AI and generative AI
Strategy, Claude and other LLM implementations, agents, retrieval, evaluation, guardrails and production deployment.
Services
Design, build and operate AI and cloud systems.
Coplanar AI is an Australian consultancy for generative AI development, AI agent development, cloud migration and the integration work between them. Engagements run from an advisory review through to production and managed operations.
Areas of work
Three practices, one delivery path.
Cloud engineering
Architecture, migration, modernisation, infrastructure as code, security, FinOps and operations on AWS, Google Cloud and Azure.
Integration and automation
APIs, workflow automation and the joins between business systems, data and a model. This is where an agent becomes part of an operation.
Applications
AI-powered software with an owner.
Some work is a feature inside a product. Some is an internal tool. Both need an interface, an API, identity, a place to run and someone who can change them after launch. We build that as software, not as a notebook that happens to answer questions.
API and systems integration
Contracts between the model, the workflow and the systems of record.
Data engineering
Pipelines and stores that feed retrieval, analytics and operations.
Workflow automation
Steps, exceptions and human approval, implemented in the systems people use.
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. Success criteria are agreed before the build, so the result can support a decision.
Eligible projects may also be evaluated for applicable cloud-vendor programs and incentives where available. We do not promise vendor funding.
Discuss a Proof of Concept01
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.
Engagement models
Engage the way your project requires.
Advisory
Architecture and technical strategy. Useful when the decision is the deliverable: a target design, a risk view, or a sequence of work.
Proof of Concept
Rapid validation of AI and cloud initiatives against criteria you can show to a sponsor.
Project Delivery
End-to-end implementation, from the agreed design through deployment.
Embedded Engineering
Specialists integrated with customer teams, working in your backlog and your tools.
Managed Services
Ongoing operation, monitoring and optimisation after the build.
AI Practice Enablement
Help internal teams adopt AI engineering practices: evaluation, delivery and review.
Managed AI and cloud
Operation after the project board closes.
Managed services cover the period when a platform or an AI system is in use: monitoring, incident response within an agreed scope, cost review, and the small changes that keep it fit for the workflow. The scope is written down. It is not an open-ended retainer with no owner.