
Case Study: Strengthening Crypto Platform Security
A fast-growing blockchain platform faced a critical challenge managing secrets securely across their trading, backend, and infrastructure services.
We build the infrastructure, security and features your AI products need, without the hassle of complex implementations
OpsFlow Labs combines years of DevOps and cloud security experience with hands-on AI engineering. We help teams take LLM features from prototype to production with the pipelines, guardrails and cost controls they need.
From the infrastructure your AI runs on to the features your users see, we help you ship AI that holds up in production.
We build the pipelines, cloud setup and access controls your AI features run on, so your team can ship safely and keep model costs in check.
Experienced platform, DevOps and AI engineers who join your team on contract, full-time or contract-to-hire.
We design and build production-ready AI features, from LLM integrations and agents to workflow automation, with security and cost control built in.
Explore the feedback and success stories from those who know us best
— OpsFlow Labs provided us with a thorough Security Audit of our Amazon Web Services systems. It was a pleasure interacting with him as a daunting process was made simple; granting efficiency and savings, allowing us to take the right steps to smoothen our operations. Glad to work with OpsFlow Labs and look forward to our next engagement.
— I have much respect for OpsFlow Lab's insight and hard work at TELUS, where their focus on building tools and culture to support CD/CD and DevOps practices made my work easier, more pleasant, and had a direct impact on the quality and speed with which we were able to ship code.
— OpsFlowLabs brought forth significant improvements to our Reference Architecture, developed application Starter Kits, set up bleeding-edge Infrastructure as Code with Terraform, revolutionized Secrets management with Vault, expedited application delivery with OpenShift, created innumerable build pipelines in Jenkins and Circle CI, flaunted impressive dashboards made with BigQuery and DataStudio, and much more.

A fast-growing blockchain platform faced a critical challenge managing secrets securely across their trading, backend, and infrastructure services.

A large telecommunications organization faced serious bottlenecks in their software delivery process with siloed teams, manual deployments, and limited visibility.

A fast-growing audio streaming company relied on a legacy platform that had become difficult to understand, hard to update, and increasingly fragile.