2-4weeks
Typical first-workflow build, full source transfer at handoff
Real-Time Data Sync
Pipelines that push field data from Survey123 and Field Maps directly into your GIS and dashboards.
Spatial Automation
Geospatial automation for repeatable maps, reports, and data pipelines
From raw survey data to published web maps — we package joins, buffers, routing, and imagery into controlled workflows so your team stops doing it manually.
Ingest and normalizeValidate and transformPublish and hand off
The status quo
The cost of manual geospatial processing
- Data arrives in 10 different formats and your team manually converts each one
- Web maps and dashboards go stale because updating them requires analyst intervention
- Field data sits in Survey123 for days before someone processes and publishes it
What we deliver
Automation solutions
02
Scheduled Report Generation
Spatial reports with maps, statistics, and change detection — delivered to stakeholders automatically.
03
Web Map Publishing
Automated tile generation, feature service updates, and dashboard refreshes from your source data.
04
Compliance Automation
Automated regulatory checks, buffer analysis, and constraint mapping for permitting workflows.
05
QA & Validation
Topology checks, attribute validation, and data quality reporting in every pipeline.
Proof-led positioning
What this page needs to make obvious
Geospatial data pipeline automation, spatial ETL automation, and ArcGIS Pro automation.
Ingest and normalize
Bring survey data, imagery, vector layers, or spreadsheet exports into a controlled schema.
Validate and transform
Run geometry, schema, topology, duplicate, and attribute checks before publishing.
Publish and hand off
Produce map layers, reports, dashboards, exports, logs, and runbooks.
Proof workflow
Input, review, evidence, output.
Modeled on the live Geospatial Solutions demos: the page should show what the buyer sends, what they review, what evidence stays visible, and what they receive.
Input
Survey files, GIS layers, databases, spreadsheets, imagery, and APIs.
Review surface
Data is normalized, validated, transformed, and held at review gates before publishing.
Evidence
Schema checks, geometry flags, exception logs, and reviewer decisions remain visible.
Output
Published map, feature layer, report, CSV, GeoJSON, shapefile, or dashboard.
Source and limits
Technical trust should stay visible.
Confidence
Every automated pipeline needs logs and failure states.
Caveat
Bad source data should be flagged, not silently transformed.
Source
Survey files, GIS layers, databases, spreadsheets, imagery, and APIs.
QA boundary
Schema validation, geometry checks, exception logs, and review gates.
Export path
Published map, feature layer, report, CSV, GeoJSON, shapefile, or dashboard.
Before the first call
What you send · What you get
No vague discovery phase. You bring four or five things, we return a specific plan you can evaluate.
→ What you send
- 1Description of one workflow your team runs repeatedly
- 2Source data sample (CSV, shapefile, GDB, screenshot is fine)
- 3Destination system (ArcGIS Online, Power BI, PostGIS, etc.)
- 4Cadence (hourly, daily, weekly) and trigger (schedule, webhook, manual)
- 5Any current automation attempts and where they break
← What you get back
- 1Written automation scope returned within 48 hours
- 2Effort estimate with fixed-price build option
- 3Tech stack recommendation (Python, Node, Docker, serverless)
- 4Risk + exception handling plan with named failure modes
- 5Runbook structure preview so your team can evaluate maintainability
Sample deliverable
A pipeline run, as your team would see it in production
Structured logging on every step. When something fails, your on-call knows what failed and why before they open the runbook.
log
[2024-08-15 14:23:08] INFO pipeline.survey123_sync start
[2024-08-15 14:23:08] INFO fetch.survey123 form_id=da472a records=14302 elapsed=412ms
[2024-08-15 14:23:09] INFO validate.schema passed=14302 failed=0
[2024-08-15 14:23:11] INFO geometry.buffer features=14302 radius=500m elapsed=2.1s
[2024-08-15 14:23:14] INFO spatial.join layer=parcels result=27894 elapsed=3.2s
[2024-08-15 14:23:17] INFO publish.arcgis_online service=ParcelsBuffered version=v847 elapsed=2.8s
[2024-08-15 14:23:17] INFO pipeline.survey123_sync complete duration=9.2s next_run=2024-08-16T02:00:00ZDeliverables
What you walk away with
- Automated workflow running on your schedule with structured logging
- Infrastructure-as-code deployment (Docker / serverless / your cloud)
- Runbook so the next person can maintain it without you
- Full source code transfer and unlimited derivative use
How we work
A scoped path from sample data to running system
No open-ended retainers. No "discovery phases" that bill for months without producing anything you can evaluate.
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01
Discovery
We shadow your team for a week — watch the workflows, catalog the pain points, and rank automation candidates by hours saved per quarter.
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02
Build
First workflow in 2-4 weeks. Python or TypeScript, with validation, exception handling, and structured logging from day one.
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03
Harden
30 days in production with us on call. We catch the edge cases, tighten the validation, and document the failure modes.
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04
Handoff
Runbook, infrastructure-as-code (Docker or serverless), and full source. Your next analyst can read it without reverse-engineering.
Live on geospatialsolutions.co
Click into the actual work
These open the real, interactive demos on our main site — not screenshots, not videos. Click around before you decide to talk to us.
Why teams trust us
- End-to-end automation from field data collection to published web maps
- ArcGIS, PostGIS, Python, Node.js, FME, Docker, Kubernetes
- Operated by Geospatial Solutions LLC — Washington, DC
Questions teams ask before they engage us
Common questions, answered honestly
We have data in 10 different systems. Can you pull it all together?
That's the most common engagement. We build a spatial data warehouse (PostGIS, BigQuery, or your existing) that ingests from Survey123, ArcGIS Online, Field Maps, third-party APIs, file shares, and CAD systems on a schedule.
How do you handle data quality issues in source systems?
Validation runs on every ingest with structured failure logs. Bad records go to an exception queue for review — never silently to production. You see exactly what failed and why.
Can you publish back to ArcGIS Online after processing?
Yes. The pipeline publishes feature services, hosted layers, and updates web maps on schedule. Tile generation, attribute updates, and feature service overwrites are all automated.
What happens if your pipeline goes down at 2am?
Structured logging, alerts to your on-call channel, and automatic retry with exponential backoff. We document failure modes during build so your team can triage without calling us.
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Book a free automation assessment
Show us one workflow. We will tell you what to automate first.
Bring the workflow that takes the longest every week. We will scope an automation candidate with effort estimates and a written delivery plan within 48 hours.
Automate one recurring spatial pipeline