Google Cloud & Gemini
TAIYRA-Z delivers enterprise data platforms, generative AI, and AI agent solutions across Google Cloud and AWS, building governed analytics and Gemini-powered applications for business teams.
Cloud Coverage
Google Cloud + AWS
Multi-cloud delivery without locking the platform to a single vendor.
AI Stack
Gemini on Vertex AI
NL2SQL, enterprise RAG, document intelligence, and AI agents.
Delivery
PoC -> Production
From assessment and architecture design to integration and operations.
Core Scenarios
Gemini capabilities are packaged around concrete enterprise workflows, with data permissions, business context, and evaluation built in.
Knowledge & RAG
A Gemini-powered assistant grounded in enterprise documents, policies, and data definitions through retrieval-augmented generation.
Decision AI
Business users ask questions in plain language; Gemini generates and validates SQL against metric definitions, data permissions, and the business glossary.
Reporting
Recurring management reports generated from metric pipelines, change analysis, and Gemini narrative summaries.
Documents & Agents
Multimodal document analysis and AI agents that connect Gemini reasoning to business systems and approval workflows.
Delivery Model
Delivery covers consulting assessment, architecture design, PoC, system integration, production deployment, model evaluation, operations monitoring, and continuous optimization.
Assess & Design
Map business scenarios, data sources, security boundaries, and target Google Cloud architecture.
PoC & Integrate
Validate Gemini workflows on real scenarios, then integrate with enterprise systems and data platforms.
Operate & Optimize
Deploy to production with model evaluation, operations monitoring, and continuous improvement loops.
Technical Architecture
The architecture covers ingestion, lakehouse, analytics, AI development, and application deployment on Google Cloud.
Pub/Sub, Datastream, and Dataflow feed Cloud Storage, BigLake, and Dataplex-governed lakehouse layers.
BigQuery powers governed metrics and OLAP workloads; Looker delivers governed dashboards and embedded analytics.
Vertex AI hosts Gemini, Vector Search, and Agent Builder; applications run on Cloud Run or GKE.
Security & Governance
Enterprise deployments include identity, encryption, data protection, isolation, auditability, and model governance.
Cloud IAM for least-privilege access, with Cloud KMS and Secret Manager for keys and credentials.
Sensitive Data Protection, Cloud Armor, audit logging, and tenant-level data isolation.
Model evaluation, output guardrails, and traceable context keep Gemini workflows accountable.
Representative Scenario
A representative retail-operations engagement pattern assembled from our delivery method — scenario, products, architecture, and outcomes. Named, verifiable customer references are shared during the sales process.
A retail operations team needs weekly management reports and self-service metric questions answered without waiting on analysts — delivered with Gemini on Vertex AI, BigQuery, and Looker.
Datastream and Dataflow ingest POS/ERP data into a governed BigQuery lakehouse; a semantic metric layer feeds Gemini NL2SQL and report generation; the workspace runs on Cloud Run behind Cloud IAM.
Weekly management reporting moves from hours of manual assembly to minutes of automated generation with review; business users self-serve governed metric questions in natural language; evaluation sets and guardrails gate every release.