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:

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.

Case Studies

Featured Success Stories

Performance Analysis & Tool Selection: MapR DB vs. Mongo DB for Secure Data Mart Design

200% Improvement in Query Performance

Optimized Data Ingestion and ETL Design

Improved SLA for Bulk Requests

Efficient Tool Selection and Architecture Design

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

A Banking Big Data & Analytics Platform with 24x7 Support

100–300% improvement in query performance

USD 15M+ ROI in Phase 1 of implementation

10+ AI/ML use cases delivered across key functions

99.6% SLA achieved with 24x7 infrastructure support

Enterprise Data Lake and Analytics implementation for a large Pharmaceutical Company in India on AWS platform

30–40% Reduction in IT Costs

Accelerated Analytics with 3X Faster Reporting

AI/ML-Ready Infrastructure

Manual Work Reduction

Data, Process , Batch jobs and Work flow migration to Hadoop Platform

40% Reduction in IT Infrastructure Costs

60% Improvement in Data Processing Speeds

4X Scalability Boost

70% Reduction in Downtime

See More Success Stories

Modernization & Migration Factory

Modernizing the Data Platform

Modernizing the Analytics Platform

Modernizing the AI Platform