AI Automation Services
Manual processes slow businesses down and create costs that compound over time. We build AI automation that handles the work so your teams don't have to.
Classic Informatics built and modernized our loan workflow platform, maintaining the same team across three years — critical for a product of this complexity.
Soren Scheibye, Co-Founder, UdenomBanken,
Rated 4.9/5 Stars on Clutch
Rated 4.9/5 on Goodfirms
Trusted by Enterprises in 30+ Countries
OUR SERVICES
AI Automation Services We Deliver
AI Workflow Automation
We build AI automation that handles handoffs, approvals, and decisions across systems without human intervention at every step.
Smart Document Processing
We build AI systems that read, classify, and extract structured information from unstructured documents at scale.
Automation Scoping
We assess your current workflows, identify the highest-value automation opportunities, and define a practical roadmap with clear outcomes.
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AI Automation Integration
We integrate AI automation layers with your ERP, CRM, and operational platforms so everything flows cleanly.
OUR SOLUTIONS
Our AI-Powered Automation Solutions
Back-Office Process Automation
Customer Service
Automation
Finance and Invoice Automation
Manual invoice processing creates delays and errors that affect cash flow. We build AI automation for invoice capture, validation, approval routing, and payment processing.
HR and Onboarding Automation
Manual onboarding processes slow new hire productivity and create inconsistent experiences. We automate document collection, system provisioning, and task coordination across HR workflows.
Supply Chain and Operations Automation
Compliance and Reporting Automation
OUR PROCESS
How We Implement AI-Powered Automation
Our Approach
We start by mapping the processes that are consuming the most time and cost, assessing whether they are suited to AI automation, and identifying what data and systems are involved. Automating poorly understood processes creates new problems — we invest in getting this right before any build begins.
Key Activities:
- Process mapping and pain point identification
- Automation feasibility and value assessment
- Data and system dependency analysis
- Prioritisation and roadmap definition
Our Approach
We design the automation architecture — the AI models, workflow logic, integration points, and human oversight mechanisms required to make the automation reliable in production. Good automation design accounts for exceptions, edge cases, and the scenarios where a human still needs to be in the loop.
Key Activities:
- Workflow and automation logic design
- AI model selection and integration design
- Exception handling and escalation design
- Human-in-the-loop framework
Our Approach
We build the automation in focused phases, testing against real process data at every stage. AI automation requires more rigorous testing than traditional software because the inputs are variable — we test edge cases, exceptions, and failure modes throughout, not just at the end.
Key Activities:
- Automation development and integration build
- End-to-end process testing with real data
- Edge case and exception testing
- Performance and accuracy benchmarking
Our Approach
We deploy automation with monitoring and alerting built in, and train the teams who will manage and work alongside it. Automation that teams don't trust or understand gets bypassed — we make sure adoption is high from day one by involving users throughout the process.
Key Activities:
- Production deployment and monitoring setup
- Team training and change management support
- Documentation and runbook delivery
- Hypercare support period post-launch
Our Approach
AI automation improves with use and with feedback. We provide ongoing support to refine models, handle new edge cases, expand automation to adjacent processes, and keep performance high as the business and its data evolve over time.
Key Activities:
- Model refinement and accuracy improvement
- New process and workflow additions
- Performance monitoring and optimisation
- Quarterly automation health reviews
Our Approach
We start by mapping the processes that are consuming the most time and cost, assessing whether they are suited to AI automation, and identifying what data and systems are involved. Automating poorly understood processes creates new problems — we invest in getting this right before any build begins.
Key Activities:
- Process mapping and pain point identification
- Automation feasibility and value assessment
- Data and system dependency analysis
- Prioritisation and roadmap definition
Our Approach
We design the automation architecture — the AI models, workflow logic, integration points, and human oversight mechanisms required to make the automation reliable in production. Good automation design accounts for exceptions, edge cases, and the scenarios where a human still needs to be in the loop.
Key Activities:
- Workflow and automation logic design
- AI model selection and integration design
- Exception handling and escalation design
- Human-in-the-loop framework
Our Approach
We build the automation in focused phases, testing against real process data at every stage. AI automation requires more rigorous testing than traditional software because the inputs are variable — we test edge cases, exceptions, and failure modes throughout, not just at the end.
Key Activities:
- Automation development and integration build
- End-to-end process testing with real data
- Edge case and exception testing
- Performance and accuracy benchmarking
Our Approach
We deploy automation with monitoring and alerting built in, and train the teams who will manage and work alongside it. Automation that teams don't trust or understand gets bypassed — we make sure adoption is high from day one by involving users throughout the process.
Key Activities:
- Production deployment and monitoring setup
- Team training and change management support
- Documentation and runbook delivery
- Hypercare support period post-launch
Our Approach
AI automation improves with use and with feedback. We provide ongoing support to refine models, handle new edge cases, expand automation to adjacent processes, and keep performance high as the business and its data evolve over time.
Key Activities:
- Model refinement and accuracy improvement
- New process and workflow additions
- Performance monitoring and optimisation
- Quarterly automation health reviews
WHY IT MATTERS
Benefits of AI-Powered Automation
Beyond the Rules
Significant Cost Reduction
Faster Process Execution
Automated workflows run continuously without the delays that come from manual handoffs, approval queues, and human availability. Processes that took days complete in minutes.
Fewer Errors at Scale
Manual processes introduce errors that compound at volume. AI automation applies consistent logic at scale, reducing error rates and the rework costs that follow.
Scale Without Hiring
Better Data and Visibility
Automated processes generate structured, consistent data. Leadership gains real-time visibility into process performance that manual workflows can't provide.
Latest Case Studies
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Rebuilt and unified parcel operations for an Australian logistics network across 1,700+ locations
Unified 1,700+ partner locations and five carrier integrations into a single parcel management platform, processing 10,000+ daily transactions.
Read Full Case Study → -
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Replaced manual loan workflows with a custom platform for a Danish lender
Automated loan origination, credit checks, and document generation for a Danish property credit platform.
Read Full Case Study → -
Delivered a wear analysis and lifecycle management platform for a global mining manufacturer
A third-party tool replaced with a purpose-built inspection and wear platform tracking 900+ mining assets at global mine sites.
Read Full Case Study → -
Delivered three generations of analytics infrastructure for a 250-clinic dental group
Three generations of analytics infrastructure built over 20 years, delivering daily operational dashboards across 250 dental clinics and 1,000+ providers.
Read Full Case Study → -
Designed and built every internal clinical system for Australia's leading cancer centre
Clinical systems, MDT workflows, staff compliance, and an Azure analytics platform built from scratch for a specialist cancer centre across 9 departments.
Read Full Case Study →
TESTIMONIALS
Businesses Worldwide Trust Classic Informatics
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PARTNER WITH US
Why Classic Informatics?
Value Beyond Code
Real-time data and modern systems give your teams the visibility to act.
Deep Tech Expertise
20+ years across legacy, data, and AI — the hard problems aren't new to us.
Built for Growth
We align every solution to your business goals, not just your tech stack.
Reliable Delivery
Expert teams who move fast, communicate clearly, and deliver on time.
AI-First Approach
Every solution we build is designed with AI in mind, from architecture to delivery.
Complete Transparency
You know what we're building, why, and what it costs — at every stage.
FAQS
Frequently Asked Questions
Automate the Processes That Are Holding Your Business Back
From process discovery to production deployment, we handle it end to end.
