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.

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75%
Lower queue wait times (Synaptics)
40%
Throughput improvement
Weeks
To production cutover, not quarters

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.

01
Assess
Signed exit
02
Design
Signed exit
03
Build
Signed exit
04
Test
Signed exit
05
Deploy
Signed exit

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

Before:Weeks of queue contention on legacy infrastructure
After:40% throughput improvement · 75% lower queue wait times
Time:Weeks

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.

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PILLAR · DATA PLATFORM · VERTICAL · INTERNET & SOFTWARE

Flipboard: Modernization that improved engagement

Before:Legacy database under engagement load
After:Modern AWS-native foundation · improved resilience and user engagement
Time:Weeks

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.

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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

Move the foundation first. AI works against it after.

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