AWS-NATIVE DATA MODERNIZATION

Every day you run your old stack, someone is paying for it.

Not in theory. In developer hours that never return. In decisions made on data that is 36 hours old. In AI initiatives that stall because no one trusts the foundation underneath. LakeStack ends it in weeks, not quarters.

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Building enterprise-grade data and AI solutions since 2014

HOW LAKESTACK WORKS

Five layers. One system. Live in 1–2 weeks.

LakeStack doesn't extend your existing stack, it replaces the foundation underneath it. Five interconnected layers, deployed as a single system, live in one to two weeks.

STEP 01

Automated pipeline management

Schema-aware, self-healing pipelines connect every source. When upstream systems change, pipelines adapt, no ticket, no intervention.

100 GB+ per flow run

STEP 02

Metadata-driven transformation

Raw data is normalized and structured via AWS Glue without hand-coded logic. Schema evolution is handled automatically.

75–85% less ETL effort

STEP 03

Governance built in, not bolted on

Lake Formation, KMS, CloudTrail, and Macie deploy as structural controls from day one, enforced at the data layer, not the application layer.

80% faster than manual

STEP 04

Near real-time availability

CDC pipelines continuously capture changes from live systems, delivering data to dashboards, AI models, and workflows within seconds.

<20s end-to-end latency

STEP 05

Governed self-service access

QuickSight, Redshift, and Athena connect directly to the modernized foundation. Every authorized team accesses trusted data without routing through engineering.

Zero engineering dependency

WHAT MODERNIZATION DELIVERS

Real outcomes. Not projections.

These aren't estimates. They're what teams consistently experience after replacing fragmented pipelines with a governed, automated foundation.

Outcome

Time to production

Engineering effort

Data freshness

Governance

AI readiness

Scaling cost

Result

1–2 weeks instead of 8–12

Under 200 hours, not 2,000+

Near real-time, not 24–48 hour delays

Live from day one, not phase two

Day one, not a separate future initiative

Linear and predictable, not non-linear

Built on AWS. Owned by You.

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Applify, the team behind this AI innovation, built LakeStack as a true AWS-native data foundation that lives entirely inside your AWS account, giving you full sovereignty, governed lakehouse capabilities, and production-ready AI value in weeks, without tool sprawl or external dependencies.

Supports Agentic AI using Bedrock and SageMaker
Uses Apache Iceberg open table format
Enforces Lake Formation fine-grained governance
Handles schema drift automatically every time
Provides built-in active metadata and lineage
Features self-healing real-time pipelines
Eliminates all third-party tool dependencies
Enables query flexibility with any engine
Ensures full data sovereignty and control
Offers automatic sensitive data classification

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Ready to see it in your environment?

See your core systems unified inside your AWS account
Experience governed dashboards built on your real data
Validate time to value before committing to full rollout

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Why LakeStack

The moment your data becomes an asset, not a liability.

Area

Before LakeStack

After LakeStack

Pipeline maintenance

Manual, engineer-dependent, breaks on schema changes

Automated, self-healing, adapts without intervention

Data freshness

24–48 hour batch delays

Near real-time, continuously updated

Governance

A future project. Always phase two.

Structural, enforced from day one

Time to production

8–12 weeks

1–2 weeks

Engineering effort

2,000+ hours to build and maintain

Under 200 hours

AI Readiness

Separate future initiative, blocked by data quality

Day one, on governed continuously updated layer

Data access

Siloed, request-dependent

Governed self-service for every authorized team

Case Studies

What replacing the foundation actually unlocks.

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Browse customer stories

Unified CRM, workshop, and invoicing data into a single governed data foundation, enabling real-time reporting and operational visibility across locations.

80%

Reduction in manual data preparation and processing

70%

Faster access to operational insights across teams

Frequently asked questions

Is this just another migration project with a better pitch?

No. Migration moves data. LakeStack replaces the approach: fragile pipelines become self-healing ones, manual workflows become governed automation, deferred governance becomes structural controls. The result is a modernized foundation, not data in a new location.

Do we have to shut anything down to get started?

No. LakeStack connects to your existing source systems and builds the modernized layer alongside them. Your current tools and workflows keep running while we replace the foundation underneath.

What happens to our historical data?

It's ingested and structured into Apache Iceberg open table format on Amazon S3 from day one. Full historical availability, in a governed, queryable format, nothing is lost or left behind.

How do you handle governance without making it a separate project?

By making it the project. Lake Formation, KMS, CloudTrail, and Macie are deployed as structural components, not configured after the fact. Governance is live before your first dataset is ingested.

What does this actually cost?

LakeStack runs entirely on your existing AWS infrastructure. The subscription is $18,000 annually — replacing an ongoing custom pipeline maintenance cost that was already consuming far more than that in engineering time.