Technologies
Our Technology Ecosystem
We design, build, and operate production-grade data, AI, and application platforms on Microsoft Azure. Our solutions cover governed data lakes, Synapse/Fabric analytics, end-to-end MLOps, GenAI/RAG workloads, real-time streaming, microservices on AKS/Container Apps, and fully managed operational databases. With security, governance, observability, and FinOps built in from day one, we deliver faster time-to-value, lower run-costs, and reliable production SLAs across your entire Azure ecosystem.
Technologies — Built on Microsoft Azure
We design, build, and operate production-grade data and AI workloads on Azure with security, MLOps, and FinOps integrated from day one. Our blueprints accelerate time-to-value, optimize costs, and ensure reliability for mission-critical systems.
Amazon Web Services (AWS)
AI/ML services (SageMaker, Bedrock), advanced analytics (Redshift), secure cloud infrastructure.
Google Cloud
Vertex AI, BigQuery, AI APIs (Vision, NLP, Translation), zero-trust security with BeyondCorp.
Microsoft Azure
AI-powered insights (OpenAI Service, Cognitive Services), Synapse Analytics, enterprise cloud security.
IBM
Watson AI, hybrid cloud solutions, enterprise data integration, cybersecurity tools.
Oracle Cloud
Autonomous database, AI-enhanced ERP, enterprise-grade data protection.
Azure AI & Azure OpenAI
What you get
- Azure ML pipelines with feature store integration, model registry, and CI/CD automation
- Online & batch inference via Managed Endpoints or AKS, including monitoring, drift detection, and rollback strategies
- RAG (Retrieval-Augmented Generation) implementations using Azure OpenAI, Azure AI Search, and vector databases
- Responsible AI workflows: evaluation metrics, safety checks, grounding strategies, and human-in-the-loop review
Business outcomes
- Transition from experimental notebooks to production-grade ML and GenAI
- Quantifiable model performance with risk and compliance controls
- Reduced maintenance through standardized MLOps practices
Azure Data Platform
What you get
- Governed analytics lake on ADLS Gen2 with Microsoft Purview for policies, tags, and lineage
- Automated pipelines using Azure Data Factory, Synapse, or Fabric Data Engineering
- Power BI semantic models and dashboards for actionable insights
- Cost visibility & controls with budgets, quotas, and usage dashboards
Business outcomes
- Rapid data-to-insight pipeline for faster decisions
- Strong governance & compliance posture
- Predictable query and storage spend with FinOps guardrail
Streaming & Integration
What you get
- Low-latency ingestion using Azure Event Hubs, IoT Hub, and Stream Analytics for real-time telemetry
- Change Data Capture (CDC) from operational systems (SQL, SAP, mainframe) into Synapse or Microsoft Fabric
- Resiliency patterns baked in: quality checks, retries, idempotency, DLQ handling, and replay workflows
- Schema evolution & contract testing for forward-compatible data pipelines
Business outcomes
- Real-time data availability for personalization and operational decisions
- Self-healing pipelines that minimize manual intervention and reduce on-call fatigue
- Reduced data loss with deterministic recovery and observability
App Modernization
What you get
- Microservices architecture deployed on Azure Kubernetes Service (AKS) or Azure Container Apps, with namespace isolation, autoscaling, and resource quotas
- API governance via Azure API Management, including policies for throttling, authentication, and versioning
- CI/CD pipelines using GitHub Actions or Azure DevOps, supporting blue-green, canary, and progressive delivery strategies with automated rollback
- Service reliability engineering (SRE) practices: defined SLOs, error budgets, runbooks, and automated incident workflows
Business outcomes
- Accelerated release cycles with lower change-failure rates through automated deployments
- Standardized platform patterns for consistent governance and compliance across teams
- Reduced operational overhead by leveraging serverless and managed services where applicable
Security & Governance
What you get
- Identity & Access Control: Entra ID-based RBAC, least-privilege enforcement, Privileged Identity Management (PIM), and Conditional Access
- Policy & Compliance Automation: Azure Policy, Defender for Cloud, and Security Center dashboards for continuous posture management
- Secrets & Encryption: Azure Key Vault, Customer-Managed Encryption Keys (CMEK), automated secret rotation, and HSM-backed key storage
- Audit & Governance as Code: Full audit logging, retention policies, and policy-as-code for repeatable compliance in CI/CD pipelines
Business outcomes
- Risk reduction through enforced guardrails and zero-trust principles
- Streamlined audits with automated evidence collection and compliance dashboards
- Scalable security architecture that grows with your Azure estate
Observability & FinOps
What you get
End-to-End Monitoring
- Azure Monitor, Log Analytics, Application Insights, and proactive alerting
Operational Resilience
- Defined SLOs, automated incident playbooks, disaster recovery (DR) drills, and structured post-incident reviews
Cost Governance
- Real-time cost dashboards, budget thresholds with alerts, and monthly optimization actions
Business outcomes
Reliability
- Achieve 99.9%+ production SLOs with <1-hour MTTR for P1 incidents
Cost Efficiency
- Reduce operational spend without impacting performance or availability
Accountability
- Clear ownership and measurable operational KPIs across teams
Accelerators & Blueprints
Azure Landing Zone IaC
- Infrastructure-as-Code templates using Bicep and Terraform
- Automated deployment of policies, network topology, logging, and security baselines
Data Platform Guardrails
- Purview-based governance for data classification and lineage
- Pre-configured access policies and cost monitoring dashboards
Azure ML MLOps
- Pipeline templates for CI/CD of ML models
- Feature store patterns for reusable data features
Streaming Starter Kit
- Pre-built Event Hubs + Stream Analytics templates
- Dead Letter Queue (DLQ) handling and message replay support
- Optimized for real-time ingestion and processing
Cost Efficiency
- Retrieval orchestration for hybrid search
- Evaluation harness for performance and accuracy
- Safety guardrails for responsible AI deployment
Power BI Semantic Layer
- Modeled metrics for consistent reporting
- Governance framework for secure data access
- KPI dashboards for actionable insights
Data Engineering & Analytics
We deliver powerful data solutions that drive insights and innovation at scale.
Databricks
Unified Lakehouse architecture, scalable AI/ML model development, real-time analytics.
Snowflake
Multi-cloud data warehousing, secure data sharing, AI/ML integration.
Tableau (Salesforce)
Data visualization with AI-driven insights via Tableau GPT.
Qlik
End-to-end analytics and AI-powered business intelligence.
Informatica
Data governance, integration, and cloud data management.
AI Tools & Automation
We integrate AI and automation into business processes for measurable efficiency gains.
OpenAI
Generative AI models (GPT), language intelligence, custom AI solutions.
Hugging Face
Pre-trained AI models for NLP, vision, and more.
UiPath
Robotic Process Automation (RPA) with AI decision-making.
Automation Anywhere
Intelligent automation blending RPA, AI, and analytics.
Salesforce Agentforce
AI-powered CRM automation, conversational agents, predictive insights.
Technology Solutions
Enterprise-Grade Azure Technology Solutions
Azure Data Platform
Data Lake, Analytics & Warehousing
- Governed Data Lake on ADLS Gen2 with Microsoft Purview for cataloging and lineage
- Synapse Analytics and Microsoft Fabric Lakehouse for enterprise analytics and warehousing
- Data transformation & modeling via Azure Data Factory, Synapse Pipelines, or Fabric Data Engineering
- Power BI semantic models and dashboards for business-ready insights
- Cost visibility & optimization using Azure Cost Management
Azure AI & Azure OpenAI
ML & Generative AI Capabilities
- Azure ML pipelines with feature store patterns and model registry integrated into CI/CD
- Online & batch model serving via Managed Endpoints or AKS, with monitoring, drift detection, and rollback strategies
- RAG (Retrieval-Augmented Generation) patterns using Azure OpenAI, Azure AI Search, and vector indexes
- Responsible AI workflows: evaluation, safety reviews, grounding strategies, and human-in-the-loop processes
Streaming & Integration
Real-time & Batch Data Processing
- Near real-time ingestion with Event Hubs, IoT Hub, and Stream Analytics
- Batch & CDC pipelines from SQL, SAP, and other systems using Data Factory and Synapse Pipelines
- Built-in quality checks, retries, idempotency, DLQ, and replay patterns
- Schema evolution, contract testing, and full observability baked in
App Modernization
Microservices & DevOps
- Microservices on AKS and Azure Container Apps with autoscaling
- API governance and developer portals via Azure API Management
- CI/CD with GitHub Actions or Azure DevOps, supporting blue-green/canary deployments
- SLOs, error budgets, and runbooks aligned with SRE best practices
Operational Databases
Transactional & Analytical Data Stores
- Azure SQL Database / Managed Instance for transactional workloads
- Cosmos DB for global scale, low latency, and multi-model needs
- Azure Database for PostgreSQL/MySQL where open-source engines fit best
- Clear backup/DR strategy and performance tuning
Security & Governance
Compliance & Data Protection
- Entra ID (Azure AD) RBAC, PIM, and Conditional Access
- Azure Policy, Blueprints, and Defender for Cloud for continuous compliance
- Key Vault, customer-managed keys (CMEK), and secret management
- Purview for data cataloging, lineage, and data loss prevention
Observability & FinOps
Monitoring & Cost Optimization
- Azure Monitor, Log Analytics, Application Insights for full-stack observability
- SLOs, incident playbooks, DR tests, and post-incident reviews
- Budgets/alerts, Advisor & Cost Management insights, monthly savings actions
- Outcomes: faster time-to-value, lower run-costs, and reliable production SLAs.
Time to Value Packages
| Feature / Deliverable | Essentials | Plus | Enterprise (Custom) |
|---|---|---|---|
| Timeline | 4–6 weeks | 6–10 weeks | Custom |
| Landing Zone | ✔ | ✔ | ✔ |
| Data Platform Setup | ✔ | ✔ | ✔ |
| Production Pipeline | 1 included | 1 included | Multiple |
| ML / GenAI Use Case | — | ✔ | ✔ (Advanced) |
| Power BI Dashboards | — | ✔ | ✔ |
| FinOps Dashboard | — | ✔ | ✔ |
| AKS (Kubernetes) | — | — | ✔ |
| Multi-region DR | — | — | ✔ |
| Feature Store | — | — | ✔ |
| Security Review | Basic | Standard | Advanced |
| 24×7 Support | — | — | Optional |
Expected Outcomes & Proof:
Our delivery model drives consistent, measurable impact across four core pillars—Reliability, Velocity, Quality, and Cost Efficiency. Each pillar is reinforced with clear success metrics and operational proof points that demonstrate real business value. We combine engineering best practices, automated processes, and data-driven monitoring to ensure scalable and predictable outcomes.
Reliability
- 99.9%+ SLO for production APIs and dashboards
- <1 hour MTTR for Priority 1 incidents
Velocity
- Weekly release cadence
- CI/CD pipelines with automated quality and security gates
Quality
- Model evaluation reports
- Drift monitoring with automated alerts
- Rollback playbooks for safe model and pipeline deployments
Cost
- FinOps KPIs: cost per query
- Cost per pipeline run
- Cost per ML/GenAI invocation