Modernize. Migrate. Maximize Value

Modernization & Migration Factory

Modernize. Migrate. Maximize Value.

‍Legacy platforms often hold back your business from scaling, innovating, and integrating AI. Aptus Data Labs' Modernization & Migration Factory offers a structured, outcome-focused approach to revamp legacy systems and migrate them to next-gen, cloud-native platforms, enabling agility, resilience, and AI-readiness.

Modernizing the Data Platform

A robust data platform is the backbone of any AI-powered enterprise.
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Our Key Capabilities:
  • Legacy Database or Data Warehouse or Cloud Database  to Cloud Lakehouse Migration
    Migrate from on-premise systems like Oracle, Teradata, Netezza, SQL Server to Cloud Platforms like Snowflake, Databricks, or BigQuery.
  • Real-time Streaming & Event-Driven Architecture
    Introduce Kafka, Kinesis, and Apache Flink pipelines for high-velocity, real-time data processing.
  • Modern Data Stack Implementation
    Leverage tools like dbt, Airbyte, Fivetran, and Delta Lake for modular, scalable data engineering.
  • Data Mesh & Domain Ownership Models
    Shift to decentralized, business-domain-led data ownership for agility and alignment.
  • DataOps & Observability
    Establish end-to-end automation, lineage, monitoring, and CI/CD across data pipelines.

Modernizing the Analytics Platform

We empower business users, analysts, and data scientists with the latest self-service, real-time, and embedded analytics capabilities.
Key Capabilities:
  • BI Tools Modernization
    Migrate from legacy dashboards (e.g., Cognos, BO, SSRS) to Power BI, Tableau, or Looker.
  • Embedded & Conversational Analytics
    Enable AI chatbots to fetch data and insights via natural language queries.
  • Data Virtualization & Smart Caching
    Platforms such as Presto, Dremio, or Starburst are used to reduce data movement and optimize performance.
  • ML-Integrated Insights
    Machine Learning tech is infused into dashboards for predictive, anomaly detection, and simulation use cases.
  • Analytics Governance & Metrics Layer
    Reusable semantic layers are implemented for consistent KPIs across tools and teams.

Modernizing the AI Platform

A modern AI platform enables scalable experimentation, deployment, and monitoring of both predictive models and generative agents.
Key Capabilities:
  • Cloud-Native AI Workbenches
    SageMaker, Vertex AI, Azure ML are leveraged for scalable training and model management.
  • MLOps & LLMOps Pipelines
    We undertake automated model training, validation, drift monitoring with feedback loops.
  • Model Registry & Feature Stores
    Version control, reuse, and deployment of ML components are centralised.
  • Responsible AI Governance
    Enable fairness, explainability, security, and regulatory compliance across AI workflows.
  • AutoML & AI Copilots
    Democratize AI with low-code/no-code interfaces and prompt-based modeling assistants.

aptAIHub – The AI Hub for GenAI & Agentic Use Cases & Workloads

aptAIHub is our enterprise AI playground to ideate, build, test, and deploy Generative + Agentic AI use cases on defined AI infrastructure and AI governance
Key Features:

Multi-LLM Orchestration

Integrate OpenAI, Anthropic, Mistral, LLaMA, and custom-tuned models in a unified workspace.

RAG, PromptOps & LangChain Integration

Build production-ready GenAI apps using modular building blocks.

Agent Studio

Design AI agents with memory, tools, and goal-based workflows—deployed as APIs, bots, or UI widgets.

Security-First GenAI

Enable PII redaction, audit logs, and trust scoring to safely deploy GenAI in enterprise environments.

Real-time Monitoring & Analytics

Observe prompts, outputs, hallucination rates, and agent performance via interactive dashboards.

Why Aptus Data Labs for AI-Powered Modernization?

01
Factory Accelerators for faster, low-risk migration and modernization.
02
AI-Embedded Everything – from data prep to decision-making.
03
Automation-Driven Execution – eliminate manual steps, reduce TCO.
04
We are Vendor-Neutral & Cloud-Agnostic – we use Azure, AWS, GCP, Snowflake, Databricks, and more.
05
End-to-End Lifecycle Ownership – from current state assessment to post-deployment optimization.
Case Studies

Featured Success Stories

To build a scalable, secure, and analytics-ready Big Data platform to support advanced business intelligence, customer analytics, AML, segmentation, and other use cases—while optimizing existing infrastructure and unlocking the full value of enterprise data.
Big Data & Analytics Platform Implementation for Enhanced Business Performance in Banking

100% to 300% Improvement in Query Performance

Migration of 700+ TB Across 12,000+ Tables

USD 15+ Million ROI from Phase 1 Implementation

99.6% SLA Achieved with 24x7 Platform Support

To minimize scrap (initially at 21%) and enhance ADY% (production efficiency initially at 79%) using a consolidated BI & analytics platform with integrated ML models, real-time reporting, and on-demand data availability.
BI & Analytics Platform to Improve ADY% and Reduce Scrap in Telecom Manufacturing

200% Improvement in Model Execution Performance

Enhanced ADY% and Scrap Reduction

Integrated Reporting with Real-Time Dashboards

Always-On Platform Support

To build an ML-driven predictive pricing engine that could accurately forecast monthly supply, demand, and pricing for different food product categories, improve decision-making, and reduce time and cost spent on manual estimations.
ML-Based Price Prediction Engine for Optimizing Supply, Demand, and Pricing

Automated Optimal Price Estimation

Improved Forecasting Efficiency

CI/CD Enabled Retraining Pipeline

Cost and Time Savings Through Automation

To enhance regulatory adherence, document clarity, and operational efficiency by implementing an AI-based web platform for SOP evaluation and rewriting—addressing variability, complex language, and manual review bottlenecks in Biocon’s document processes.
AI-Powered SOP Rewriting Interface for Regulatory Compliance and Document Quality

Streamlined SOP Rewriting and Review Workflow

Improved SOP Quality and Readability

Audit-Ready Change Traceability

Foundation for AI-Enabled Regulatory Compliance at Scale

To automate and digitize the process of updating medicine preparation templates by replacing placeholder text with meaningful chemical and process information—eliminating manual effort, reducing human error, and speeding up processing across large volumes of documents.
Automated Placeholder Document Creation for Digitization of Pharma Templates

95% Reduction in Manual Effort

90–95% Accuracy in Placeholder Text Replacement

Drastic Time Reduction

Significant Cost Savings

See More Success Stories

Our integrated offering

Advanced Analytics & AI
Production Deployment & Support Enablement
Modernization & Migration Factory

Ready to modernize with AI and automation at the core? Let’s reimagine your future—one platform at a time.

Connect with our modernization architects for a free consultation or demo.
Talk to Our Modernization Experts

Reach out to our Consultants,
Data and AI Practioners

Upload your RFP/RFI/EoI
HQ - Novel Tech Park, #46/4, GB Palya, Near Kudlu Gate, Hosur Main Road, Bengaluru, India, Pin – 560068
info@aptusdatalabs.com
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