Prodhee Technologies partners with global enterprises and digital-native companies to design, migrate, and scale cloud environments that are resilient, secure, and AI-ready. Whether lifting legacy workloads, optimizing multi-cloud footprints, or infusing AI/MLOps practices, we deliver operational excellence without business disruption.
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Cloud Services
Our portfolio spans migration, operations, and AI-ready architectures—all hardened for scale, security, and compliance.
Cloud Migration & Modernization
Liberate workloads. Modernize legacy. Scale infinitely.
- What we do: Assessment workshops, cloud landing zones, migration runbooks, refactoring monoliths into microservices, cost/performance tuning.
- Use cases: Data-center exit, app containerization, hybrid-cloud consolidation, performance-hungry workloads.
- Deliverables: Cloud strategy brief, migration factory plan, architecture blueprints, cost governance model, runbooks.
- KPI Impact: Infra cost ↓ 25–40%, release velocity ↑ 2–3x, downtime risk ↓ drastically.
AI/MLOps (Machine Learning Operations)
Operationalize intelligence—safely, repeatably, and at scale.
- What we do: Data/feature stores, CI/CD pipelines for models, automated retraining triggers, drift detection, experiment tracking.
- Use cases: Continuous AI deployment, high-stakes ML in BFSI/Healthcare, recommendation engines, predictive analytics.
- Deliverables: ML pipeline diagrams, experiment registry, monitoring dashboards, rollback playbooks.
- KPI Impact: Model release cycles ↓ 60%, escaped defects ↓, cost per inference ↓ 30%.
Serverless Computing
Elastic scale. Zero ops. Pay only for execution.
- What we do: Event-driven workloads, API gateways, micro-batching, GPU-backed serverless for AI, cold-start optimization.
- Use cases: Event stream processing, IoT ingestion, backend APIs, AI inference pipelines.
- Deliverables: Serverless blueprints, cost models, performance tuning playbooks, IaC templates.
- KPI Impact: OpEx ↓ 40–70%, latency compliance ↑, DevOps overhead nearly eliminated.
Data Warehouse & Data Lake Solutions
Unify, govern, and query at petabyte scale.
- What we do: Lakehouse architectures, data ingestion pipelines, schema harmonization, real-time analytics, governance frameworks.
- Use cases: Enterprise analytics, customer 360, IoT data unification, regulatory reporting.
- Deliverables: Data ingestion pipelines, governance catalog, query performance dashboards, consumption layers.
- KPI Impact: Query latency ↓ 50–80%, analytics coverage ↑, compliance breaches ↓.
Cloud Security & Compliance
Guardrails, governance, and guaranteed peace of mind.
- What we do: Zero-trust architecture, IAM hardening, SOC2/HIPAA/GDPR compliance, KMS/HSM integration, penetration tests, anomaly detection.
- Use cases: BFSI/Healthcare-grade compliance, regulated workloads, sensitive PII/PHI, cross-border data residency.
- Deliverables: Security playbooks, IAM policies, compliance audit reports, automated guardrails, threat dashboards.
- KPI Impact: Audit readiness ↑, breach probability ↓, regulatory costs ↓.
Delivery Approach
We operationalize clarity through structured, testable execution.
Discovery & Readiness
Infra audit, risk registry, ROI model, migration vs. modernization decision.
Experimentation & Prototyping
PoCs with multi-cloud tools, bake-off benchmarks.
Pilot / MVP
Thin-slice workloads, instrumented for latency/cost/compliance.
Hardening & MLOps
IaC, CI/CD pipelines, failover strategies, disaster recovery, observability.
Security, Privacy & Governance
PII scrubbing, governance templates, audit logs.
Scale & Continuous Improvement
Cost tuning, auto-scaling policies, AI-driven workload placement.
Platforms & Tooling
Platforms & Tooling
We remain vendor-neutral, choosing the right weapon for each workload.
- Cloud Providers: AWS, Azure, GCP, Oracle, Alibaba.
- Data Warehousing: Snowflake, BigQuery, Redshift, Databricks Lakehouse.
- Serverless & Containers: AWS Lambda, Azure Functions, GCP Cloud Run, Kubernetes, OpenShift.
- MLOps: MLflow, Kubeflow, Airflow, Weights & Biases, SageMaker.
- Security & Compliance: HashiCorp Vault, Prisma Cloud, Checkov, Open Policy Agent.
- Observability: Prometheus, Grafana, Splunk, Datadog.
Security & Compliance
- Data: Mask, encrypt, regional residency, immutable audit logs.
- Access: SSO/SAML/OIDC, least privilege, role-based approvals.
- Safety: DDoS protection, anomaly detection, threat intelligence feeds.
- Compliance: SOC 2, ISO 27001, HIPAA, GDPR, PCI DSS.
- Observability: Security dashboards, cost/latency tracking, compliance alerts.
The Team You Get
Roles: Cloud Architect, Infra Engineer, Data Engineer, Security Engineer, MLOps Engineer, DevOps, Delivery Manager, QA/SDET, Compliance Officer.
Working Model: Agile pods, sprint demos, cost telemetry, risk logs, built-in redundancy.
Visuals: Org diagram, sprint animation timeline.
Case Studies
Lifted 700+ workloads from data centers to hybrid-cloud. Outcomes: Infra cost ↓ 32%, release velocity ↑ 2.7x, downtime risk near-zero.
Built model pipelines with PHI masking. Outcomes: 65% faster deployments, 98% compliance adherence.
Event-driven APIs scaling to 200k concurrent users. Outcomes: Ops cost ↓ 70%, latency compliance ↑ to 99.95%.
FAQ
Can you handle multi-cloud + hybrid setups?
Yes—AWS, Azure, GCP, on-prem, VMware—optimized for workload placement.
How do you ensure compliance?
Pre-built controls, audit logs, and certification-ready templates.
How do you optimize costs?
Rightsizing, auto-scaling, FinOps dashboards, reserved instances, spot optimization.
Can we run entirely in our VPC?
Yes—air-gapped, no egress, customer-managed keys.
How fast is value realized?
Most orgs see tangible ROI within 4–8 weeks post migration pilot.