Google Cloud Services

Google Cloud Data & AI

AQBEE leverages Google Cloud's industry-leading data and AI capabilities to build intelligent platforms that transform Salesforce data into actionable insights. From BigQuery analytics and Vertex AI models to Dataflow pipelines and Looker dashboards, we create end-to-end data solutions that enhance CRM intelligence and drive business outcomes.

Capabilities

What We Deliver

Vertex AI & AutoML

Train and deploy custom ML models on Vertex AI — from AutoML for quick wins to custom TensorFlow/PyTorch models for complex predictions integrated back into Salesforce.

BigQuery ML

Build and deploy machine learning models directly in BigQuery using SQL, making predictive analytics accessible to data analysts working with Salesforce data.

Dataflow Pipelines

Design real-time and batch data processing pipelines with Apache Beam on Dataflow for Salesforce data transformation and enrichment at scale.

Document AI & Vision AI

Extract structured data from documents and images using Google Document AI and Vision AI, feeding results into Salesforce for automated processing.

Natural Language AI

Implement sentiment analysis, entity extraction, and text classification on customer communications to enrich Salesforce records with AI-derived insights.

Real-World Applications

How We Apply It

Predictive Customer Health Scoring

A SaaS company trains a churn prediction model on Vertex AI using Salesforce usage data, support tickets, and billing patterns — surfacing risk scores directly in Service Cloud for CSM action.

Key Highlight

Vertex AI custom model with automated retraining pipeline, predictions served via Cloud Functions into Salesforce custom fields.

Intelligent Document Processing

A real estate firm uses Document AI to extract key terms from lease agreements and property documents, automatically populating Salesforce records and triggering compliance workflows.

Key Highlight

Google Document AI with custom processors trained on domain-specific document layouts for 95%+ extraction accuracy.

Customer Sentiment Dashboard

A hospitality brand analyses guest reviews and support transcripts using Natural Language AI, scoring sentiment and extracting themes that feed into Salesforce for service improvement tracking.

Key Highlight

Google Natural Language API processes text at scale, with results aggregated in BigQuery and visualised in Looker dashboards connected to Salesforce metrics.

Case Studies

Google Cloud Data & AI Success Stories

See how we've delivered measurable results with Google Cloud Data & AI.

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

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

Building an AI-Powered Knowledge Base with RAG for Enterprise Support

NovaBridge Software

NovaBridge had accumulated over 50,000 support articles, API docs, and troubleshooting guides across Confluence, Zendesk, and internal wikis. Support agents spent an average of 8 minutes searching for answers per ticket, and customers frequently received inconsistent or outdated guidance. The knowledge was there — finding it was the problem.

Google Cloud Vertex AIGemini ProClaudeCloud Run

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