In today’s market, every executive conversation about growth, efficiency, and competitive advantage inevitably leads to one place: Artificial Intelligence.
From generative AI through to agentic systems, organisations are rapidly exploring how platforms like Amazon Bedrock and emerging capabilities such as Agentcore can transform customer experience, automate operations, and unlock new revenue streams.
But there is a hard truth that many organisations are now confronting:
AI ambitions are only as strong as the data and platforms that underpin them, and modern data foundations for AI unlocks and unblocks these ambitions.
The hidden constraint: Legacy database platforms
Across Financial Services, Energy & Utilities, Retail, SaaS, and the Public Sector, we consistently see the same pattern:
- Critical workloads anchored in SQL Server and Oracle estates
- Heavy reliance on on-premises or legacy hosted environments
- Increasing licensing, infrastructure, and operational costs
- Limited ability to scale, integrate, or operationalise data for AI use cases
These environments were never designed for the velocity, elasticity, or integration demands of modern AI platforms.
As a result, organisations are finding themselves in a position where:
AI is strategically urgent — but their data platforms are structurally limiting, as we found recently in a large scale financial services institution
Why database modernisation is the “Ticket to the game” for AI
At Cevo, we view database modernisation not as an IT upgrade, but as a strategic enabler of AI adoption at scale.
Migrating and modernising SQL Server and Oracle workloads into AWS fully managed services such as:
- Amazon RDS for SQL Server
- Amazon RDS for Oracle
- Oracle Database @ AWS
- Amazon RDS Postgres
- Amazon RDS Aurora for Postgres
…provides a foundational shift in capability:
1. Elastic scale for AI workloads
AI and agentic systems require dynamic access to large volumes of data. Cloud-native databases provide the performance and scalability required to support this in real time.
2. Integrated data ecosystems
Seamless integration with AWS analytics, machine learning, and AI services — including Amazon Bedrock — enables faster experimentation and production launch of AI use cases.
3. Operational efficiency & cost optimisation
Reduced licensing overheads, improved utilisation, and alignment to consumption-based models unlock significant cost efficiencies — often reinvested into innovation.
4. Accelerated time to value
Modern platforms reduce friction across development, data engineering, and AI model deployment, enabling organisations to move from idea to impact faster.
5. Data gravity & reduced data movement
Moving the database onto AWS keeps data closer to the services that consume it, reducing transfer friction and complexity, strengthening security and governance, and improving end-to-end performance for AI and real-time use cases.
Introducing a new AWS–Cevo acceleration pathway
Amazon Web Services has recently engaged Cevo under a new program focused on accelerating customer migration from SQL Server and Oracle environments to AWS-native database platforms.
This is not just a migration initiative — it is a strategic transformation pathway designed to:
- Reduce dependency on legacy database platforms
- Unlock cloud-native data architectures
- Create a scalable foundation for AI and agentic systems
Cevo’s approach: From migration to Intelligent Modernisation
What differentiates Cevo is not just our ability to migrate — it is how we modernise with intent.
Our Intelligent Modernisation Accelerator (IMA) is purpose-built to:
- Rapidly discover and analyse complex database estates
- Apply AI-driven insights to workload classification and optimisation
- Define right-fit migration and modernisation strategies
- Enable wave-based execution at enterprise scale
This approach allows us to move beyond “lift-and-shift” and instead deliver:
Modern, optimised, and AI-ready data platforms.
Accelerating outcomes with AWS MAP funding
Through the AWS Migration Acceleration Program (MAP), organisations can access:
- Funding to reduce the cost of migration
- Proven frameworks for large-scale transformation
- Structured governance and delivery models
When combined with Cevo’s delivery capability and accelerators, this creates a low-risk, high-impact pathway to modernisation.
From data modernisation to AI activation
The connection between modern data platforms and AI is not theoretical — it is direct and measurable.
Organisations that successfully modernise their database environments are seeing:
- Faster deployment of generative AI solutions via Amazon Bedrock
- Increased adoption of agentic workflows and automation
- Improved data accessibility across business and technology teams
- Enhanced ability to operationalise insights at scale
Without question Cevo have helped our clients to achieve their scaled AI aspirations:
Modern data platforms turn AI from experimentation into enterprise capability. Once Assessment and Mobilisation plans are complete, Cevo recommends clients amplify their experience through Experience Based Accelerators, and bring their vision to life.
A call to action for technology and business leaders
For organisations still operating large SQL Server and Oracle estates, the question is no longer if modernisation is required — but how quickly it can be achieved.
The convergence of:
- AI-driven business demand
- AWS-native database capabilities
- Migration funding programs
- Proven delivery accelerators
…means that the opportunity to act has never been stronger.
Partnering for Continuous Evolution
At Cevo, we believe transformation is not a one-off event — it is a continuous journey.
By modernising your data platforms today, you are not just reducing cost or technical debt.
You are:
- Enabling AI at scale
- Unlocking innovation
- Positioning your organisation for long-term competitive advantage
Ready to take the first step?
Cevo is working closely with AWS to help organisations rapidly assess, modernise, and transform their database environments.
If you’re exploring how to unlock AI through modern data platforms, we’d welcome the conversation.
I am a highly driven, focused and committed growth leader now with 15+ years working with the most recognisable Technology transformation brands in Australia.
