We design and operate custom systems, cloud infrastructure, and internal processes for teams that need to move fast without losing engineering rigor. AI is one more tool in the workflow — engineering judgment stays human.
Four fronts that almost always go together: building custom software, running it as our own product, keeping the infrastructure it runs on healthy, and using AI to make all of that better.
Systems built for a business's real process, not a generic use case: a proprietary service bus and frontends, designed end to end. This is how we built SGS for Viollier Ajustadores de Seguros (see the case →) and how we work with EGR Corredora de Seguros (see the case →).
Platforms we run as an ongoing product, with continuous evolution and support. This is how we built and operate Nexo, BSP's operational flow manager. See the full case →
Infrastructure as code, Kubernetes orchestration, monitoring and observability, and continuous deployment pipelines. Systems that fail less and, when they do fail, warn you before your customer does.
Legacy system modernization and practical AI adoption in development and operations workflows: agents, repetitive task automation, and judgment about where AI actually adds value.
We work in sectors with demanding processes — healthcare, insurance, logistics — where software has to be correct, not just good-looking.
Web platforms for case management, approval workflows, and document traceability, integrated with the client's existing systems.
Android apps for field operations teams — inspections, data collection, and work under intermittent connectivity.
Observability for servers, networks, and critical services, with alerting configured for the real context of each operation.
Migrating .NET systems and monolithic architectures toward services that are simpler to maintain, without stopping operations during the transition.
We don't sell AI as a product. We use it as part of the craft, the same way we use version control or automated testing.
Generating supporting code, documentation, and tests, so engineering time focuses on the decisions that matter.
Agents that help catch errors and security risks during development, not after the incident.
Every architecture decision, every business trade-off, is made by an engineer. AI proposes; the team decides.
Tell us what you're building or what system needs attention. We reply from info@inline.cl.