Focused AI engineering offers for teams that need production outcomes.
I help you ship the hard middle: model behavior, retrieval quality, tool use, observability, cost controls, and the product workflows around them.
Design and build an AI feature or product slice from idea to usable production workflow.
Architecture, UX flow, provider integration, evaluation hooks, and release-ready implementation.
Teams with a clear problem and a product surface that needs AI to become dependable software.
Audit and improve retrieval pipelines that need better grounding, latency, safety, or answer quality.
Corpus review, chunking/search strategy, eval set design, reranking/routing recommendations, and implementation fixes.
Teams with a working RAG prototype that is not yet reliable enough for customers.
Connect agents to real tools, workflows, and business systems without losing control of behavior.
Tool/server design, permissions, observability, failure handling, and production integration.
Teams adding MCP servers, internal agents, or context-aware automation to existing software.
OAuth, support intake, app catalog, AI Units, and AI gateway boundaries live inside this hub.
Switchboard and the free tools keep the advice grounded in products that have to work for real users.
English and Arabic surfaces are built together, with RTL support treated as product architecture.
Pricing is scoped privately after fit, risk, timeline, and delivery shape are clear.