Engineering Services
We build production AI agent systems for companies shipping distributed products and internal platforms across web, mobile, and operational environments where reliability, governance, and runtime quality are non-negotiable.
AI Systems Engineering
Architecture and implementation for production agent workflows, tool orchestration, and evaluation pipelines.
View service →Backend & Platform Engineering
Distributed backend and platform foundations for resilient AI delivery in production.
View service →RAG & Knowledge Systems
Retrieval architecture for grounded AI outputs with freshness, access control, and governance standards.
View service →Delivery Surfaces
The core service is AI agent engineering. Web, mobile, and internal software are the delivery surfaces where those systems are operated, supervised, and used in production.
Custom Product Workflows
Agent systems embedded into business-specific products, internal tooling, and operational workflows that need more than prompt wrappers or generic automation.
Web Application Surfaces
Browser-based operator consoles, customer portals, and internal tools where agents, approvals, observability, and human handoff need to work together in production.
Mobile Application Surfaces
Mobile experiences for field teams and end users where AI-driven workflows, orchestration, and platform reliability need to extend beyond the browser.
Latest thinking
Featured Insights
Architecture notes on evaluation, platform reliability, retrieval, and agent operations for companies shipping AI in production.
Event-Driven Patterns for Production AI Workloads
Production AI systems become more reliable when model work leaves the user request path and moves into explicit event-driven workflows.
Human-in-the-Loop Patterns for High-Risk Agent Workflows
High-risk agent workflows need explicit review patterns, not vague promises that humans can always intervene later.
Permission-Aware RAG for Enterprise Knowledge Systems
Enterprise RAG systems fail when retrieval relevance is optimized without equal attention to permissions, freshness, and source trust.