What is a data lake on AWS?

A centralized storage on Amazon S3 where you keep all your data in its original format. Lake Formation adds governance and permissions on top. Unlike a warehouse, you store everything first and decide how to query it later.

How long does it take to set up?

A basic data lake with ETL pipelines takes 3 to 6 weeks. Adding BI dashboards and AI integration adds 2 to 4 weeks. Depends on number of data sources and transformation complexity.

Can we use our data lake for AI?

Yes. AWS Bedrock Knowledge Base connects directly to S3. The cleaner your data, the more accurate your AI responses. This is one of the strongest reasons to invest in a proper data lake.

How much does it cost?

S3 storage is around $0.023/GB/month. Glue ETL is billed per run. Athena charges per query. Most early-stage data lakes cost $50–$200/month. We optimize with Parquet formats and partitioning to reduce costs.

Do we need a data warehouse too?

Usually not. Athena lets you query S3 directly without a warehouse. For most startups this is enough and much cheaper. If you need sub-second performance later, Redshift can complement your lake.

Can you fix our existing pipelines?

Yes. We audit existing ETL jobs, find bottlenecks, and either refactor them or rebuild on Glue with proper error handling and monitoring.

What if our data is scattered across many systems?

That's the normal starting point. We build pipelines that consolidate data from databases, APIs, S3, and third-party tools into one structured data lake.

AWS Data Engineering

Data lakes, ETL pipelines, and analytics infrastructure on AWS. We build the data foundation that turns raw information into assets your business can use for reporting, decisions, and AI.

Talk to a Data Engineering Specialist

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Your Data Is Growing Faster Than Your Ability to Use It

Data is everywhere but usable nowhere

You have data in databases, S3 buckets, APIs, and third-party tools, but no central place to query and analyze it

ETL jobs are fragile and slow

Your data pipelines break, run late, or produce inconsistent results. Nobody wants to touch them

Reporting depends on engineers

Business teams can't get numbers without asking a developer to write a query

No clear data permissions

Sensitive data exposed where it shouldn't be, no audit trail for who accessed what

You want AI features but your data isn't ready

Tools like AWS Bedrock Knowledge Base need structured, clean data. Yours is scattered and poorly organized

What We Deliver

A Structured Data Lake on S3

A central repository with clear zones for raw, processed, and ready-to-use data. Lake Formation handles permissions and governance so the right people access the right data.
Reliable ETL pipelines

Serverless data pipelines on AWS Glue that extract from your sources, transform and validate your data, and load it where it needs to go. Scheduled or event-driven. They run without babysitting.
Self-service analytics

Amazon Athena for SQL queries directly on your data lake. Amazon QuickSight for dashboards and reports that business teams can use without engineering help.
Your data as an AI knowledge base

We structure your data lake to work with AWS Bedrock Knowledge Base so your AI agents and assistants reference real business data — not generic content.

AWS Services We Use

Amazon S3

Data lake storage

AWS Glue

Serverless ETL

AWS Lake Formation

Governance and permissions

Amazon Athena

SQL queries on S3

Amazon QuickSight

Dashboards and BI

AWS Bedrock Knowledge Base

AI knowledge source

Who This Is For

SaaS companies with growing data

Your product generates data but there is no pipeline to aggregate and analyze it

Teams with broken ETL jobs

Existing pipelines are unreliable and nobody wants to maintain them

Companies preparing for AI

You want to use AWS Bedrock but your data isn't clean or structured enough

Startups building data-driven products

You need a data foundation that supports reporting and AI from the start

Featured Case

Building an AI Grant Management Platform on AWS Bedrock

85%

Reduction in form creation time

3×

Faster grant application completion

months full platform delivery

AI EngineeringAWS BedrockGovTech

Building an AI Grant Management Platform on AWS Bedrock

Perfsys built four AI services for EPIRA.ai on AWS Bedrock, automating grant form creation (80–90% faster) and pre-application eligibility scoring. Delivered in 3 months by 2 engineers with a fully serverless, scalable architecture.

Apr 27, 2026