AI engineering & automation
Less repetitive work.
More engineering
that matters.
Put AI agents to work on software maintenance, vulnerability remediation and engineering workflows. We build the integrations, execution environments and validation steps that turn individual tools into dependable automation.
Built around your repositories, infrastructure and review process.
01 / Expertise
AI automation.
Engineering underneath.
Automate repeatable engineering work, backed by the software, cloud and reliability expertise needed to run it.
Automate repeatable engineering
AI engineering & automation
Put coding agents to work on dependency updates, vulnerability remediation and recurring maintenance. Integrate them with your repositories, CI and review process.
Reduce repetitive engineering workSpend with intention
AWS cost
optimization
Understand where the money goes. Identify waste, implement the right changes and measure the difference.
Make your cloud more efficientBuild a better foundation
Platform
engineering
Give your team infrastructure they can trust. Automate delivery, improve visibility and build for resilience.
Remove operational frictionMake every request count
SRE &
performance
Find bottlenecks, reduce latency and improve reliability. Validate changes against real workloads and measurable goals.
Make your systems fasterConnect the pieces
Software
engineering
Turn complex requirements into maintainable applications, APIs and integrations that fit your business.
Build what your business needs02 / The approach
From repeatable task
to working automation.
Start with a bounded task and a clear definition of success. Build the workflow around your team’s tools, checks and approval process.
How infra-dev works-
01
Find the repeatable task.
Identify the backlog, required access and constraints. Agree on which tasks an agent can handle and when a person needs to decide.
-
02
Build the workflow.
Connect the tools, configure isolated runners and define validation steps. Make failures, costs and proposed changes visible.
-
03
Validate the result.
Evaluate the output against real tasks. Review the changes, measure useful outcomes and hand over a workflow your team can operate.
03 / A practical fit
Your team has a backlog.
Not everything needs to be manual.
Maintenance keeps slipping down the backlog. Turn dependency updates and vulnerability findings into scoped tasks and reviewable pull requests.
Your engineers repeat the same steps across repositories. Build reusable workflows around project-specific instructions, tooling and checks.
Your AI experiment needs to work in production. Add scheduling, isolated execution, concurrency controls and cost visibility.
A good place to start
What would you take
off your team’s backlog?
Tell us what you’re working with and what you’d like to improve.