Devotica designs and operates cloud-native platforms — data, DevOps, GenAI and managed infrastructure that scale automatically, heal themselves, and stay out of your team's way. AWS-first as an Advanced Tier Services Partner — and multi-cloud when the workload calls for it.
Tooling we live in, day in, day out
From zero-downtime VMware migrations to Kubernetes orchestration at global scale — one engineering team, end-to-end.
Refactor legacy stacks into cloud-native architectures — VMware and on-prem to containers or serverless. AWS-first, with multi-cloud reach when you need it.
Aurora, RDS, Postgres, DynamoDB and more. Online migrations, read replicas, and automated failover across multi-AZ topologies.
Lakehouses and pipelines on Glue, Redshift, Databricks or Snowflake. From ingestion to BI — versioned, observable, and built for ML workloads.
RAG apps, agents and LLMOps grounded in your own data — built on Amazon Bedrock and model-agnostic underneath, so you're never locked in. Built to reach production.
Terraform, OpenTofu and CDK modules tailored to your compliance posture. CI/CD on GitHub Actions, GitLab or CodePipeline, with reproducible environments.
Proactive chaos testing, SLO instrumentation, and 24/7 incident response — so failure is a feature, not a Friday-night surprise. Uptime you can put in a contract.
We start with your goals, constraints and current stack — an architecture review and risk assessment that maps where you are against where you need to be.
We design the target architecture and a pragmatic, phased roadmap — AWS-first, cost-aware and mapped to your compliance posture. No surprises at build time.
We implement with automation and IaC, migrate with zero-downtime cutovers, and stay on for the reliability, observability and cost control that keep you live.
AI is now a pillar, not a side project. We build RAG apps, tool-using agents and the LLMOps to run them safely — on Amazon Bedrock and model-agnostic underneath, so you're never locked to one model.
Real engagements on AWS — the problem, the architecture, and the numbers it moved. See all case studies →
A Redshift billing data mart with automated EMR/MWAA pipelines replaced manual monthly invoicing across 300+ lenders.
Re-architected ~900 Redshift queries to a hybrid lakehouse on EMR and Iceberg — zero downtime at cutover.
Unified Postgres, MongoDB and third-party data into a GDPR-compliant lake with embedded QuickSight dashboards.
Replaced an overloaded database with a pay-per-use streaming pipeline ingesting 3.3 billion records a month.
Engineered outcomes, measured