We build AI and data tools that help companies serve customers better, understand their financial performance and spend less time on routine work.
We combine Big Four analytics and valuation experience with hands-on development. We identify what is worth building, then test a working version with your team before you invest in a full solution.
Test before you commit.Tested with the people who will use it.Our approach
Big Four practice leadershipBuilt and led a financial modelling and data analytics practice across the Middle East.
Group CFO experienceFinancial and operational responsibility in mid-sized and multinational businesses.
Regional understandingMore than thirteen years working with businesses in the Middle East.
Selected workClient work, prototypes & our own platforms
What we built. What it changed.
Our work includes financial reporting tools, AI matching between creators and clients, and a platform for analysing online feedback. Each addresses a specific business need.
Finance intelligence · Healthtech
Report sooner. Ask better questions.
Financial trendsOperating context
What changed? What needs attention?A repeatable financial review
Illustration of the review approach · no client data
Ongoing Kojent engagement
Report faster. Explain what changed.
For a healthtech group, we built tools that substantially shortened month-end reporting and added a repeatable review of the results.
The analysis examines financial trends alongside operating information: what has changed, what may explain it and what needs investigation. It brings the questions an experienced CFO would ask into each reporting cycle.
The value
Management gets the numbers sooner, with analysis of the changes that need attention. Finance spends less time preparing the report and more time investigating the business.
Our role
We designed the reporting process, combined the group’s financial data and built the AI-supported analysis and interactive board dashboard. We continue to provide financial analysis.
Kojent’s in-house platform
Understand how the market sees a business.
A company’s website says what it promises. Reviews, social posts and employee feedback reveal how people experience it. We built sentimend to collect and analyse those accounts across a business and its competitors.
The capability
AI gathers and organises public feedback, identifying recurring themes, concerns and perceived strengths. The analysis can be repeated as new information appears.
Why it matters
Management can see where service needs attention or where competitors disappoint customers. A buyer can use the same evidence to decide what to investigate before an acquisition.
We analyse publicly available sources we are permitted to access. Feedback guides further investigation; it does not establish a company’s value.
An influencer marketing agency wanted to grow without adding manual work at the same pace. We assessed its market and the services clients valued, then set out a technology roadmap for delivering them at scale.
We built prototypes of the most important tools, including AI matching between creators and clients. The agency could test and refine the features and user experience before handing the work to an outsourced development team.
The value
A clearer brief for developers, based on working tools the agency had tried. This helped establish which features mattered before committing to full development.
Our role
We took the project from market assessment to technology roadmap, built the critical prototypes and refined them for development handover.
Industrial finance & treasury
100+
month-end processes automated
Capacity redirected towards analysisExperience from a prior role
Illustrative role portrait
Team experience · delivered in a prior role
Give finance more time to work with the business.
For a leading industrial business, we led the design and implementation of automation across more than 100 month-end processes in Finance and Treasury. Reporting was faster, and the team could spend more time on analysis and working with other departments.
Rules-based software handled the recurring tasks, freeing the team to deal with questions that required judgement.
Team experience · developed at a Big Four firm
Make a new tax regime visible in the numbers.
Ahead of the UAE’s introduction of VAT, businesses needed to understand what the new rules would mean for their own transactions and accounts. We helped develop a machine-learning tool to analyse account-level data and assess potential VAT exposure.
The tool connected a broad regulatory change to the detail of each business: which accounts could be affected, how they might be treated and where further tax review was needed.
The value
A company-specific view of potential exposure, giving finance and tax teams a clearer basis for investigating the affected accounts and preparing for implementation.
Our role
We combined financial analysis and machine learning to make account-level VAT assessment repeatable. The tool supported professional review; it did not replace tax judgement.
Machine learning · VAT readiness
One new tax. Different exposures.
Account-level analysisWhat is affected? What needs review?
Potential exposure informs professional review Illustration · no client data
A prototype makes a proposal concrete. People can use it, discover what is missing and change it. We do that early, while the design is still easy to revise.
01 / Assess
Work out what is worth fixing.
We examine the task, the people doing it and the information they use. We agree what would count as an improvement: a better service, better decisions, lower costs or time saved.
OutputA business case and a small, testable first step.
02 / Test
Put a prototype to work.
Your team uses a working version on a real task. We see where it helps, where it falls short and what needs to change before you spend on a full build.
OutputA tested prototype and a decision to build, revise or stop.
03 / Develop & improve
Build it into everyday work.
We develop the tool or prepare it for your development team, connect it to the way you work and establish who will maintain it. Results give us a basis for testing later changes.
OutputA working solution, clear ownership and a way to track results.
How we judge success
Count the effort as well as the output.
A tool that produces an answer in seconds may still take hours to check. We count the time spent preparing data, reviewing outputs and correcting mistakes when deciding whether it is worth using.
We also design for the next decision. Recording which matches succeed, which recommendations help and where errors occur gives a business evidence to improve the tool—and knowledge competitors cannot get simply by buying the same software.
Meet the teamCommercial experience. Hands-on delivery.
The people behind the work.
Our experience spans financial modelling, valuations, analytics and running finance functions. We bring that understanding to the tools we design and the decisions they support.
Founder · Analytics & technology
Tim Kroemer
Tim established and led a Big Four financial modelling and data analytics practice across the Middle East. He has held group CFO roles in mid-sized and multinational businesses and works directly on the design and development of our solutions.
Kirti brings Big Four experience in deals and valuations. Her focus is the financial case for a decision: how a business is valued, which assumptions matter and what those assumptions mean for an investment.
Can you connect a business problem to a useful solution? We’d like to hear from people who combine commercial judgement with the ability to build, test and improve.
Tell us your website and what you want to improve. We’ll suggest an opportunity based on public information, explain why it may matter and identify what we would need to check.
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Tell us what is slowing the business down or what you want to do better. We’ll discuss the problem, the information you have and whether a tool could make a worthwhile difference.
