The Agent-Native AWS Modernization Firm

The AI era runs on systems that work.
We build them.

Mactores delivers the modernizations that decide the next decade: bets that compound for years, finished in weeks instead of quarters. On a fixed date. At a fraction of the hours of a traditional proposal. With customer-signed acceptance, not status decks.

60–70%

Engagement work absorbed by Aedeon

Fixed fee

Customer-signed acceptance, every engagement

12 weeks

Median time to production

21

Public case studies with named customers

100%

Forward-Deployed Engineers who have shipped production agentic AI on AWS

AWS Advanced Tier Services Partner · Agentic AI Specialization · 7 Consulting Competencies · 14+ Years on AWS

See full partner detail →

Why This Moment

The next decade of competitive advantage is being decided right now.

The Pattern Leaders Recognize

The companies that put AI to work in their operations in the next twenty-four months will set the architecture the rest of the category reacts to in 2027 and 2028. The companies that ran AI pilots and stopped will spend the same decade catching up. The cost of stalling has already been priced into the cost of buying.

The Mactores Claim

We exist to deliver the modernizations that put AI to work in real operations, not the strategy decks about it. Production systems running. Legacy retired. Real outcomes measured in real currency. Our customers' AI investments compound. Their competitors' AI investments stall.

Read the thesis →

What We Ship

Three things change at once. We deliver all three.

01

Data Platform Modernization

The data foundation that decides what AI can read, ground against, and act on. Modernized in weeks, not quarters. Lower engagement cost than traditional consulting.

See data work

02

Application & Database Modernization

The legacy stack that prices into every future AI decision, retired on a date we put in the contract. Oracle and SQL Server replaced. Technical debt cleared. Capital reallocated.

See app & DB work

03

AI Agents for Apps

Agents that work in real operations, not POCs. Customer support that handles intent. Claims systems that pass audit on first review. Grids that decide in real time.

See agent work

The Economics

Most of the AI budget you think you need is already in the building.

The capital-allocation question every CFO is now solving for: how to fund a multi-year AI program without growing the IT budget. The answer is in the building. The legacy database license. The data warehouse renewal. The integration tier that bills hours to keep itself alive. Each line is paying interest on systems built for a world that has ended. Each line is a candidate for reallocation.

Where the budget is trapped today

  • Annual renewals on legacy database and ERP nobody loves
  • Pipelines and integrations that bill maintenance hours to stay alive
  • Multi-quarter consulting engagements that produce decks, not production systems
  • Change orders against modernizations that never reached the production goal

Where the budget should reallocate

  • A cloud-native data foundation that AI can actually read against
  • Application and database refactors that retire the debt permanently
  • Production agentic platforms running against real data and real workloads
  • Forward-deployed engineering paid to ship, not to staff

The companies that pivot inside their existing IT envelope in the next twenty-four months will fund their AI program from the budget they already have. The companies that do not will be the ones asking their boards for a budget increase to fund a program their competitors have already shipped. The first move is reallocation.

Read the funding-AI POV →

How We Deliver

Two assets that change the unit economics of modernization.

Most consulting firms staff modernization with a pyramid: a junior pool under a thin senior layer. The economics depend on hours billed. We replaced that pyramid with two assets: Aedeon, an agent platform that absorbs 60–70% of the engagement work, and forward-deployed engineers who own architecture, cutover, and customer relationship personally.

Aedeon

AGENT PLATFORM

01 · ASSESS

Discovery scan, source mapping, dependency graph

02 · DESIGN

Architecture analysis, options modeled, cost projection

03 · BUILD

Code translation, pipeline scaffolds, observability

04 · TEST

Replay validation, regression harness, audit logging

05 · DEPLOY

Cutover automation, monitoring, FinOps watch

Forward-Deployed Engineers

SENIOR DELIVERY

01 · ASSESS

Frame the problem with the executive team

02 · DESIGN

Target architecture, trade-off decisions, SOW

03 · BUILD

Refactor judgment, agent authority boundary

04 · TEST

Cutover plan, risk-weighted sequencing

05 · DEPLOY

Customer-signed acceptance, on-call handover

Customer team

OWNS IT AFTER

01 · ASSESS

Roadmap signed

02 · DESIGN

SOW countersigned

03 · BUILD

Domain validation, business rules

04 · TEST

Acceptance gate passed

05 · DEPLOY

Acceptance signed · runs the platform

Aedeon absorbs ~60–70% of engagement hours
FDEs own architecture, cutover, sign-off
Customer signs every phase exit

Aedeon Does

The discovery, mapping, validation, and observability work that traditionally consumed analyst hours.

FDEs Own

The architecture decisions, the cutover, and the customer-facing commitment, personally, not as account-team relay.

The Contract Carries

The delivery date. Mactores absorbs overage on delays inside our control.

Read how we work →

Our Commitment

Fixed date. Fixed fee. Customer-signed acceptance.

Every Mactores engagement closes on customer-signed acceptance, not a status review. The five-phase delivery has named exits the customer's CFO and CIO sign at each gate. Mactores absorbs overage on delays inside our control. Customer-caused delays convert to T&M at standard rates. The commercial structure exists because the delivery model justifies it.

Fixed date

Fixed fee

Overage on us

Signed acceptance

Read the commitment →

In Production

A six-month process, replaced in twelve weeks.

KLEARTRUST

Pillar · AI AgentsVertical · HCLS

Baseline

6 months

of clinical claims-review cycle

Outcome

12 weeks

to production

Time to Value

12 weeks

KlearTrust replaced a six-month manual claims-review cycle with a HIPAA-compliant agentic AI platform on AWS Bedrock. Clinician time now reallocates to the edge cases that need it. Internal audit and HIPAA review passed on first cycle.

Executives, In Their Words

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

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

Michael Brooker

CTO, Synaptics

A big thank-you to the Mactores team for the execution. Poshmark recognizes how complex this project was, and their expertise made it land.

Gautam Golwala

Gautam Golwala

Co-founder & CTO, Poshmark

KlearTrust logo
Synaptics logo
Flipboard logo
Poshmark logo
Seagate logo
HP logo
Adani Power logo
Tilia logo
DocuSign logo
TotalExpert logo
Sterne Kessler logo

The Mactores Advantage

What you've been buying, and what you should be buying instead.

The model you've been buying

  • Hourly billing
  • Strategy decks and slow handoffs
  • Pyramid staffing
  • Multi-quarter timelines
  • Change-order spirals

The Mactores model

  • Fixed-date and fixed-fee
  • Production systems live
  • Forward-deployed engineers
  • Weeks to production
  • Customer-signed acceptance

The right side of this comparison is a different kind of firm, not a better version of the left.

For Your Role · 10

One firm. Four reads. Pick yours.

Mactores reads differently from each side of the executive table. Below is the single thing each CXO role takes from working with us. The four reads describe the same firm.

For the CEO

Competitive position in the AI era.

Mactores lands the modernizations that decide the next decade. Production systems running. Legacy retired. Named customers in production. The board narrative is defensible because the numbers and the customer names hold up to scrutiny. The companies that move now set the architecture competitors will spend 2027–28 reacting to.

For the CFO

AI as a capital-allocation question, not an R&D one.

Fixed date. Fixed fee. Mactores absorbs overage on delays inside our control. Most of the AI budget reallocates from inside the existing IT envelope: the legacy renewals, the integration hours, the multi-quarter consulting projects that never reached production. The CFO files this as reallocation, not new spend.

For the CTO

Production agentic systems on architectures that survive five years.

Built around forward-deployed engineers who have shipped production agentic AI, not a pyramid of generalists with a thin specialty layer. Architecture decisions made by the people who will run the result. Aedeon absorbs the analyst-tier work that would otherwise consume engineering cycles. The architecture is delivered by the firm whose own delivery model is agent-native.

For the CIO

Modernization without taking the business offline.

Cutover-safe by construction. Audit evidence captured at decision time, not reconstructed after. Customer-signed acceptance at each phase exit; engagements close on signed paperwork, not on status decks. The operations team owns the running system on day-after-cutover. No hanging change orders. Clean account closure.

Let's Deliver

Start the conversation.

Thirty minutes with a Mactores forward-deployed engineer to shape your modernization. No procurement pre-qualification. No slide decks. The first conversation is a working session, and you leave with a real view on whether we are the right partner for what you are trying to land.

01 · Send the note.

A one-line message to lets-talk@mactores.com describing the modernization you want to land.

02 · We come back inside 24 hours.

A short reply confirming fit and proposing a working-session time. If we are not the right firm for the work, we say so.

03 · The working session.

Thirty minutes with a forward-deployed engineer, the person who would actually run your engagement. You walk out with a fixed-fee discovery-sprint scope if we are a fit.

Let's deliver.