Put AI to work for public service, with accountability intact.
Public institutions run on cases, records and rules.
Margins builds AI into public-sector workflows to help teams process applications faster, handle correspondence, find the right regulation or procedure and prepare cases for decision — while keeping data under the institution’s control and decisions with accountable officials.
Faster public services. Less administrative load. Clear human accountability.
Public administration already runs on procedure. AI changes how much of it people have to do by hand.
Behind every application, permit and public inquiry sits a large amount of work done by people:
- Reading
- Checking
- Verifying
- Searching
- Classifying
- Routing
- Drafting
- Answering
- Recording
- Reporting
AI is most valuable when it expands public-sector capacity without removing public accountability.
Most public-sector work arrives as documents, not database fields.
- Applications
- Permit requests
- Citizen letters
- Emails
- Supporting evidence
- Inspection reports
- Tender documentation
- Legislation
- Internal procedures
- Decisions and rulings
- Scanned archives
- Spreadsheets
- Meeting minutes
- 01Incoming submission
- 02Understand
- 03Extract
- 04Classify
- 05Check completeness
- 06Case record
- 07Official review
Turn submissions people have to read into cases systems can work with.
Not every step requires discretion.
Most administrative procedures contain both. AI and automation can take on the repetitive information work while officials stay focused on the parts that require legal and professional judgment.
Preparation.
- Register submissions.
- Check completeness.
- Extract data.
- Cross-check registries.
- Apply defined criteria.
- Route to the right department.
- Draft standard responses.
Accountability.
- Interpret the law in context.
- Assess unusual circumstances.
- Approve exceptions.
- Make decisions that affect citizens.
Automate the preparation. Keep decisions with accountable officials.
Let officials work the exceptions instead of handling every file the same way.
Traditional procedures often require a person to open every file. AI can read submissions, check them against defined criteria and flag uncertainty — moving complete, routine cases forward and sending the rest to the people who should look at them.
The objective isn’t maximum automation. It’s putting official attention where citizens need it most.
The answer shouldn’t depend on finding the one person who knows the regulation.
Don’t make staff search through legislation and circulars. Let approved sources answer them.
Explore Enterprise Knowledge & RAG- “Which procedure applies to this type of application?”
- “What documents must the applicant submit?”
- “What changed in the latest amendment to this regulation?”
- “How did we decide similar cases before?”
- “Show me the legal basis for this answer.”
Some of your institution’s most valuable knowledge isn’t written down.
- 01
An experienced case officer sees immediately what is missing from an application.
- 02
A legal advisor knows which detail changes how a regulation applies.
- 03
An inspector knows which findings deserve a closer look.
- 04
A front-office employee understands what citizens actually ask — and why.
- 05
A department head knows why the documented procedure works differently in practice.
Regulations describe how the institution should work. Experienced staff understand how it actually works — and that knowledge leaves when they retire. AI becomes more useful when it can work with both.
Explore CaptaPublic data should stay under public control.
Useful public-sector AI may need access to- Citizen personal data
- Case files
- Registry data
- Tax and benefit records
- Internal procedures
- Inspection findings
- Classified or restricted material
- Inter-agency data
- Historical archives
- 01Government or sovereign cloud
- 02Institution-owned infrastructure
- 03On-premise deployment
- 04Private models
- 05Open-source models
- 06Selective external models
- 07Hybrid architectures
Sovereign AI isn’t about avoiding innovation. It’s about deciding deliberately what stays inside, what can leave and on what legal basis.
AI should fit into the systems the institution already runs, not sit beside them.
Relevant information may live across case management systems, public registries, document and records management, ERP and budgeting, citizen portals, e-services, archives, legacy applications and identity systems — often across several agencies.
The goal isn’t another platform staff need to log into. It’s intelligence inside the procedures they already follow.
Explore IntegrationsStart with the procedure where backlogs build up.
Look for processes where:
- Officials read large volumes of submissions.
- The same completeness checks happen repeatedly.
- Cases move between departments or agencies.
- Experts spend time preparing files rather than deciding.
- Citizens wait while requests sit in a queue.
- Staff repeatedly search legislation and procedures.
- Similar inquiries are answered by hand, one at a time.
- Reporting means pulling data from several systems.
- 01Public service problem
- 02Procedure
- 03Information + systems
- 04Legal / control requirements
- 05AI opportunity
- 06Value × Feasibility
- 07First implementation
The best AI opportunity is where automation improves the service without weakening the safeguards the procedure requires.
Start controlled. Expand with evidence.
Public-sector AI doesn’t need to begin with automated decisions. It should start where the risk is lowest and the workload is highest.
Search
Find the right regulation or procedure faster.
Assist
Draft replies and prepare files for staff.
Analyze
Flag incomplete or unusual cases.
Recommend
Support officials’ decisions with sources.
Automate
Handle defined routine steps.
Agentic
Allow controlled, recorded actions.
Increase autonomy as confidence, safeguards and evidence increase.
Build the intelligence and the accountability around it.
Service first
Start with the public service or administrative outcome rather than the model.
AI + software engineering
Build complete production systems rather than isolated pilots that never leave the lab.
Sovereign architecture
Design around personal data and institution-controlled environments.
Integration with existing systems
Connect AI to case management, registries and records — including legacy systems.
Traceable by design
Sources, steps and human approvals recorded, so decisions can be explained and reviewed.
Production ownership
Forward Deployed Engineering and Managed AI keep the system close to operational reality after deployment.
Related capabilities
Intelligent Automation
Move application and case processing toward exception-based work.
Explore Intelligent Automation →Enterprise Knowledge & RAG
Give staff source-grounded access to legislation, procedures and past decisions.
Explore Enterprise Knowledge →Private & On-Premise AI
Run AI on citizen and case data without giving up control of it.
Explore Private AI →AI Agents
Introduce controlled, recorded AI actions into administrative workflows.
Explore AI Agents →Managed AI
Operate and monitor public-sector AI after it enters production.
Explore Managed AI →
Where are citizens waiting on work that doesn’t need an official’s judgment?
We’ll work with your leadership, case-handling and IT teams to identify where AI can reduce administrative load, shorten response times or improve access to institutional knowledge — while respecting the legal, data-protection, accessibility and procurement requirements your institution operates under.
Explore AI opportunitiesStart with the procedure. Define the safeguards. Prove the value.