Modernization & Cloud Migration Services | AI-Ready Platforms

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: