Jacobo Pablos Mengs (Cordoba, 1979) is the CEO and founder of , a company specialized in the application of machine learning to the data generated by its clients (text, audio, video, data tables) to achieve objectives such as cost savings, process optimization or providing them with a better service. To find out a little better how Foqum works and what his plans are for the future, we have spoken with him.
Seven years ago you co-founded Foqum, coming from the world of banking, how do you remember that time? What advice would you give to someone who is thinking of starting their own business, based on your experience?
It was a time of which I have great memories and where I learned that when the product you sell is sophisticated and generates great value in the client’s income statement, it is key work together between technical and business teams both from your own company and from those of the clients.
At Foqum we sell simple solutions for business teams that sometimes have complex needs and, therefore, if adequate trust is not generated by working as a team, it is much more difficult to scale our solutions.
When it comes to advice, I’m more into receiving it than giving it, since I deeply believe that if you don’t constantly criticize yourself, it’s difficult to evolve. However, to give a structural one, I would say that before undertaking, correctly analyze “being able to afford it” both on a personal (family, economic, etc.) and professional level which for me is mainly summed up in evaluating the opportunity cost.
For me, the reflection is not so much whether I want to be an entrepreneur or not, whose main ingredients are freedom, fulfilling dreams, the desire to be your own boss, but rather whether I am prepared to face what it means to be an entrepreneur…
How did the idea of creating Foqum come about?
It was mainly due to two reasons: the need to make use of data by the business areas to continue evolving and improving their companies was beginning to consolidate, and we detected important technological advances in cloud infrastructures (AWS, Azure, Google Cloud,…) that allowed at an affordable cost train algorithms and serve them under different formats to clients.
On this basis we created Foqum with the great challenge of allowing our clients’ business areas to use artificial intelligence “inadvertently”.
How would you explain to our readers what you do at Foqum?
I begin by contextualizing a bit the type of companies machine learning that currently exist. In general, I group them mainly into two profiles: those that use third-party tools and introduce visualization and business intelligence (BI) layers, and companies like us that develop our own technological assets. This allows us to be able to explain the results we provide to clients (increasingly relevant and undoubtedly fundamental from the point of view of ethics in the use of data) and most importantly: to be able to evolve in the short, medium and long term. our tools.
At Foqum we develop solutions to be used by business teams, the objective being to allow them make the most of your company’s data in order to increase sales, save costs, or provide better service to its customers.
Our main tool is our AI platform that allows to process any type of data; text, video, image, audio or data in tables, executing our functionalities in specific use cases in order to get the most value from business data in less than 4 weeks.
What is machine learning and how can it help companies?
It is the science focused on the exhaustive analysis of data covering its entire life cycle from collection, processing and visualization, in order to enable data-driven decision making to be automatic, consistent, and measurable.
One of the aspects that I consider key in the management of a company is that “What is not measured can not be improved” and this is, in my opinion, one of the most important aspects that we should know about machine learning / data science, which allows you to measure the results and make decisions iteratively based on them.
What are Foqum’s clients like? What are your main needs?
SMEs and large multi-sector companies, whose main objective is to promote the development of their companies through the use of their data and where they put into practice one of our maxims, what is not measured cannot be improved. The needs are multiple, but one of the most relevant is in the least used / exploited type of data, such as text data. In this sense we have three main functionalities:
- Document classification in monolabel (for example invoices, cvs, claims, news, etc…) or multilabel that enters the type of information of the document. Following the previous list, for example, in the claims, include more labels such as; order problem, shipping delay, angry customer, etc…
- Extraction of information / specific fields in documents of more structured as; payrolls, invoices, expense tickets, tax agency models unless structured as official state gazettes or court rulings.
- Related semantic search. Our tool works in two formats: search in a free text bar “Google search style” or the possibility of dragging paragraphs or complete documents to find the most related documents that the company has. I illustrate it with a small example: a lawyer who needs to focus his procedural strategy on a specific case, can drag a sentence or a document from his office to our search engine, which will show him the most related sentences.
What do your clients value most about your work?
I would cite two main aspects:
- Ttransparency about what can/can be done and what cannot/cannot be done. In this sense, the fact that the technological asset has been developed by us allows us to give great interpretability to everything we deliver to clients, accompanying it with specific metrics supporting them in the evaluation of the results and the ROI of the investment.
- Short term analysis And if possible, always start with a pilot. This allows us to create cohesion / trust with the internal teams and with the client to be able to make better use of their economic resources.
What would you recommend to a company that wants to start its digital transformation but doesn’t know where to start? What do you think are the main shortcomings in this field in Spanish companies?
The truth is that we have run into this problem many times since the beginning of the company and that is why after a lot of internal analysis we created our product Discovery which answers questions like:Are you not sure which projects to tackle, which one to start with, which team to incorporate to undertake them, what the cost is and how to plan the investment of your digital transformation?”
Discovery does not judge whether the data is good, bad, too much or too little, but rather diagnoses their condition throughout their life cycle (collection, processing, visualization, and decision-making based on the data) for each area and process (operations, finance, etc.) with the aim of identifying specific potential projects to be developed and framed within a roadmap that allows the company to jump to the next level.
What headline about Foqum would you like to read next year in Marketing4eCommerce?
The sexiest technology company of 2023, a reference in machine learning and experts in document processing.
Imagine that you travel back in time ten years ago. What advice would you have given your Self at that time?
Take advantage of every moment of life because it flies…
Quick Quiz:
- What is the first social network you open in the day? LinkedIn
- iOS or Android? iOS
- App or website? Web
- In which eCommerce and how long ago did you make your last online purchase? Aqua di Parma
- And it was? candles for home
- Last book read? 11 minutes, by Paulo Coelho
- Recommend us a fiction series stranger things
- What website have you come across lately that has surprised you for the better?
- What is your favorite thing to do that has nothing to do with digital? Sport. Specifically golf, tennis and swimming.
- Let’s spin a magic chain: Which acquaintance of yours (from another company) do you think we should interview? Why? Josep Coll from Repscan, Manu Marín from Livall or
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