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Google Cloud & Workspace

Data analytics, AI/ML, and cloud-native infrastructure on GCP.

Leverage Google Cloud Platform for advanced analytics with BigQuery, AI/ML with Vertex AI and Gemini, real-time data pipelines, and cloud-native infrastructure. We also build intelligent automation workflows on Google Workspace to streamline team collaboration.

4Capabilities
3Specialized Services
What We Deliver

Our Capabilities

01

BigQuery & Advanced Analytics

Unlock insights from petabytes of data with BigQuery — Google's serverless, highly scalable data warehouse. We design analytics architectures that combine BigQuery with Looker, Data Studio, and custom dashboards for real-time business intelligence.

  • BigQuery data warehouse design and optimization
  • Looker and Looker Studio dashboards and reports
  • BigQuery ML for in-database machine learning
  • Cost optimization with partitioning, clustering, and BI Engine
  • Cross-cloud analytics with BigQuery Omni
Google Cloud
BigQuery & Advanced Analytics
02

Vertex AI & Gemini Integrations

Build and deploy AI/ML models with Vertex AI, and integrate Gemini's multimodal capabilities into your applications. From custom model training to foundation model fine-tuning — we deliver production-ready AI on Google Cloud.

  • Vertex AI for custom model training and deployment
  • Gemini API integration for multimodal AI applications
  • AutoML for no-code model building and evaluation
  • Model monitoring, A/B testing, and continuous retraining
  • Vertex AI Search and Conversation for enterprise RAG
Google Cloud
Vertex AI & Gemini Integrations
03

Real-Time Pipelines

Build real-time and batch data pipelines with Pub/Sub, Dataflow, and Cloud Composer. We architect event-driven data systems that process millions of events per second with exactly-once semantics.

  • Pub/Sub for real-time event streaming and messaging
  • Dataflow (Apache Beam) for stream and batch processing
  • Cloud Composer (Airflow) for workflow orchestration
  • Dataproc for managed Spark and Hadoop workloads
  • Change data capture and real-time sync pipelines
Google Cloud
Real-Time Pipelines
04

Workspace Automation & AI Workflows

Transform Google Workspace into an intelligent productivity platform. We build custom Apps Script automations, Gemini-powered workflows, and integrations that connect Workspace with your CRM and business systems.

  • Google Apps Script automations for Sheets, Docs, and Gmail
  • Gemini for Workspace — AI-assisted writing, analysis, and presentations
  • Custom Google Chat bots and Spaces integrations
  • Workspace ↔ Salesforce ↔ AWS bidirectional sync
  • Admin console automation and security policy management
Google CloudSalesforce
Workspace Automation & AI Workflows
Case Studies

Google Cloud & Workspace Success Stories

See how we've delivered measurable results with google cloud & workspace.

AI-Powered Sales Intelligence with Google Cloud & Salesforce
75% reduction
Meeting Prep Time
Financial Services

AI-Powered Sales Intelligence with Google Cloud & Salesforce

Atlas Capital Group

Atlas, a mid-market investment advisory firm with 300+ relationship managers, had rich but fragmented data across Salesforce, market feeds, custodian platforms, and internal research documents. RMs spent hours manually preparing for client meetings by searching through disconnected systems. The firm had no predictive capabilities for identifying cross-sell opportunities or anticipating client needs, and leadership lacked a unified view of revenue drivers across the business.

Google BigQueryVertex AIGoogle Cloud NLPLooker
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Real-Time Retail Analytics Platform on Google Cloud
340%
Return on Investment
Retail

Real-Time Retail Analytics Platform on Google Cloud

MegaMart Analytics

MegaMart operated 1,200 stores nationwide but lacked a unified analytics platform. Merchandising decisions relied on week-old batch reports, and the data team spent 80% of their time preparing data rather than generating insights. The absence of real-time inventory analytics was leading to both stockouts on high-demand SKUs and overstock write-downs exceeding $18M annually.

BigQueryVertex AILookerPub/Sub
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Banking Infrastructure Modernisation on Google Cloud Platform
60%
Infrastructure Cost Reduction
Financial Services

Banking Infrastructure Modernisation on Google Cloud Platform

FinCore Banking

FinCore's on-premises data centres were nearing end-of-life, with hardware refresh costs estimated at $14M. The legacy infrastructure could not support the bank's digital banking initiatives, and scaling for peak transaction periods required 6-month lead times for hardware procurement. Regulatory requirements for SOC2 and PCI compliance added complexity to any migration strategy.

Google Kubernetes EngineCloud SQLCloud ArmorAnthos
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