Why Mactores
The AI era will be decided by what reaches production.
We exist to deliver it.
Most enterprises have spent the last three years running pilots. The companies that will win the next decade are the ones that put AI to work in their operations now, at scale, on real workloads, on a date their board can plan around. That is the work this firm was built to deliver.
The Pattern
Most AI investment never reaches operations.
Two decades of enterprise IT have followed the same pattern. A program starts. It is scoped by one partner and staffed by another. It produces decks and architecture diagrams. It stalls at handoff between strategy and implementation. It limps through a pilot. It never reaches production, or it reaches production a year late at three times the budget.
The pattern is so consistent that finance teams have priced it in. Two-to-three times the budget. One-and-a-half-to-three times the timeline. Three out of four programs never reaching the production goal originally signed off. AI is now repeating the same arc: pilots that win innovation awards and fail to land in revenue, in cost, or in customer experience.
Most firms have added AI to traditional consulting. We were built around AI from day one.
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 do we fund a multi-year AI program without growing the IT budget. The answer is in plain sight. The legacy database license. The legacy data warehouse. The stored-procedure layer no one understands. 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.
The companies that pivot in the next twenty-four months will fund their AI program from inside their existing IT budget. 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.
Where the budget is trapped today:
- Renewals on legacy database and ERP nobody loves
- Pipelines and integrations no one built and no one owns
- Hours billed by partners who staff and do not ship
- Change orders against programs that never reached production
Where the budget should go:
- A cloud-native data foundation that AI can actually read
- Application and database refactors that retire the debt permanently
- Production agentic platforms running against real data
- Forward-deployed engineers paid to ship, not to staff
The Firm
Built around AI from day one.
Mactores is not a consulting firm that added an AI service line. The firm is structured around two assets that did not exist when traditional consulting was built. An agent platform, Aedeon, that absorbs 60–70% of the engagement work. A team of forward-deployed engineers who own architecture, judgment, and cutover personally. The combination is the firm. It is not the methodology. The methodology slides look standard. The economics inside them are not.
Aedeon does what would otherwise be a pyramid of analysts. Forward-deployed engineers do what would otherwise be a thin senior layer with no time to execute. The result for the customer: modernization delivered to production on a fixed date, at meaningfully lower hours than a traditional proposal of equivalent scope, with a contract that carries the commitment.
The Numbers
60–70%
fewer hours
Leaner
Fixed
date and fee
Surer
14+
years on AWS
Deeper
21
public case studies
Proven