Repeatable work, visible controls

GIS Automation and ETL Workflows

We deliver end-to-end web solutions, data solutions and GIS automation: user interfaces, APIs, databases, integrations, deployment and ongoing administration. Our team also implements computer vision, AI and agent integrations with defined permissions, testing and human review.

Request a project review How delivery works

No polished brief required. Start with the corridor, asset data or workflow that is holding delivery back.

Europe • USA • APAC

Your decisionCan this work package move without creating another handover problem?

Our roleConnect engineering, spatial evidence, quality and operating ownership.

Low-risk startTest representative data and acceptance rules before programme rollout.

Where delivery breaks down

The workflow problem

Manual processing becomes operational risk when the rules live in one person’s memory and every dataset needs a different workaround.

The same data is handled repeatedly

Teams export, rename, join, check and reformat files every reporting cycle or project release.

Errors are hard to trace

Spreadsheets and desktop steps overwrite evidence and provide little visibility into what changed.

Scripts depend on one person

Useful prototypes lack configuration, logging, testing, documentation and an agreed owner.

A controlled delivery workflow

From first review to operational handover.

Map the current process

Document sources, decisions, rules, exceptions, volumes, timing and the people who use each output.

Design a contained pilot

Automate a representative workflow with clear acceptance criteria, error handling and measurable operational checks.

Productionise and integrate

Add configuration, validation, logs, scheduling, access controls and connections to the required systems.

Document and hand over

Provide source, deployment steps, runbooks, troubleshooting and training for the nominated owner.

What you receive

Specific deliverables, agreed before rollout.

Final formats and acceptance criteria are confirmed during discovery and tested during the pilot.

Current state workflow and automation backlog
Python, PyQGIS or FME workflows
Spatial database procedures and validation rules
File, database and API integration pipelines
Configuration, logging and exception handling
Scheduled processing and reporting jobs
Test cases and acceptance evidence
Source code, runbook and support handover
End-to-end web applications, interfaces, APIs and deployment pipelines
Data architecture, ingestion, transformation, storage and serving layers
Computer vision and AI evaluation, confidence thresholds and review queues
Agent integration with scoped tools, approval gates, audit logs and monitoring

Operational outcomes

What should be different after the work.

Consistent processing

The same rules are applied to every run, with inputs, outputs and failures made visible.

Less repetitive effort

Specialists spend more time resolving real exceptions and less time repeating mechanical steps.

Maintainable automation

Source, configuration, logs and support ownership are included in the delivery.

Software engineering and practical AI

End-to-end web solutions. Connected data. Controlled automation.

Web applications and data solutions

Deliver user experience, frontend, backend APIs, databases and integrations through testing, deployment and administration. Include access controls, monitoring, source code, documentation and an agreed support model.

FME and GIS integration

Build and maintain FME Form and FME Flow workflows, Python pipelines, ArcPy and ArcGIS API for Python automation. Connect files, databases, web services and applications with validation and recoverable error handling.

Computer vision, AI and agents

Implement asset detection from imagery, classification, document extraction and task-oriented agents. Test representative inputs, restrict tool permissions, require approval for consequential actions and record outputs, uncertainty and audit trails.

View platforms, implementation scope and lifecycle notes →

Platforms and methods

Tools selected around the operating requirement.

PythonFME FormFME FlowPyQGISArcGIS API for PythonArcPyArcGIS Maps SDK for JavaScriptJavaScript and TypeScriptSQL and PostGISREST APIsComputer visionAI and agent integrationsAutomated testing and deployment

Handover is part of delivery

Your team receives more than final files.

We provide source code, configuration, deployment instructions, dependencies, test cases, logs, known limitations and a troubleshooting runbook. The nominated owner is walked through routine operation and recovery.

Common buyer questions

What teams usually need to clarify.

These answers describe our normal approach. The project review confirms what applies to your environment.

When should a workflow use FME instead of Python?

The choice depends on existing licences, internal skills, integration needs, complexity, support and how transparent the workflow must be. We use the tool that best fits the operating model.

Can you automate quality control for GIS and As-Built data?

Yes. Common checks cover schemas, required values, domains, geometry, topology, connectivity, duplicate assets, file naming and cross source consistency.

Do you maintain existing scripts?

We can review and stabilise existing automation if the source, dependencies and business rules are available. Discovery identifies whether repair or replacement is more sensible.

How do you prevent automation from hiding bad data?

Validation, thresholds, rejected record outputs and exception reporting are designed into the workflow. Automation should expose ambiguity, not silently force it through.

Connected capabilities

Related work that often sits beside this service.

A low-risk first step

Review the workflow, data and next delivery decision with our team.

Share one representative work package, dataset or stalled workflow. We will identify the missing inputs, acceptance gates and smallest pilot that can produce a useful decision.

Request a project review

Start with a focused scope. Agree the inputs, outputs and acceptance criteria before scaling.