AI-Augmented Development Services
Most teams add AI to software after it's already built. Classic Informatics delivers AI-augmented software development where intelligence is architected into the product from day one.
Trusted by Enterprises in 30+ Countries
OUR SERVICES
AI-Augmented Development We Deliver
Architecture Consulting
We design systems where AI is a core component, not an afterthought.
Custom Software Development
Custom software built around your business logic, data, and users.
AI Integration & Engineering
We build the pipelines and feedback loops that make AI perform reliably.
Deployment & Optimisation
We manage deployment & optimisation so your product's intelligence improves with use.
OUR SOLUTIONS
Our AI-Augmented Development Solutions
AI-Assisted Development
AI-Powered QA
AI Code Generation
AI-Optimized Delivery Workflow
AI-Assisted Code
Analysis
Development
Efficiency
OUR PROCESS
How We Implement AI-Augmented Development
Our Approach
We identify where AI will deliver real value in your product — and where it won't. You leave with a scoped product brief, prioritised AI use cases, and a clear starting point.
Key Activities:
- Define product goals and AI use cases
- Assess existing data and infrastructure
- Prioritise AI integration points by value
- Produce a scoped product brief
Our Approach
We design the full system — application and AI layer together. Every data flow, integration point, and model selection decision is made here, before any development begins.
Key Activities:
- Design architecture with AI built in
- Define data pipelines and retrieval strategies
- Select models and tooling for your needs
- Specify integration points and fallback behaviours
Our Approach
We build the application and AI components in parallel, not in sequence. Integrations are tested at realistic scale, with observability tooling in place from the start.
Key Activities:
- Build application and AI pipelines together
- Fine-tune models against your product data
- Implement inference and feedback loop components
- Set up monitoring and observability tooling
Our Approach
We manage production deployment and run a stabilisation period to catch issues that only surface at scale. Full technical ownership transfers to your team before we close.
Key Activities:
- Manage production deployment and rollout
- Configure performance dashboards and monitoring
- Resolve issues surfaced at production load
- Complete documentation and knowledge transfer
Our Approach
Post-launch, we analyse how the AI is performing against real usage and iterate where needed. Your product's intelligence should improve with use — this phase makes that happen.
Key Activities:
- Analyse production AI performance data
- Identify model drift and retrieval gaps
- Iterate on fine-tuning and retrieval strategies
- Expand AI use cases as data grows
Our Approach
We identify where AI will deliver real value in your product — and where it won't. You leave with a scoped product brief, prioritised AI use cases, and a clear starting point.
Key Activities:
- Define product goals and AI use cases
- Assess existing data and infrastructure
- Prioritise AI integration points by value
- Produce a scoped product brief
Our Approach
We design the full system — application and AI layer together. Every data flow, integration point, and model selection decision is made here, before any development begins.
Key Activities:
- Design architecture with AI built in
- Define data pipelines and retrieval strategies
- Select models and tooling for your needs
- Specify integration points and fallback behaviours
Our Approach
We build the application and AI components in parallel, not in sequence. Integrations are tested at realistic scale, with observability tooling in place from the start.
Key Activities:
- Build application and AI pipelines together
- Fine-tune models against your product data
- Implement inference and feedback loop components
- Set up monitoring and observability tooling
Our Approach
We manage production deployment and run a stabilisation period to catch issues that only surface at scale. Full technical ownership transfers to your team before we close.
Key Activities:
- Manage production deployment and rollout
- Configure performance dashboards and monitoring
- Resolve issues surfaced at production load
- Complete documentation and knowledge transfer
Our Approach
Post-launch, we analyse how the AI is performing against real usage and iterate where needed. Your product's intelligence should improve with use — this phase makes that happen.
Key Activities:
- Analyse production AI performance data
- Identify model drift and retrieval gaps
- Iterate on fine-tuning and retrieval strategies
- Expand AI use cases as data grows
WHY IT MATTERS
Benefits of AI-Augmented Development
Reliable Performance
Faster Time to Value
AI That Improves
Less Manual Work
Product Advantage
Full Engineering Control
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
AI Should Be How Your Product Works. Not an Afterthought.
We build software with intelligence at the core, delivered end to end.
