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AI Strategy to Production
Turn AI opportunities into reliable production systems. We help organisations move from discovery and proof-of-concept through architecture, implementation, security and deployment.
Melbourne · Australia & APAC
Build what's next with AI and cloud.
Coplanar AI helps organisations design, build and operate production-ready AI and cloud systems — from generative AI and intelligent agents to cloud architecture, automation and modern applications.
AI & cloud engineering for organisations across Australia and APAC.
Building with AWS, Claude, Google Cloud and Azure
Platforms and technologies
Built across the world's leading AI and cloud platforms
Technology ecosystems we build with. The work is chosen for the problem, the operating model and the constraints — not for a badge on a slide.
- AWSCloud platform
- Anthropic ClaudeModel family
- Google CloudCloud platform
- Microsoft AzureCloud platform
- OpenAIModel family
- KubernetesContainers
- TerraformInfrastructure as code
- DockerContainers
- GitHubDelivery
- PythonEngineering
- TypeScriptEngineering
- PostgreSQLData
Building with AWS, Claude, Google Cloud and Azure. These names describe technology ecosystems we work with. Listing a platform is not a claim of partnership, certification or endorsement.
Capabilities
Strategy, platforms and systems that have to run.
Most engagements sit in one of three places. Many move through all three, from the first decision to something an operations team can own.
02
Modern Cloud Engineering
Design secure, scalable cloud foundations and modernise existing environments across leading cloud platforms.
03
Automation & Intelligent Systems
Combine AI agents, APIs, business systems and cloud infrastructure to automate complex workflows and operational processes.
Solutions
Where the work usually starts.
Each path below leads into the service area it belongs to. They are ways of scoping a problem, not packaged products with a fixed price.
AI Adoption
Decide where generative AI belongs, and what has to be true before anyone depends on it.
AI servicesCloud Modernisation
Move platforms and applications onto a foundation that can be changed safely.
Cloud engineeringEnterprise AI Agents
Agents tied to a business process, its systems and a point where a person can stop them.
AgentsIntelligent Automation
Workflows that join models, APIs and the systems people already use.
ServicesData & AI Platforms
Retrieval, knowledge and the data paths a model is allowed to use.
AI platformsApplication Modernisation
Replace the parts of an application that block delivery, without a rewrite for its own sake.
ModernisationAI-Powered Software
Applications and interfaces built around a model, with an API and an owner.
ApplicationsCloud Security
Identity, network boundaries, logging and the controls around a landing zone.
SecurityManaged AI & Cloud
Ongoing operation once a system is live: monitoring, cost and the next change.
Managed servicesAI Proof-of-Concepts
A working build against agreed criteria, before a full deployment is funded.
Proof of conceptGenerative AI
Turn generative AI into operational capability.
A model demo is not a system. We support the path from the first question through to something that can be secured, deployed and looked after.
01
Discover
The decision, the users and the constraint.
02
Prototype
A narrow build against a real workflow.
03
Validate
Quality, failure modes and operating cost.
04
Build
The system, the integrations and the interface.
05
Secure
Access, data handling, guardrails and audit.
06
Deploy
Release into the environment it will run in.
07
Operate
Quality, incidents and a named owner.
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Optimise
Cost, latency and the workflow around it.
Agentic AI
AI agents built for real business workflows.
We design agents around business processes, systems and governance — not demos. Coplanar AI integrates models with enterprise data, APIs, cloud services and human approval workflows.
Customer service agents
Answers grounded in policy, orders and the product catalogue.
Internal knowledge agents
Search across approved material, with the source attached.
Research agents
Structured collection and comparison, handed back for review.
Document processing agents
Extract, classify and route, with a person on the exceptions.
Operations agents
Triage across the systems an operations team already watches.
Developer productivity agents
Tied to repositories, tickets and the review path a team uses.
Compliance assistants
Drafts and checks against a controlled set of rules.
Sales assistants
Preparation from approved product and account information.
Data analysis agents
Questions over a defined dataset, not an open warehouse.
Workflow orchestration agents
Steps that call APIs and stop when a decision needs a person.
Cloud engineering
Cloud foundations built for scale.
Landing zones, migration, delivery pipelines and the controls that keep a platform operable. Designed on AWS, Google Cloud and Microsoft Azure.
Cloud architecture
Accounts, networks, identity and the shape of the platform.
Migration
A path off the current estate, with a rollback that is real.
Infrastructure as code
Terraform and pipelines, so the environment can be rebuilt.
Kubernetes & serverless
The runtime that fits the workload, not a default.
Security & FinOps
Boundaries, logging, and a design that can be paid for.
Managed operations
Monitoring, change and cost once the platform is live.
Proof of concept
Move from idea to proof-of-concept — fast.
Coplanar AI works with organisations to validate cloud and AI initiatives before committing to full-scale deployments. The point of the exercise is a decision, backed by a working build and a production plan.
Eligible projects may also be evaluated for applicable cloud-vendor programs and incentives where available. That is not a promise of funding.
01
Discovery
Identify the problem, desired business outcome and technical constraints.
02
Architecture
Design the cloud, AI, data and integration architecture.
03
Proof of Concept
Build a working solution against measurable success criteria.
04
Production Plan
Define security, scalability, governance and production requirements.
05
Production Deployment
Turn successful prototypes into operational systems.
Industries
Solutions applicable across sectors.
These are relevant use cases, not a client list. We do not imply a named customer, a completed project or a measured result.
Financial services
Policy assistants and migration planning with a controlled cutover.
Use casesProfessional services
Knowledge over prior work, and document-heavy internal workflows.
Use casesTechnology
Product AI features, platforms and engineering workflow.
Use casesHealthcare
Document workflows with a person still responsible for the decision.
Use casesGovernment
Staff assistants and cloud designs where access and audit matter.
Use casesStartups & scale-ups
A first production cloud, and a prototype taken through to deployment.
Use casesExample engagements
Representative shapes of work.
These describe engagement types. They are not completed customer projects. They do not name a client, state a result, or present a testimonial.
Type
Enterprise knowledge assistant
Source systems and access rules, a grounded assistant over approved content, then evaluation, guardrails and a production plan.
Type
Cloud migration assessment
Current estate, constraints and a target landing zone, with a sequenced move and an honest view of what should stay put.
Type
AI document processing system
Classification and extraction on a defined document set, exception handling, and a review step before anything is written back.
Type
Customer support agent
A bounded agent on policy and order data, with tools it is allowed to call and a handoff when it should stop.
Type
Legacy application modernisation
The parts of an application that block change, a target architecture, and a delivery path that keeps the business running.
Type
AI-powered workflow automation
A process that currently lives in inboxes, joined to APIs and a model, with ownership and a way to see what it did.
Engagement models
Engage the way your project requires.
Advisory
Architecture and technical strategy.
Proof of Concept
Rapid validation of AI and cloud initiatives.
Project Delivery
End-to-end implementation.
Embedded Engineering
Specialists integrated with customer teams.
Managed Services
Ongoing operation, monitoring and optimisation.
AI Practice Enablement
Help internal teams adopt AI engineering practices.
Why Coplanar AI
Engineering first. Outcomes focused.
The useful test of this work is whether a system can be run, changed and explained six months after it goes live.
- 01
AI-native engineering
Evaluation, retrieval and guardrails are part of the design, not a slide added at the end.
- 02
Cloud-first architecture
Identity, delivery and cost are designed with the workload, not bolted on after a diagram.
- 03
Vendor-agnostic approach
AWS, Google Cloud, Azure and the model are chosen for the job. We do not dress that up as a partnership.
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Production-focused delivery
A prototype is useful when it has a path into the environment people will actually use.
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Security by design
Access, data handling and audit are scoped while the architecture is still cheap to change.
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Cost-aware architecture
Model choice, caching, tenancy and runtime are treated as operating decisions.
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Automation-first mindset
Infrastructure, tests and the workflow itself should not depend on a single person's memory.
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Australian-based consultancy
Coplanar AI Pty Ltd is based in Melbourne and works in Australian business hours as a default.
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APAC delivery capability
Engagements are delivered for organisations across Australia and the Asia-Pacific.
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From strategy through operations
Discovery, build, deployment and the period after go-live can sit with the same team.
Process
From the first conversation to a system you can run.
01
Discover
The problem, the outcome and the constraints that are not negotiable.
02
Design
Architecture for cloud, data, AI and the integrations between them.
03
Validate
A proof of concept measured against criteria agreed up front.
04
Build
Implementation, with security and operability in the same backlog.
05
Deploy
Release into the real environment, with a rollback and an owner.
06
Optimise
Cost, quality and the next change once the system is in use.
Company
About Coplanar AI
Coplanar AI Pty Ltd is an Australian AI and cloud consultancy focused on helping organisations adopt and operationalise modern cloud and artificial intelligence technologies.
We combine cloud engineering, software development, data, automation and generative AI to build practical systems that move beyond experimentation and into production.
From initial discovery and proof-of-concept through implementation and managed operations, we work with organisations to build secure, scalable and maintainable technology platforms.
We are based in Melbourne, Australia, and we serve organisations across Australia and the Asia-Pacific.