Solutions
AI systems I design and build.
Four focused offers. Each page covers the problem, the architecture, security and deployment, how correctness is evaluated, and how an engagement starts. If your problem doesn’t fit these, I’ll tell you.
Enterprise Knowledge Assistants in English and Arabic
Staff waste hours hunting through scattered policies and documents, and generic chatbots answer without sources or respect for who is allowed to see what.
Agentic Workflow Automation
Multi-step processes that involve reading, deciding, and acting across several systems eat staff time, yet handing them to an unsupervised agent is too risky to trust.
Intelligent Document Processing
Teams retype data from PDFs and scans by hand, and mixed Arabic-English documents defeat generic extraction tools, making the process slow and error-prone.
AI Evaluation and Reliability
Teams ship AI features on the strength of a few good demos, with no measurement of whether the system is accurate, safe, or ready for production.
How I work
The same path on every engagement — from “we have a problem” to a system running in production.
-
Discovery
Understand the process, constraints, and what would actually be better.
-
Requirements & architecture
Scope it; design an architecture that fits your systems and data.
-
Engineering
Build with reliable tools — Python, FastAPI, PostgreSQL, containers.
-
Evaluation
Prove behavior with structured evaluation before launch.
-
Deployment
Ship into your cloud or on-prem, with the data-residency posture you need.
-
Monitoring & support
Observability, drift/cost monitoring, human-in-the-loop controls.