Data Infrastructure
Reliable data ingestion, transformations, and interfaces that power operations and decision-making, including LLM-based enrichment and cleaning with evaluation sets to verify accuracy.
Best when
Your data is spread across systems that don't talk to each other, and the manual work of consolidating it is eating staff time or blocking the automation you actually need.
Want to pressure-test fit quickly?
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Typical engagements
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Engineering Leadership
Senior technical leadership embedded with your team to align product, architecture, and delivery.
AI Integration
Most teams find the real problems after the pilot: token costs that outrun the value, context that degrades output quality as sessions grow, model choices that made sense in a demo but not at volume, and data privacy constraints that limit what can go to which provider. We build the infrastructure that makes AI reliable, cost-controlled, and compliant before those problems surface in production.
Workflow Automation
Map the manual overhead in your operations and build systems that reduce it. Whether that is a customer-facing product, an internal workflow tool, or a backend process that currently requires too much human intervention, we build it with reliability, security, and compliance as first-class concerns.
Platform Engineering
Right-sized infrastructure, CI/CD, and production-grade reliability practices that reduce operational risk. Not every problem needs Kubernetes.