Agentic and generative AI sit at the front: real tool-use, multi-agent orchestration, and evaluation you can read rather than a demo you have to trust. Behind them is the infrastructure work that has to hold when they run.
Autonomous agents, tool-use, and multi-agent orchestration, wired into the workflows you actually run. Observable, evaluated, and accountable for what they do. This is the core of what we do.
Migration and re-architecture across AWS, Azure and Google Cloud: hybrid and multi-cloud estates, private cloud, and the bare-metal provisioning automation beneath. Infrastructure as code, networking, security, and the cost and performance work underneath it.
Shared VPC design and address planning, public and internal DNS with zones kept under version control, NAT, VPN and interconnect, load balancing, and the firewall and WAF rules in front of all of it. Usually the first thing a migration turns out to depend on.
Internal developer platforms and golden paths, plus products that simplify the operation and observability of the platform beneath: network, compute and storage. Tooling your engineers reach for because the friction is gone.
Service level objectives with error budgets that gate a release rather than decorate a dashboard, on-call rotation and incident response, and the metrics, logs and traces underneath them. We have built the function from nothing as well as joined one already running.
Model applications, retrieval and content generation, shipped with evaluation you can read rather than a demo you have to trust.
Custom workflow and process automation, wired into where teams already work, so a process stays visible while it runs instead of vanishing into a black box.
Pipelines, analytics and decisioning that turn a stream of signal into something a person can act on.
Two disciplines, kept distinct. MLOps is the operational layer beneath the models and agents: versioned pipelines, a registry, retraining on drift, and evaluation gates in the deploy path. AIOps is AI turned back on the systems themselves: anomaly detection across metrics, logs and traces, correlation that collapses an alert storm into one incident, and root-cause analysis that names the fault rather than the symptom.
APIs, platforms and services built with clean seams, made to hold their edges for years.
Reviews, blueprints and system design: the enduring pattern, drawn once and drawn correctly.