Healthcare Data Platform on AWS: HIPAA-Aligned by Construction
Compliance engineered into the architecture, not audited after the fact. Mactores ships production healthcare data platforms on AWS on a committed date, for a fixed fee. If a delay is ours, we absorb the cost. If it is a customer-side blocker, that portion of the work is billed at a rate already named in the same document, agreed before anyone signs it.
Mactores is the agent-native AWS modernization firm. Agent-native describes what kind of company this is rather than a technique it uses: the commercial model, the team and the practice are all built around it.
Start with your compliance scope
Bring the PHI footprint and the date you are working against.
A scoping conversation ends with a scope, a production date and a fixed fee, or a straight answer on what has to change first.
- 60–70%
- of engagement hours absorbed by agents rather than 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; 18 years of production migrations
- AWS Services Partner
- Premier Tier
- AWS Specialization
- Agentic AI
- One of seven AWS Competencies
- Healthcare
- AWS Service Validations
- 17 Validations
Top Mactores Clients
Why Healthcare Data Platform Modernization Stalls Before It Reaches Production
Enterprise data teams in healthcare and life sciences have lived this pattern: a modernization program gets scoped, gets staffed, produces architecture diagrams and a compliance checklist, then stalls at the handoff between strategy and implementation. Or it limps through a pilot and never reaches production. Or it reaches production a year late, over budget, with a compliance review still pending.
The cost of that stall is no longer theoretical. IBM's Cost of a Data Breach report puts the average healthcare breach at 7.42 million dollars, the highest of any industry it tracks and the fourteenth consecutive year healthcare has held that position, with 279 days to identify and contain, roughly five weeks longer than the cross-industry average. In 2025, 710 large breaches were reported to the HHS Office for Civil Rights, exposing 61.5 million patient records.
Most vendors answer that risk with a compliance review bolted onto the end of the project. Mactores builds a healthcare data platform to pass that review from the first commit: agent-native modernization for systems that have to pass validation.
Where the program is now
If a healthcare data platform build has already stalled once, that history is useful to us.
Knowing where the last attempt stopped shapes the scope, and it usually shortens it.
Which Compliance Frameworks Does a Healthcare Data Platform Have to Satisfy?
Mactores healthcare data platform builds are engineered against the frameworks that govern US healthcare data. Designing against a framework is not the same as certifying you to it, and the certification stays yours and your assessor's.
- HIPAA
- HITECH
- HITRUST CSF
- NIST SP 800-66
What each framework asks for, and where the build produces it
| Framework | What it governs | How the build answers it |
|---|---|---|
| HIPAA Privacy and Security Rules | Access control, audit controls under 45 CFR 164.312(b), encryption, and the minimum-necessary standard | Built into the reference architecture from the start, with a Business Associate Agreement executed before any PHI is touched |
| HITECH Act | Breach notification obligations and the higher enforcement bar it introduced for business associates | Shapes how access logging and incident detection are architected from day one |
| 21st Century Cures Act | Interoperability and information blocking, where data is exposed through APIs to patients, providers or partner systems | Shapes the data layer so it is reachable by everyone with a right to it, and closed to everyone without one |
| HITRUST CSF | A single certifiable control environment where an organisation maps beyond a HIPAA-only checklist | The same underlying controls satisfy both, so access management, encryption, audit logging and risk cadence are not built twice |
| NIST SP 800-66 | The implementation reference for translating HIPAA Security Rule controls into configuration | Used during architecture design to settle the actual AWS configuration decisions |
The HIPAA mark appears as published and is not recoloured. HITECH, HITRUST and NIST are named in type because their owners do not license a mark for this use. Naming a framework indicates what the delivery work is designed against, and not endorsement or certification by that body.
Bring your last audit finding
We will show you which phase exit produces the evidence for it.
The documentation package is the same set your internal audit team would assemble by hand afterwards.
The Delivery Process, Phase by Phase
Five phases, each closing on customer-signed acceptance before the next one opens. The same five gates run on every Mactores engagement, and on a healthcare data platform build they are also where the compliance evidence is produced.
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01
Scoping and fixed-date commitment
Typically one to two weeks. Discovery and PHI data-flow mapping across source systems, with the target architecture defined against your compliance scope: Business Associate Agreement coverage, HIPAA Security Rule controls, minimum-necessary access design. The statement of work is signed with a committed production date and a fixed fee attached to it.
Exit
Scope, date and fee signed
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02
Compliance baseline and target design
The control set is fixed before anything migrates. Encryption, role-based access mapped to the minimum-necessary standard, PHI classification and audit logging are documented against the HIPAA Security Rule and, where you map to it, HITRUST. Your compliance and security owners review the mapping here rather than at the end.
Exit
Control mapping accepted
-
03
Build against non-production copies
Schema mapping, data migration and lineage extraction run against non-production copies first. Every artefact, schema diffs, access logs and validation results, stays traceable to source for your compliance and audit teams.
Exit
Build reviewed in your environment
-
04
Parallel validation on live workloads
A validation harness runs in parallel against live workloads to prove throughput, latency and data integrity before anything is cut over. Forward-deployed engineers make the architecture and cutover-risk calls, and explain any variance before anyone signs.
Exit
Validation results accepted
-
05
Staged cutover and audit-ready handoff
Staged cutover with customer-signed acceptance at each phase exit. Legacy systems retire on schedule. You receive the documentation set an assessor asks for: the lineage, the access control mapping, and the validation evidence behind both, ready to hand over without assembling anything by hand.
Exit
Production acceptance signed
Delays caused by Mactores do not extend your fee. That overage is absorbed on our side under the standard clause in the statement of work. Where the cause sits on your side, that portion moves to the standard rate printed in the statement of work, so nothing about it is negotiated after the event.
The clause behind the date
The date, the fee and the overage terms are contract language.
Our commitment page sets out exactly what enters the statement of work at each of these five gates.
How Much Does a Healthcare Data Platform on AWS Cost?
Every Mactores engagement is fixed-fee. The number itself is set after scoping, because a defensible fixed fee requires knowing your source system count, data volume, PHI classification scope and target AWS footprint first.
What moves the number, and where each one is settled
| What moves the fee | What pushes it up | Settled at |
|---|---|---|
| Source systems | More systems and more legacy variety, including multiple EHR instances or acquired estates | Discovery, during scoping |
| Data volume and retention | Larger PHI datasets, longer retention windows, archival requirements | Scoping call and discovery |
| Compliance scope | Broader PHI classification, multiple Business Associate Agreements, cross-entity data sharing | The compliance baseline step in phase 02 |
| AWS footprint and integration surface | More downstream consumers such as reporting, analytics and partner systems | Target architecture design |
Where the funding usually comes from
Much of the budget for this programme is already inside your existing IT spend: a legacy database licence coming up for renewal, a legacy data warehouse nobody fully depends on any more, an integration layer that bills hours largely to keep itself running. Each is a candidate for reallocation toward a fixed-fee modernization rather than a new budget request.
Pricing disclaimer. Any pricing, cost ranges or savings language on this page, including the fixed-fee model itself, is directional and illustrative only. Final scope and fee are determined during a scoping call and documented in a signed statement of work. Nothing on this page constitutes a quote.
Put your own numbers against it
Bring the licence, warehouse and integration lines you are already paying.
Half an hour with the engineer who would scope the work, and the fixed fee stops being an abstraction.
Which AWS Credentials Sit Behind This Work?
Everything above is Mactores describing its own delivery model. This part is not. AWS runs its own technical review before granting any of these, which makes them the claims on this page you can verify without asking us.
AWS Premier Tier Services Partner, with the AWS Healthcare Competency. Mactores also holds the AWS Agentic AI Specialization, the credential most directly behind the delivery model described on this page. Each item below is listed publicly, so procurement can confirm it in the AWS Partner Solutions Finder before the first call.
- Specialization
- AWS Agentic AI
- Competencies
- 7, including Migration and Modernization
- Service validations
- 17 across data, ML and infrastructure
- Certified engineers
- 200 and counting
- Building on AWS since
- 2008
- Partner tier
- Premier
The AWS services that carry the most weight on this build
AWS Database Migration Service moves data off the legacy systems, AWS Glue handles schema mapping and transformation, Amazon Redshift and Amazon RDS carry the target warehouse and relational stores, and AWS Lambda runs the automation layer connecting them. Where clinical data needs structuring, Amazon HealthLake and Amazon Comprehend Medical extract and normalize health information into a usable, compliant format. Every service named here is covered by the AWS Business Associate Addendum, which is checked during architecture design rather than assumed.
The Agentic AI Specialization is named in words because we hold the credential and not the badge artwork. Full detail is on the partners page.