Stories
What modernization looks like when an agent-native firm delivers it.
Twenty-one public case studies. Five verticals. Three pillars. Every one delivered the same way — Aedeon absorbing the analyst tier, forward-deployed engineers owning the architecture and cutover, the engagement closing on customer-signed acceptance. The proof your board and your audit committee will recognize. And the proof that the agent-native delivery model is what makes these outcomes economically possible.
The Common Thread · 00
Every story is two stories.
Read any one of these case studies and you are reading two stories at once. The first is the customer's transformation story — a six-month claims cycle replaced in twelve weeks, a Hadoop database modernized without disrupting engagement, a chip-design cluster running 40% faster. The second is the delivery story — what changes about the engagement when an agent-native firm runs it. Aedeon does the discovery, mapping, validation, and observability work that a traditional SI would have staffed a pyramid of analysts for. Forward-deployed engineers own the architecture decisions, the cutover, and the customer-signed acceptance.
The two stories are inseparable. A traditional SI could not have shipped the customer outcome — not at the timeline, not at the cost, not with the date in the contract. The agent-native delivery model is the reason these stories exist as case studies and not as cautionary tales.
Start Here · 01
KlearTrust
Two pilots had stalled. The third reached production in twelve weeks.
KlearTrust had spent eighteen months on two prior attempts to put a claims-review agent into production. Both pilots reached a demo and stopped at the audit step. Mactores landed the third attempt on Bedrock — HIPAA-aligned, eval-harnessed, and signed off by Internal Audit on first review.
Read the full story →Claims-Review Cycle
6 months→12 weeks
Audit Posture
Passed first review
Architecture
Bedrock + Aedeon
All Stories · 02
KlearTrust
Claims-review cycle from six months to twelve weeks.
HIPAA-aligned agentic AI on Bedrock. Internal audit cleared on first review.
6mo → 12wkcycle time
Personalization platform replatformed; engagement up post-cutover.
"We're more resilient, and overall user engagement has improved." — Greg Scallan, VP Engineering.
+engagement & resilience
Synaptics
40% EDA throughput. 75% lower queue wait.
One of the largest EDA clusters on AWS, with smart queues replacing static partitioning.
40% / 75%throughput / wait
Poshmark
Zero-downtime migration on active marketplace.
The migration the internal team called impossible — landed agent-native.
0downtime
Fortune 500 Life Insurer
MBS pricing engine modernized without rewriting valuation logic.
Oracle to Aurora migration with pricing integrity preserved through cutover.
100%pricing integrity
Regional Bank
Branded card payments platform — legacy retired.
Mainframe-era payments logic moved to cloud-native, audit-ready architecture.
Legacymainframe status
Plume
Analytics run-rate down 58% after leaving Databricks.
All 20 workspaces moved to an AWS lakehouse in 18 weeks, with zero rollbacks.
58%lower run-rate
Safaricom
Africa's largest telco moved from menus to intent.
Zuri agent platform handling customer intent at continental scale.
Intentover menus
Sterne Kessler
Patent response time cut from 8-12 hours to 2-4.
AI-powered Office Action response framework on Amazon Bedrock.
8-12hr → 2-4hrresponse time
Sterne Kessler
Trademark classification: 2 hours to 10 minutes.
85%+ accuracy across 45 Nice Classes with AI-powered classification.
2hr → 10minclassification time
Renewable Grid Operator
Real-time grid decisioning with bounded agent authority.
Agentic intelligence layer deciding against real-time grid signals.
Real-timedecisioning
HP
Smart factory analytics at global manufacturing scale.
Production intelligence across HP's manufacturing footprint.
Globalscale
Tilia
Virtual economy payments platform modernized.
Payment rails for digital economies rebuilt cloud-native.
Cloudnative
In Their Words · 03
Engineering leaders. On record.
“We're more resilient, and overall user engagement has improved as a direct result of this migration. The Mactores team brought exceptional technical depth.”
Greg Scallan
VP of Engineering, Flipboard
“We improved throughput on one of our largest EDA clusters by up to 40%, and improved queue contention with 75% lower wait times using smart queues.”
Michael Brooker
CTO, Synaptics
“A big thank-you to the Mactores team for the execution. Poshmark recognizes how complex this project was — their expertise made it land.”
Gautam Golwala
Co-founder & CTO, Poshmark
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