A short list, on purpose. Each one represents a team that has deployed it, broken it in a lab, and run it in production for someone else — not a logo on a slide.
Where a platform is the right answer we will say so. Where your own build would be cheaper to own over three years, we will say that instead — and we will show the working.
The core of our observability and SecOps work. Search, logging, metrics and traces on one pipeline; ingestion and retention economics; detection engineering; and enterprise search built on the same stack. Delivered for capital markets, manufacturing and government estates, and paired with TurfAI where retrieval feeds an assistant.
Enterprise Linux and platform foundations for regulated estates — subscription discipline, hardening and run patterns where the operating system layer is a compliance artefact rather than an implementation detail.
Container platform delivery and run — cluster design, migration of existing workloads, operator patterns, and the developer experience work that determines whether anyone actually uses the platform after it is built.
Model-based test automation on large enterprise applications, where the test estate is too big to maintain as scripts. Used inside i3QA™ engagements alongside Selenium, CodeCept and Postman depending on what the application actually needs.
Robotic process automation where the process is stable, rule-bound and high-volume — the cases where an agent is the wrong tool. Delivered at national scale across Indian state governments and in production across enterprise back offices since.
Migration paths, workload right-sizing, and the cost engineering that follows — measured against your pre-engagement monthly bill rather than a vendor calculator.
Migration, modernisation and cost engineering across Azure estates — including hybrid patterns where the operating model matters as much as the landing zone.
Migration and workload engineering on Google Cloud, including bring-your-own-cloud TurfAI deployments where the platform has to run inside your perimeter.
Cluster delivery and run for platforms that cannot go down — CPaaS and messaging estates live on Kubernetes, with autoscaling tied to queue depth, graceful drain on scale-down, and migrations sequenced so each step stands on its own.
Dashboards and alerting on production estates — monitoring and compliance evidence wired to the same pipelines that carry application and security telemetry.
Event-driven backbones at volume — ingestion, fan-out and consumer scaling on estates where billions of events a day are normal and backlog depth is the signal that should drive capacity.
Private and hybrid cloud substrates — workload placement, migration and run where the estate is yours to operate, not a hyperscaler console.
IT workflow and ITSM integration — connecting automation, observability and release outcomes to the system operations teams already run in production.
OpenTelemetry-native observability where teams want traces and metrics on a single instrumentation path alongside Elastic-based estates.
The technologies our engineers work in every day — no partnership behind them, listed because it is a fair question to ask before a first conversation.
We are interested in partnerships where the services depth is the point — where your customers need someone to deploy, tune and run the platform rather than to renew the licence.
We have delivery capacity in Bengaluru, with an established practice structure that a platform capability can be built inside rather than bolted onto.
Partnerships and alliances sit under our VP Growth. Start there and we will tell you quickly whether it fits.
Tell us the requirement rather than the shortlist. We will give you a build-versus-buy comparison over three years, including what each option costs to operate.
