Legacy Software Modernization Services
As an AWS Premier Tier Services Partner, Mactores modernizes legacy software and databases by moving them from end-of-life stacks to AWS. We handle discovery, refactoring, schema conversion, validation, cutover, and legacy decommissioning.
The scope, timeline, and price are locked in the SOW before build begins. If we cause the delay, we absorb the cost.
Most modernization programs stall in discovery, stop at a pilot, or go live while the legacy system keeps running—and billing. The next section shows where yours is stuck.
Talk to us
Legacy applications and databases on cloud-native AWS, on a fixed date, for a fixed fee.
You leave knowing whether the date is reachable and what the work actually involves.
- AWS Partner Tier
- Premier Tier Services
- AWS Specialization
- Agentic AI
- Incl. Migration & Modernization
- 7 Competencies
- AWS Service Validations
- 17 Validations
60–70%
Engagement hours carried by agents instead of billed as analyst time
12 wks
Median time to production across Mactores engagements
21
Public case studies with named customers
200+
AWS-certified engineers
2008
Building on AWS since, with 18 years of production migrations
Top Mactores Clients
Where Legacy Modernization Actually Dies
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01
Discovery that never becomes a build plan.
The team maps the estate, documents dependencies, produces a migration architecture, and the deck becomes the deliverable. With no committed cutover date on the other side of discovery, discovery expands to fill the calendar. A regulated payments platform we later took on had lived this twice: two prior modernization attempts, both of which consumed their budgets in analysis and stalled before a single workload cut over. The debt didn't move for years, because nothing after “understand the system” was ever scheduled. -
02
A pilot that proves the technology and nothing else.
Something works in a sandbox account against a subset of data, everyone agrees it can be done, and then no one puts a production date on it. A pilot has no cutover, so it can't fail publicly, which is exactly why it's safe to let it sit forever. -
03
A false trade-off that shrinks the scope to fit the deadline.
Partway through, the team discovers that fixing what the business asked for (security posture, say) appears to cost something the business also needs (transaction throughput). Scope gets cut to protect the date, instead of the plan being reworked to protect the scope. A payments infrastructure client came to us after being told exactly this: that better transaction security and better operational efficiency were mutually exclusive on their platform. They weren't. The earlier approach had simply been optimized to look done on schedule. -
04
Cutover happens, but the legacy system never gets switched off.
The new system goes live, everyone celebrates, and the old system stays running “for a few more months, just in case,” which is how a few more months becomes a few more years. The license renewal the CFO was promised would disappear keeps renewing. This is the quietest failure mode, because on paper the project succeeded.
Scope around the real risk
Four specific points where a program stalls — each turned into a named, dated, contractually owned checkpoint.
You leave knowing whether the date is reachable and what the work actually involves.
What Do Legacy Software Modernization Services Include?
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01
Evidence-based discovery of code, schema and integration dependencies, ending in a build plan with a cutover date attached rather than an assessment deck.
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02
Refactoring and schema conversion, with FDEs deciding what is rearchitected, what is lifted, and what is retired outright.
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03
Parallel-run validation that compares the modernized system's behavior with the legacy system's under live conditions before anyone schedules cutover.
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04
Production cutover with a go/no-go decision owned by a named FDE and rollback criteria agreed with your team in advance.
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05
Post-cutover optimization, runbooks and knowledge transfer so your own team runs the system afterward.
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06
Legacy switch-off: decommissioning the old application, database and supporting infrastructure, including stopping the license renewals attached to them.
Application & Database Modernization is one of three delivery pillars. See what Mactores ships across all three.
Check your migration path
Tell us the application and the source database, and we will show you where that path has already run.
Oracle or SQL Server to Amazon Aurora are the routes with the most case history behind them.
What We Won't Do
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We won't scope a discovery-only engagement with no committed cutover date attached.
That's failure mode #1, and we've seen it happen to a client twice before we got involved.
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We won't take a system to production without parallel-run validation proving it behaves like the legacy system first.
Cutover judgment belongs to an FDE who has staked their name on it, not to a scripted rollback plan nobody has tested.
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We won't stay on as a permanent operations team after post-cutover optimization closes.
The point of the engagement is a system your own team can run, not a dependency on ours.
Who this is built for
Who this isn't built for
How a Fixed-Date Legacy Modernization Engagement Runs
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01
Discovery that ends in a date
Agents analyze code, schemas and integrations across the estate, and FDEs turn that output into a target architecture and migration sequence. Discovery has a fixed end, and what comes out of it is a build plan, not a report. This is where failure mode #1 is closed.Phase exit
Scope, cutover date and fixed fee signed into the statement of work.
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02
Build with parallel-run validation
Refactoring and schema conversion run against a validation step that compares new and legacy behavior on live data as the work progresses. Nothing stays a sandbox experiment, because every component is being proven toward a production date. Trade-offs such as security versus throughput are tested against real workloads here, instead of being settled by cutting scope. This is where failure modes #2 and #3 are closed.Phase exit
Customer-signed acceptance record for the validated build.
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03
Cutover
Cutover is rehearsed before it's executed. The go/no-go decision sits with a named FDE, and rollback criteria are agreed with your team before the window opens.Phase exit
Go/no-go confirmed and rollback criteria signed off.
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04
Post-cutover optimization and legacy switch-off
FDEs tune the new system under real production load, hand over runbooks and architecture documentation, and confirm the legacy environment can be decommissioned. The engagement isn't finished while the old system is still running. This is where failure mode #4 is closed.Phase exit
Legacy system decommissioned and its license and infrastructure lines closed.
On duration
A single-database, single-application migration against a well-understood schema closes in weeks. A multi-year technical-debt portfolio carrying live regulatory sign-off requirements (the shape of the payments engagement below) also closed in weeks, not months, because discovery no longer consumed the calendar the way it had in two earlier attempts. \"It depends on scope\" is true of every engagement on earth. The useful version of that sentence is the week count for a specific portfolio, which is fixed at scoping, not held back until after it.
Start at Phase 1
Phase 1 ends with scope, cutover date and fixed fee signed, not estimated.
Every phase closes on a customer signature before the next one starts.
Three Engagements, What Actually Moved
Three engagements from Mactores' named reference set. Each describes one engagement, not a promise about yours, but together they give the claims above something more specific to stand on than an industry average.
Legacy Modernization · Semiconductor
40%
Higher throughput on one of Synaptics' largest EDA clusters
75%
Lower queue wait times using smart queues
Synaptics: EDA cluster bottleneck turned into a scheduled build
Chip-design workloads were stalling on job-queue contention, and design teams were losing cycles to waiting instead of shipping designs. Mactores ran discovery on the cluster estate, then built smart queues on top of an operational data lake on AWS. This is failure mode #1 avoided: discovery converted into a scheduled build, not a deck.
Full storyLegacy Modernization · Payments
Zero
Audit incidents, aligned to PCI DSS
2 → 1
Two earlier attempts stalled in discovery. One engagement reached production.
A regulated payments platform: two stalled attempts, then one that shipped
This is the estate described in failure mode #1: multi-year technical debt and two earlier modernization efforts that spent their budgets in discovery and never reached cutover. The engagement that shipped moved mainframe-era payments logic to cloud-native AWS, cleared the debt in a single pass, and passed audit with zero incidents. Because discovery no longer consumed the budget, the team's velocity on new feature work doubled afterward.
Full storyLegacy Modernization · Payments
Both
Transaction security and operational efficiency, one engagement
0
Platform swaps — both delivered on the existing platform, aligned to PCI DSS
Tilia: the trade-off that wasn't real
This is failure mode #3. Earlier partners had told this payments infrastructure business that improving transaction security and improving operational efficiency on the same platform were mutually exclusive: pick one. They weren't. Mactores analyzed both layers in one engagement and designed an architecture that delivered both on the existing platform.
Full storyThree engagements are a starting point, not the whole record. The full case study library covers more work across industries and all three delivery pillars.
Ask for the closest reference
We will name the engagement nearest your stack, not the category.
Named accounts and audited figures are shared under NDA during commercial discussions.
Where This Sits Against the Alternatives
- Big 4 or strategy-led firm
- Strong at the assessment and architecture layer and usually hands the build to a systems integrator or to the customer's own team, which is where failure mode #1 tends to begin.
- Tier-1 systems integrator
Delivers at scale on time-and-materials staffing, with its commercial incentive pointed at more billed hours rather than a fixed date.
- AWS ProServe
- Brings deep platform expertise and is often the right call for AWS-native architecture guidance, but doesn't typically carry a fixed-fee, delay-absorbing commitment on a legacy estate.
- In-house team
- Knows the system best and is also the team already fully booked keeping it alive, which is usually the real reason the modernization hasn't happened, not a skills gap.
What's different here isn't a claim to being better across the board. It's that the commercial model (fixed date, fixed fee, Mactores absorbing its own delays) only works because of how the engagement is staffed, and that structural fact is the whole basis for comparison.
Agent-native by structure
One legacy estate, one committed date, and a firm that absorbs the cost of a delay it causes.
How that delivery model works across every engagement is set out on the how we work page.
Compliance, Named and Explained
Compliance evidence can come from two places: the delivery process itself, or a clean-up exercise at the end that works from whatever documentation survived. This model is designed around the first. Every phase closes with a customer-signed acceptance record, and parallel-run validation produces traceable, source-linked evidence as it runs. For US-based programs, that evidence supports:
"Built around" means the acceptance records and validation evidence exist because every phase exit produces them, not because a separate compliance project was added later to recreate them.
Audit-ready by default
Acceptance records and validation evidence exist because every phase exit produces them.
Bring the scope your examiner cares about and we will map it to the phase exits that produce the evidence.
Which Industries Does Legacy Modernization Serve?
The four failure modes show up in every sector. What differs is which one does the most damage.
Financial Services
Core banking, card and trading platforms where failure mode #1 is most common, because every discovery phase also has to satisfy risk and compliance reviewers. Validation evidence is structured for examiner review from the first phase.
Financial servicesHealthcare & Life Sciences
Claims, clinical and research applications carrying PHI, where cutover planning includes data-handling controls, and legacy switch-off includes a documented retention decision for the records the old system held.
HealthcareInternet & Software
Legacy code that makes every deploy a coordinated event, split into services each team ships independently and tuned for the latency users expect.
Internet & SoftwareManufacturing
Plant and supply-chain systems where downtime is measured in lost output. Cutover windows are planned against production schedules, and parallel-run validation uses operational data before the switch.
ManufacturingTelco, Media, Entertainment, Gaming, and Sports (TMEGS)
Subscriber, billing and content systems with no quiet hours. Validation includes peak-traffic behavior, so a cutover date is set on proven capacity rather than hope.
TMEGSThe delivery model stays the same in every vertical. What changes is emphasis: governance for regulated data, continuity for operational systems, speed for product-led teams.
Scoped to your sector
The four failure modes show up everywhere. Which one does the most damage is what changes by industry.
Governance for regulated data, continuity for operational systems, speed for product-led teams.
What Drives the Fee
Disclaimer: figures, ranges or tiers referenced anywhere on this page are illustrative until confirmed for a specific portfolio at a scoping call. They are not a quote.
The fee and the date are fixed once scoping closes, and both are set against the portfolio in front of us, not priced off a rate card, because the delivery model isn't built around billable hours to begin with.
What Standing Still Actually Costs
The industry-wide numbers are real, but none of them is the number that matters for your estate. Research by Pega and Savanta estimates the average global enterprise wastes more than $370 million a year because it can't modernize legacy systems efficiently. Technical debt is estimated to absorb 21 to 40% of IT spend across the industry. And in a 2026 survey of 1,550 enterprise technology leaders, legacy systems not built for AI were the most frequently named barrier, ahead of fragmented data and siloed teams. Quote any of those in a pitch and a competitor can quote them right back. They describe the industry; they don't diagnose your estate.
Your own number is arithmetic
Take the Oracle or SQL Server license renewal that's coming up, the legacy data warehouse nobody has run a new workload against in two years, and the integration tier that bills hours just to keep itself alive. Add up what those cost each year, and that total is the AI budget a board would otherwise have to approve as new spend. A twelve-application estate carrying a single six-figure database license has a six-figure AI compute allowance the day that license lapses instead of renewing: not a projection, but a line item that stops recurring. The scoping call runs the actual number for your portfolio; the shape of the arithmetic is the point here.
Make the numbers yours
Put your own license, warehouse and integration lines against the four drivers above.
The scoping call runs the actual number for your portfolio, and the fixed fee stops being a range.
Terms Worth Defining
- Agent-native
- How Mactores is built, not a tool it happens to use. Agents carry most of the engagement hours, the people are specialists rather than generalist consultants, and the contract commits to a delivery date. Take the agents away and the fixed-date, fixed-fee model stops working.
- Forward-deployed engineer (FDE)
- The Mactores role that embeds with a customer's team, owns refactoring and cutover judgment personally, and carries the delivery commitment by name, not by title.
- Fixed-date, fixed-fee delivery
- The commercial model where the date and fee are set at scoping and don't move for reasons inside Mactores' control. Mactores absorbs overage cost it causes, and customer-caused delays convert to time-and-materials at standard rates agreed in advance.
- Statement of work (SOW)
The signed document that holds the scope, cutover date, fixed fee and delay terms for an engagement. It is the number and date that bind, whatever a page or proposal says.
- Legacy system
- A production application and its database that cost more to keep running than to replace, whether through license renewals, integration upkeep or change that has become too risky to attempt.
- Technical debt
- The accumulated cost of shortcuts, deferred upgrades and undocumented dependencies that makes every future change to a system slower, riskier and more expensive.
- Parallel-run validation
- Running the modernized system alongside the legacy system on live or production-representative data and comparing their behavior, so differences surface before cutover rather than after it.
- Phase exit
- The formal close of an engagement phase, marked by a customer-signed acceptance record. No phase closes, and no next phase starts, without it.
- Cutover
- The moment production traffic moves from the legacy system to the modernized one, executed against a rehearsed plan and agreed rollback criteria.
- Hypercare
- The period right after cutover when FDEs stay engaged to tune performance under real load and hand operations over to the customer's team.
- Legacy switch-off
- Decommissioning the old application, database and infrastructure once the new system is proven in production, including ending the licenses and contracts tied to them.
- Time-and-materials (T&M)
Billing by hours worked and resources used rather than a fixed price. In this model it applies only to delays that originate on the customer side, at rates disclosed in the SOW.
The commitment in full
Read exactly what Mactores is on the hook for.
The cutover date, the fixed fee, and who carries the cost if that date moves — in contract language you can check line by line.
What This Actually Runs On
Vague credentialing is easy to write and easy to ignore. Here's what sits under the claim.
Mactores is an AWS Premier Tier Services Partner, the highest partner tier AWS grants, earned on delivery evidence rather than self-attestation. It also holds the AWS Agentic AI Specialization, which AWS awards specifically for agent-based delivery.
Mactores holds 17 AWS Service Validations. The ones this work touches directly are Amazon RDS, AWS Database Migration Service, AWS Glue, AWS CloudFormation, AWS Lambda, Amazon DynamoDB, AWS Control Tower and Amazon EC2 for Windows Server: the services a database and application migration actually runs on, not an unrelated list. The remaining validations sit under the Data Platform Modernization pillar. These sit inside 7 AWS Consulting Competencies, including Migration and Modernization, backed by 200+ AWS-certified engineers and a history of building on AWS since 2008.
None of that is a substitute for naming the failure modes above or the engagements that back them up. It's the floor underneath both, and because AWS grants each credential after its own review, it's the one part of this page you can check in the AWS Partner Solutions Finder without taking our word for it.
- Specialization
- AWS Agentic AI Specialization
- Partner tier
- AWS Premier Tier Services
- Applies to this page
- Migration & Modernization
- Service validations
- 17 Service Validations
- Team
- 200+ AWS-certified engineers
- Building on AWS since
- 2008
7 Consulting Competencies
- Migration and Modernization
- DevOps
- Data and Analytics
- Machine Learning
- AI Services
- Healthcare
- Manufacturing and Industrial Services
Verified by AWS
Every credential here is granted by AWS, so you can check it without us.
The tier, the specialization and every competency are listed in the AWS Partner Solutions Finder.