From problem framing to reliable delivery, we design and build AI products that are clear, verifiable, and made to evolve.
We connect data, models, tools, interfaces, and evaluation in one engineering path—giving intelligence a source, clear boundaries, and a coherent user experience.
Product engineering across information retrieval, agent workflows, and verifiable outputs.
A single-document RAG workspace with verifiable evidence.
A proof-of-concept product for PDF and Markdown analysis, bringing answers, structured reports, source evidence, and execution traces into one interface.
Additional project profiles are being verified and will be added as they are confirmed.
Every project starts with constraints and a definition of success. Prototypes answer critical questions; engineering makes those answers durable.
Map user tasks, data boundaries, risks, and measurable success criteria.
Combine models, retrieval, tools, and interface into a working end-to-end product.
Test quality, boundaries, and operational state with real tasks, then iterate.
SYSTEM VIEW
Clear boundaries let models, tools, and product behavior evolve without rebuilding the entire system.
Inputs pass through orchestration, connect to models and tools, and produce usable outcomes.
DiQi Tech is an AI product engineering company.
We focus on how complex AI capabilities enter real workflows: whether the interface is clear, evidence is traceable, and the system can evolve as models and requirements change.
Visit the DiQi Tech organization and accessible repositories on GitHub.