AI strategy
Prioritise opportunities by business value, data availability and implementation effort.
Data-driven decision systems
From data to decisions. From decisions to action.
I build systems that automatically analyse metrics, time series, documents and news – and turn the findings into controlled actions. Built with the rigour of quantitative finance.
The problem
The data is there. The response comes too late.
Relevant signals sit in reports, time series, e-mails, news and customer feedback. They are reviewed manually – or not at all. Deviations get noticed once they have already become costly.
- 01Metrics and time series
- 02Documents and news
- 03Customer feedback and requests
Services
For entrepreneurs, management teams and investors.
Less manual work. Earlier signals. Decisions that can be checked. We define success in your terms: time saved, error rates, response times and total operating cost.
Analysis & assistants
Combine quantitative models with document analysis and AI assistants.
Integration & execution
Connect existing systems and trigger actions with clear approval rules.
Validation & operation
Test quality, monitor costs and maintain the solution in daily use.
How it works
Four steps, one closed loop.
Capture data.
Quantitative sources (metrics, time series, systems) and qualitative sources (documents, news, feedback) are connected.
Understand patterns.
Models detect patterns, trends and deviations – validated on your historical data.
Identify what matters.
Defined triggers decide when an event is relevant. Thresholds and rules are transparent.
Take action.
A notification, a task, an update in a business system or a defined process – automatically or after approval.
Use cases
Where this typically makes a difference.
Finance & treasury
Continuously monitor liquidity, risk and market metrics.
limit exceeded → alert + task
Research & compliance
Screen news, publications and documents, summarise what matters and route it for approval.
relevant update → review
Sales & service
Classify feedback and requests, measure sentiment, assign cases.
critical feedback → ticket
Operations & planning
Detect anomalies in sales, inventory or process data early.
planning deviation → planner
Examples for illustration. Every system is tailored to your data and processes.
Control
Automatic where it is safe. Approved where it matters.
Depending on the use case, actions run automatically or after human approval. Clear rules, permissions and a traceable log keep every process under control – and auditable.
Data protection is part of the design: we agree which data may be processed, where it is stored and which providers can access it. Permissions, retention and human approval are defined before deployment.
- ARules, not black boxes
- BRoles & permissions
- CTraceable activity logs
Working together
Start small, scale on evidence.
Intro call
30 minutes, free of charge. Clarify the situation and the potential.
Analysis & concept
Define data sources, triggers, actions and control points.
Prototype on real data
Validate benefits and error rates before scaling the solution.
Operation & development
Monitoring, adjustment, expansion.
About
Karim Jadallah
I connect business leadership, quantitative modelling and practical AI implementation. My career has taken me from UBS Fixed Income Research through asset management as Head of Investment to SwissQuant and leading quantitative consulting in the UBS Quant Hub.
Today, I help entrepreneurs, management teams and investors translate that experience into better processes: from identifying the opportunity and building a prototype to integration and ongoing monitoring.
- Since 2000Finance, models and automation
- LeadershipInvestment management and quant consulting
- CQFCertificate in Quantitative Finance
Contact
Which decision should happen faster?
Briefly describe your situation. I will get back to you within two working days.