01 / Solutions
AI-powered solutions
Purpose-built capabilities that apply AI to defined GIS and land-records workflows, including cadastral extraction and natural-language search.
Explore Sidwell AI solutions →Sidwell Artificial Intelligence
Practical AI for Government GIS
Sidwell helps local governments apply artificial intelligence to real GIS and land-records challenges. Our approach combines AI speed and scale with authoritative data, expert review, strong quality controls, and human accountability.
- Human-in-the-loop
- Authoritative data
- Transparent processes
- Measurable quality controls
AI does the heavy lifting. Experienced people make the call.
Practical intelligence. Human accountability.
Our point of view
AI should strengthen professional judgment
Sidwell begins with the government’s operational need, authoritative data, and responsibility to the public. We apply AI where it can produce a measurable benefit, then use the human review, testing, security, and governance appropriate to the risk.
Public value firstEvery initiative begins with a defined operational or service need.
People remain accountableQualified professionals validate results and make consequential decisions.
Data is the foundationApproved records, data quality, and lineage shape every AI workflow.
Trust must be demonstratedSecurity, transparency, testing, and monitoring are built into delivery.
How Sidwell applies AI
From AI potential to practical GIS results
Sidwell connects AI to defined government workflows, clear sources of truth, and outcomes customers can evaluate.
02 / ArcGIS
AI within ArcGIS
Guidance and implementation support for GeoAI models, AI assistants, spatial analysis, imagery extraction, pattern detection, and emerging ArcGIS capabilities.
Explore Esri implementations →03 / Advisory
AI advisory and implementation
Consulting that helps local governments identify suitable use cases, assess data readiness, establish controls, select technology, and test controlled pilots.
Explore AI advisory services →
AI-assisted cadastral extraction with expert review and validated delivery.
Featured AI solution
Turn cadastral records into validated parcel data
MTerra uses purpose-built AI to extract boundaries, parcel lines, COGO measurements, symbols, and attributes from plats and historical maps. Sidwell’s cadastral professionals review uncertain results, correct discrepancies, and validate each record before delivery.
- AI-assisted record extraction
- Human-in-the-loop cadastral review
- COGO and geodetic validation
- ArcGIS Parcel Fabric-ready delivery
- Traceable source-to-output workflow
SourceScanned plat or historical map
AI-assisted workFeatures detected and uncertainty flagged
Expert validationParcel Fabric-ready result
Public information access
Make property information easier to find
The Portico AI Assistant gives users a more natural way to search for parcels and navigate public property information. Users can describe what they need in everyday language while the jurisdiction’s approved data remains the authoritative source.
- Natural-language parcel search
- Easier navigation for occasional users
- Clear scope and user guidance
- Approved government data remains authoritative
Practical applications
Where AI can support government GIS
The right use case is specific, measurable, supported by suitable data, and governed according to the impact of a potential error.
01
Land records and parcel modernization
- Extract parcel information from plats and historical maps
- Identify boundaries, measurements, symbols, and annotations
- Flag incomplete or uncertain records for expert review
- Accelerate Parcel Fabric preparation and data cleanup
02
Public information access
- Support natural-language parcel searches
- Help residents navigate public mapping applications
- Explain application features and available information
- Direct complex questions to the appropriate department
03
GIS operations
- Assist with metadata, code, Arcade, and workflow development
- Classify imagery and extract geographic features
- Identify possible anomalies or data-quality issues
- Summarize technical documentation for staff
04
Planning and analysis
- Detect patterns across spatial datasets
- Support change detection and forecasting
- Analyze imagery, land use, and infrastructure conditions
- Help teams evaluate scenarios and allocate resources
AI advisory and implementation
A disciplined path from idea to implementation
Sidwell helps local governments determine where AI belongs in their GIS strategy, what must be in place before deployment, and how results will be evaluated.
Define the problem
Identify the operational challenge, affected users, desired outcome, and current baseline.
Assess the data
Review quality, completeness, sensitivity, ownership, accessibility, and suitability.
Evaluate value and risk
Determine whether AI is appropriate and define the human oversight required.
Pilot and validate
Test with controlled data, acceptance criteria, expert review, and measurable targets.
Deploy and monitor
Introduce training, documentation, governance, monitoring, and issue management.
Start with a practical assessment
Sidwell AI Readiness Assessment
Build a clear view of where AI can deliver value, whether your data is ready, which risks require attention, and what your first controlled pilot should address.
Potential assessment outputs
- Current-state AI and GIS review
- Data-readiness findings
- Prioritized use-case matrix
- Risk and governance considerations
- Recommended pilot and implementation roadmap
Sidwell’s AI philosophy
Eight principles guide our work
01
Public value comes first
AI should improve a defined government operation, service, or decision-support need.
02
People remain accountable
Human review increases with the potential impact of an error.
03
Authoritative data is foundational
Approved records, business rules, data quality, and lineage govern the result.
04
Security and customer control are built in
Data handling, access, retention, and third-party involvement must be understood.
05
Results are understandable and traceable
Users should know AI’s role, limitations, source information, and review process.
06
Accuracy is demonstrated
Testing, acceptance criteria, expert validation, and monitoring provide evidence.
07
Adoption is deliberate and proportional
Controlled pilots and risk-based governance precede broader deployment.
08
AI strengthens organizational capability
Training and knowledge transfer help customers maintain control of their workflows.
AI resource center
Practical guidance for government GIS teams
Use this section to publish educational content, support customer conversations, and build an informed path toward AI adoption.
A Practical Guide to AI for Local Government GIS
GeoAI, generative AI, appropriate use cases, governance, security, and pilot planning.
Coming soonIs Your GIS Ready for AI?
A structured review of data, governance, staffing, infrastructure, risk, and measurement.
Coming soon10 Questions to Ask Before Adding AI to a GIS Workflow
Questions covering data use, retention, accuracy, review, auditability, and vendor controls.
Coming soonFrequently asked questions
Clear answers about AI and GIS
Does Sidwell use AI to make decisions for government customers?
Sidwell uses AI to support defined tasks such as information extraction, pattern identification, search, analysis, and workflow assistance. Government officials and qualified professionals remain responsible for consequential decisions and authoritative records.
How does Sidwell validate AI-generated results?
Validation depends on the use case and may include comparison with source records, expert review, accuracy testing, exception handling, documented acceptance criteria, and ongoing monitoring.
Can AI change authoritative parcel data?
AI may assist with extracting or preparing parcel information. Changes to authoritative data should follow the customer’s approved editing, validation, and authorization processes.
What is human-in-the-loop AI?
Human-in-the-loop AI assigns specific review and decision responsibilities to qualified people. AI performs defined analytical or production tasks, while people evaluate uncertainty, correct errors, and approve consequential results.
What is GeoAI?
GeoAI applies artificial intelligence and machine learning to geographic data. Common applications include imagery classification, feature extraction, change detection, forecasting, spatial pattern recognition, and workflow assistance.
How should our organization begin?
Begin with a clearly defined operational problem, assess the relevant data, evaluate risk, and conduct a controlled pilot with measurable acceptance criteria and qualified human review.
Move AI into a practical workflow
Start with the problem your GIS team needs to solve
Talk with Sidwell about your data, operational priorities, potential use cases, and the right next step for a responsible AI pilot or implementation.