Data to decisions. Automated.
Automated analysis systems for R&D teams and business leadership.
What I build
Automated analysis systems
I take the analyses your team repeats by hand, across experiments, runs, and measurements, and turn them into applications anyone on the team can drive. Set the inputs, explore the output, reach the answer, without needing data modeling or analysis skills.
Includes: Data pipelines (ETL/ELT), data modeling, visualization, UI/UX
Systems modeling and simulation
Modeling of complex, multi-disciplinary systems. Synthetic data design for experiments. Sensitivity analysis and scenario modeling.
Measurement and characterization system design
Designing how to measure quality, performance, and outcomes. Defining tolerances, turning messy physical reality into decision-grade data.
Calibration procedures design
Designing calibration procedures for instruments, outputs, and processes. Reproducible, traceable results across runs and conditions.
AI and agentic systems development
End-to-end: architecture, development, deployment. AI agents, multi-agent systems, RAG systems, skills, connectors (MCP servers), Claude CoWork plugins. The AI layer on top of your data.
Knowledge graph and ontologies development
Graph databases (Neo4j), ontology design, knowledge representation. Decision and tracing systems where logic and audit trail are explicit and every answer is explainable.
AI literacy training and support
Hands-on workshops and ongoing support. Help your team understand, adopt, and get real value from AI tools in their daily research work.
Data literacy and BI self-service training
Teach your team to explore data and answer their own questions. Fewer requests funneled through one person, more of the team working with data directly.
Process automation and documentation
Automate existing manual data processes. Document systems so they run without me in the loop.
How I work
Map it
Requirements gathering first: the decisions you need to make, the people who make them, and the sources that should support them.
Model it
One trustworthy model: extraction, transformation, and a layer that matches how your team actually thinks.
Make it usable
Applications your team can drive directly. Built in short, agile iterations: you work with a live version early and steer what comes next.
Hand it over
Automated and documented, so it runs without me.
Sample work
Arabtech Data
Deployed BI dashboard for a public-data analytics project. Full data pipeline and interactive visualization.
Visit the dashboard ↗Power BI MCP connector
Privately query your published Power BI models from any MCP client, with row-level security enforced on every query, no need for Fabric license. The foundation for the natural-language layer I build on top.
Get the connector →
Querist is my studio. I'm Effrat Katz.
I do the data work and the AI work. Most consultancies split those across teams. I do both, end-to-end, with multidisciplinary R&D, business, and financial experience.
I've spent a decade turning fragmented, multi-disciplinary data into decisions. I started in R&D at Landa Digital Printing, as a print-quality researcher inside a multi-disciplinary effort where chemistry, physics, and software all fed one technology. That work taught me to take messy physical reality and make it measurable.
From there I moved into BI consulting for B2B SaaS companies, building trustworthy data models over the systems they already run.
Now I'm building the next layer on top: AI and graph tools that turn trusted data into answers and decisions.
I work in English and Hebrew. Find me on LinkedIn.
Let's talk
Tell me what you're trying to solve with your data.