IoT data.

Yes, 100%. We have extensive experience working with Australian clients and standards. All our systems are designed to be compliant with the Geocentric Datum of Australia 2020 (GDA2020) and associated MGA2020 grid. We handle all necessary coordinate transformations to ensure your data is accurate and interoperable. We also build in accordance with the Australian Privacy Act and can deploy solutions onshore to meet data sovereignty requirements.

You might, if your needs are very generic. However, off-the-shelf products often force you to change your workflow to fit the software, and you end up paying for dozens of features you'll never use. If you have a specific, high-value workflow you want to optimize, or a unique integration need, a custom solution almost always provides a better long-term ROI. It's the difference between buying a generic suit and getting one tailored to you. One fits okay, the other fits perfectly.