Cloud, DevOps and AI operations for systems already in production
LLMOps, evaluation, cloud infrastructure, CI/CD and cost control that keep AI agents and products reliable and keep bills under control.
What we do in Cloud, DevOps & AI Ops
AI and cloud systems that stay reliable, observable and affordable.
Deploy, monitor, and improve AI models in production with automated pipelines.
Measure accuracy, cost, and latency of your AI systems and catch issues early.
Move applications and data to AWS, Azure, or Google Cloud with minimal disruption.
Design secure, scalable cloud infrastructure built for growth and AI workloads.
Automate builds, tests, and releases so your team ships faster with fewer bugs.
Containerize and manage infrastructure with Kubernetes, Terraform, and repeatable deployments.
Monitoring, incident response and reliability engineering with coverage matched to your SLOs, not a blanket 24/7 claim.
Cut cloud and LLM spend without losing performance through usage and architecture tuning.
Protect critical systems and data with tested backup and recovery plans.
Shipped work and accelerators
AI call screening on web + mobile
An AI phone assistant that screens calls and messages across web and mobile
Agent ops from prototype to production
An operations console to register, run, monitor and govern fleets of AI agents
AI Booking Agent
An appointment-booking agent that answers, qualifies and books into your calendar over phone or chat.
ChatAI
Our internal builder for knowledge assistants and chatbots trained on your documents and tools.
Decode
A client RAG knowledge assistant with mobile app, retrieval over their content, deployed on AWS Fargate.
Phases, timelines and what you receive
Assess
Current-state review of systems, costs and risks
Instrument
Tracing, evaluation, monitoring and cost dashboards
Harden
Pipelines, guardrails, alerts and runbooks
Operate
Monitoring, incident response and reports
FAQ for Cloud, DevOps & AI Ops
Questions specific to cloud, devops & ai ops.
The practices and tools for running LLM apps in production: monitoring, evaluation, cost control, versioning and incident response.
Yes. We instrument common agent frameworks and export to your observability tools.
Gartner expects over 40% of agentic AI projects to be cancelled by 2027 due to cost, unclear value or weak risk controls. Observability is how you avoid becoming one of them.
With labelled test sets, rule checks and model-graded evaluations, reviewed against human judgement.
We plan cut-overs for low-traffic windows and keep a tested rollback for each step.
Usually the one your team and customers already use. We design for your compliance and cost needs.
Ready to talk about what to build?
Book a short call with a senior engineer. No pitch deck, just a clear next step.
- We reply within 1 business day.
- NDA available on request
- You own all code from day one