AWS re:Invent 2025 - Unlocking GenAI potential with automated modernization to AWS (ANT313)

Published: 1 hour ago (December 5, 2025 at 09:51 PM EST)

3 min read

Source: Dev.to

Introduction

Good afternoon everyone, and welcome to the session. I’m Sachneet Singh Bains, leading the solutions architecture team at Impetus Technologies. In this talk I’ll explain how we help enterprises unlock GenAI potential by automating the modernization of legacy data systems to AWS.

About Impetus Technologies

Over 3,600 engineering staff worldwide.
More than 30 Fortune 100 customers.
Premier tier AWS Services and Solution Partner; number 1 in the ETL migration space.
Operates an AWS Center of Excellence and offers 10+ services and solutions on AWS Marketplace.
G2E certified.

Intelligent Enterprise Portfolio

Impetus delivers a full‑stack portfolio that spans data, cloud, and GenAI:

Strategy & Design – Data, cloud, and AI strategy definition for customers.
Accelerators –
- Data Platform Accelerator: jump‑starts data platform creation.
- Pres: unified observability across multi‑cloud environments.
Workload Modernization – Migration of EDW, ETL, BI, and Hadoop workloads to AWS services (Glue, Redshift, etc.).
DevOps & MLOps – End‑to‑end CI/CD pipelines, AI model lifecycle management.
GenAI Labs – Rapid prototyping of agentic AI solutions, AI governance, and custom AI frameworks.

GenAI‑Powered BI Services

Legacy BI environments often contain thousands of reports. With GenAI‑enabled BI we can:

Automatically generate or refactor ad‑hoc reports without manual redesign.
Preserve existing business logic while modernizing the underlying platform.

This enables enterprises to make data‑driven decisions faster and at scale.

Modernizing the Data Ecosystem for the GenAI Era

A recent survey shows that 90 % of leaders prioritizing GenAI first focus on modernizing legacy data systems (EDW, ETL, BI) to unlock the value of accumulated business logic. Impetus addresses the common impediments to modernization with its LeapLogic solution accelerator, which automates the migration process.

Strategic Considerations

Reuse vs. Rebuild – Determine which legacy assets can be transformed and which require a rewrite.
Effort Estimation – Assess whether the project will take 6 months, 1 year, or longer.

Our approach typically follows an 80/20 rule:

80 % of the workload is transformed using pattern‑based automation.
20 % (technical debt) may need custom re‑engineering.

Modernization Methodology

Impetus employs a four‑step methodology to migrate legacy data ecosystems to AWS.

1. Assess

Score & Volume Metrics – Quantify data size and workload intensity.
Business Logic Complexity – Evaluate the intricacy of transformations, calculations, and rules.
Technical Debt Identification – Detect outdated code, schema issues, and performance bottlenecks.
Lineage & Dependency Mapping – Build end‑to‑end maps from orchestration tools through ETL pipelines to the data warehouse and BI layers.

The assessment delivers a tailored modernization strategy, timeline, target architecture, and recommendation set.

2. Transform

Automated Code Conversion – LeapLogic auto‑transforms 90‑95 % of legacy code (Informatica, DataStage, Teradata, Oracle, etc.) into native AWS services such as Glue, Redshift, and Athena.
Pattern‑Based Migration – Leverages reusable transformation patterns to ensure consistency and speed.

3. Validate

(Content not provided in the source excerpt – typically includes cell‑by‑cell validation, data quality checks, and functional testing to confirm parity between source and target.)

4. Operationalize

(Content not provided in the source excerpt – generally covers CI/CD pipelines, monitoring, governance, and ongoing optimization.)

Differentiators

Pattern‑Based Transformation – Reusable, proven migration patterns reduce manual effort.
End‑to‑End Lineage Mapping – Full visibility of data flow and dependencies across the ecosystem.
Cell‑by‑Cell Validation – Guarantees data fidelity post‑migration.

Customer Success Highlights

United Airlines – Achieved 70 % effort savings migrating from Teradata to Redshift.
Bank United – Reduced reporting migration time by 50 %.

PRISM – AI‑Enabled Unified Observability

PRISM is Impetus’s AI‑driven observability platform that provides:

Multi‑cloud cost optimization.
Governance and compliance monitoring.
Automated anomaly detection and remediation recommendations.

This article is auto‑generated from the original presentation content. Typos or minor inaccuracies may be present.