AlgoQuest System is now owned by Celinvest

Back in 2010, Elie Ouzi Koskas had already spent several years conceiving the database engine that would then become the core of the technology. Yet, at this moment, the technology was efficient but not mature enough to be marketed directly to customers. This is the reason why it was decided to create the company AlgoQuest System SA, to finance the development of the tool, and to market it and sell it to potential customers.

The technology is built around two main parts: the engine (called AlgoQuest Engine) and the tools (called AlgoQuest Tools). Roughly speaking, the Engine is the part where all calculations happen, and in which queries are handled. The Tools is the user interface of the system, allowing all interactions with the Engine: adding a new database, submitting new queries, updating content, collecting answers from the Engine, and making them readable for the end-user.

The main logic behind the Engine, and the key invention from Elie Ouzi Koskas, is a new way of managing data through a new approach of mathematics: the Engine only manages unique iterations of the data in databases, allowing to avoid repetitions in the calculation while still taking them into account for the final result. As a consequence, the Engine proves itself to be extremely efficient and creates a huge difference with standard database management systems for the management of combinatorial queries with high volumetry, answering SQL queries much faster, with 100% accuracy and no statistical approximation.

This engine relies on a fully new mathematical approach to be so efficient. Because it was built from the ground up with this new approach, many constraints known by all other database management systems (such as data indexing for instance) are not relevant anymore with this solution, making it much more agile and efficient.

Since 2010, Celinvest has been by very far the main financial support for AlgoQuest System (a few other minor investors joined the project as well, yet all other financial efforts cumulated did not equal what Celinvest injected in the technology). Yet, after over 9 years of financing for all the teams to develop the platform, no client purchased any license of the solution.

This is the reason why in July 2019, Celinvest decided to involve one of its founders with deeper technical knowledge as a trusted expert to not only audit the solution, but also review with the teams the development strategy and overall the organization of the company. After a few months of using the solution, confronting it in real market situations, and understanding the potential and limitations of the tool, he came to a question-raising conclusion. The Engine was indeed extremely powerful, yet is lacking so many necessary functions provided by all major actors today on the market (AWS, Oracle, Microsoft just to name a few) that it would take over another 10 years of development just to get closer to the “must-have” features that these solutions are providing today.

As powerful as the solution was at this moment, its true added-value did not compensate for the missing capabilities that were required by potential clients.

This is how we concluded in early 2020 that the way of auto-financing and self-developing the company was not a reliable way to go, and another path was needed.

Celinvest, as the primary financial investor of the company, suggested that the way to further develop the technology would be through a partnership with one of the major actors of the market. Such a partnership would have allowed the AlgoQuest System technology to get access to much larger capabilities, and then develop all the missing features quickly by leveraging the already existing technologies of such a partner. Yet, the discussion on this topic led to a disagreement with the technology inventor and blocked all the development opportunities for the company.

Following this, it was decided that Celinvest would not finance anymore a strategy we did not believe in; yet our investments in the technology remained fully valid. After a few months, it was then decided that AlgoQuest System SA would be liquidated, and following legal procedure Celinvest SA legally bought all assets of the company including the technology, all intellectual properties attached, and all applications of the technology (existing and future) that Elie Ouzi Koskas fully sold to the company. Consequently, all potential future developments of this technology are Celinvest’s property.

In September 2024, Google Research was awarded the prestigious Beale-Orchard-Hays Prize for PDLP (Primal-Dual Hybrid Gradient enhanced for Linear Programming), recognizing their breakthrough in solving large-scale optimization problems. This achievement validates a fundamental principle that has been at the core of AlgoQuest System’s technology since its inception over a decade earlier.

Both technologies independently arrived at the same revolutionary insight: traditional approaches relying on matrix factorization and extensive indexing are fundamentally limited by combinatorial explosion. The solution lies in transforming complex optimization problems into graph-based path-finding operations that scale linearly with data volume.

While Google’s research focused on linear programming optimization, and AlgoQuest System on relational database management, the underlying mathematical principles converge remarkably:

• Elimination of expensive computational overhead: AlgoQuest removes the need for data indexing; PDLP eliminates matrix factorization requirements
• Linear complexity achievement: both technologies successfully avoid combinatorial explosion through graph-theoretical approaches
• Processor efficiency optimization: AlgoQuest demonstrated up to 15x better processor utilization for actual calculations; PDLP achieves similar gains through matrix-vector multiplication instead of factorization
• Superior scalability: performance advantages increase proportionally with data volume in both systems

The recognition of PDLP’s approach by the Mathematical Optimization Society (one of the highest honors in computational optimization) confirms that the mathematical foundations pioneered by AlgoQuest System represent a fundamental advancement in how we approach large-scale combinatorial problems.

Where traditional database systems face insurmountable bottlenecks at high volumes, and where conventional optimization solvers require expensive hardware and extensive memory, both AlgoQuest and Google’s research demonstrate that the path forward lies in fundamentally reimagining how we structure these computational challenges.

AlgoQuest System’s proven performance on real-world banking data (delivering in 12 minutes what took optimized enterprise systems over 11 hours) demonstrated these principles years before they gained broader recognition in the optimization community.

The parallel evolution of these technologies in different application domains underscores a broader paradigm shift in computational problem-solving: moving away from brute-force approaches toward mathematically elegant solutions that leverage graph theory and linear scaling principles.

For years, AlgoQuest System’s approach was met with skepticism from an industry deeply entrenched in conventional methodologies. The independent validation by Google Research, and the subsequent recognition by the world’s leading optimization authority, fundamentally changes this narrative.

What was once considered an unproven alternative is now recognized as part of a legitimate paradigm shift in how we solve large-scale computational problems. Organizations seeking solutions to combinatorial challenges at scale now have concrete evidence that this mathematical approach delivers results where traditional methods fail.