Pillar 01 · Data Platform Modernization
Move the data foundation. Run the business on it.
AI works on the data it can read. If the data foundation is stuck in a legacy warehouse, an on-prem Hadoop cluster, or pipelines no one owns, AI is stuck with it. We move the foundation to AWS, in weeks, not quarters, so the company runs on something AI can actually use.
What Changes
The outcomes a CFO and CIO can budget against.
A modernized data foundation on AWS is not a technology outcome. It is a business outcome that compounds. The analytics team stops fighting infrastructure and starts answering questions. The product team gets data fresh enough to act on. The audit team gets a lineage trail that holds up to a regulator. The AI program gets a substrate it can actually read.
What customers tell us mattered after cutover:
- The cost of running the data platform dropped and became predictable.
- The data team stopped owning the system and started owning what it produces.
- The next AI initiative did not need a separate data project to precede it.
How We Deliver
Aedeon scales the migration work. FDEs own the cutover.
Aedeon handles the work that traditionally consumed analyst hours: source discovery across the data systems, mapping, validation, observability. Forward-deployed engineers own the architecture choices, the cutover sequencing, and the production sign-off. The customer's data team takes over the running system on customer-signed acceptance.
In Production
Where this work has landed.
Pillar · Data Platform · Vertical · Manufacturing
Synaptics: Operational data lake on AWS
Mactores delivered an AI-backed operational data lake on AWS for Synaptics. The design team stopped losing cycles to queue contention and reallocated them to the work that ships chips.
Pillar · Data Platform · Vertical · Internet & Software
Flipboard: Modernization that improved engagement
Mactores modernized Flipboard's data foundation to AWS-native infrastructure. The migration did not just hold the platform together; it improved what the platform delivered to users.
Where This Lands
Verticals where data platform work goes first.
Financial Services
Audit-grade lineage, regulator-defensible analytics
Healthcare & Life Sciences
HIPAA-aligned data foundation, clinical-grade evidence
Internet & Software
Analytics at platform scale, customer 360
Manufacturing
Industrial data foundation without taking the line offline
TMEGS
Audience-scale content and analytics under peak load