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I build and scale products, teams and platforms.
Over 20+ years, I’ve helped grow…
Over 20+ years, I’ve helped grow…
Articles de Jean-Baptiste
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Why prompt modeling is the foundation of AI visibility
Why prompt modeling is the foundation of AI visibility
Most brands are measuring AI visibility backward : they start with the answer, then they measure the output and they…
1 commentaire -
Wake up Europe !
Wake up Europe !
2018 may be the year a company will reach 1 trillion dollars in market cap and it will be a tech company. If I sum the…
2 commentaires -
Why we decided to come back to France in Montpellier area after 11 years in the Silicon Valley and why you may want to ?
Why we decided to come back to France in Montpellier area after 11 years in the Silicon Valley and why you may want to ?
When we said to our friends and coworkers that we were leaving the bay area to go work in south of France, we got a lot…
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Jean-Baptiste Pringuey a republié ceciJean-Baptiste Pringuey a republié ceciOur CEO, Rachid Ait Addi explains on BFM Business how Meikai helps brands boost their visibility in AI search. 🎥 Watch the interview below (in French). Arnaud Kyriacos Mohamed OUADAH Jean-Baptiste Pringuey Yannick Galatol Lucas Reis Youssra E. Garti Anthony Sendra Ben Sharpington Luca Aiello Frédéric Charoy Christian Guinot Marion Raith
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Jean-Baptiste Pringuey a republié ceciMerci Clement Baccar et toute l'équipe de Brut. pour cet échange à Marseille, quelques minutes après la remise des CMA CGM Startup Awards. Expliquer en peu de mots ce que fait Meikai, c'est un exercice que j'adore : quand vous demandez à ChatGPT quel parfum offrir ou quelle voiture choisir, l'IA répond avec deux ou trois marques. Nous mesurons chaque jour si une marque fait partie de la réponse, pourquoi, et comment y entrer. Clément a posé les bonnes questions, celles que se posent les consommateurs, pas seulement les marketeurs. C'est exactement le regard qu'il faut sur ce sujet. Merci Brut, merci Rodolphe Saadé, ZEBOX et CMA Media pour cette journée, et rendez-vous très vite pour la suite avec le groupe. #Meikai #GEO #IA #CMACGMStartupAwards Jean-Baptiste PringueyYannick GalatolLucas ReisMohamed OUADAHArnaud KyriacosMarion RaithYoussra E. GartiLuca AielloAnthony SendraBen Sharpington Christian GuinotJean-Baptiste Pringuey a republié ceciClement Baccar, Head of Data & AI chez Brut., a fait partie du jury de la 3e édition des CMA CGM Startup Awards, organisée à Marseille à l’occasion d’Artificial Intelligence Marseille. C’est dans la catégorie médias de nouvelle génération que Clément a participé au jury, qui a récompensé Rachid Ait Addi, fondateur et CEO de Meikai. Meikai développe une plateforme permettant aux marques de mesurer, comprendre et optimiser leur visibilité dans les assistants d’IA générative. "On voit bien que les agents d’IA changent déjà la manière dont on cherche de l’information et dont on découvre des marques. Ce que fait Meikai est intéressant parce que ça répond à une vraie question : comment savoir si une marque est visible dans ces nouveaux usages, et comment améliorer cette visibilité ?" - Clément Baccar, Head of Data & AI chez Brut. Félicitations à Rachid Ait Addi, à Meikai et à l’ensemble des lauréats de cette édition.
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Jean-Baptiste Pringuey a republié ceciJean-Baptiste Pringuey a republié ceci82,5% des conversations retail avec une IA commencent sans qu'aucune enseigne soit nommée. Le consommateur exprime un besoin. Pas encore un distributeur. Avec Nicolas JAIMES et Open Garden, nous avons analysé plus de 94 000 conversations retail en français et testé 7 500 questions réelles sur ChatGPT, Gemini, Perplexity et Copilot. C'est le premier baromètre Open Garden × Meikai, et quelques résultats m'ont vraiment surpris : - Sur ces conversations sans enseigne, seules 3,3% débouchent sur une réponse qui en cite une - Quand l'IA introduit elle-même un distributeur, Amazon apparaît dans 20,3% des cas, loin devant leboncoin (9%) et Carrefour (8,7%) - Dans les cartes produit, l'écart se creuse : 30% pour Amazon, 10,4% pour Fnac - ChatGPT cite une enseigne dans 46,6% de ses réponses, Perplexity dans 22,5% - Les médias pèsent près de la moitié des liens cités, les sites d'enseignes à peine 20% Pour un retailer, la conséquence est simple : être cité dans une réponse ne garantit pas d'être proposé comme vendeur. Et un score global de "visibilité IA" masque des réalités très différentes entre le texte, les liens et les modules shopping. L'espace est ouvert. Il reste à l'occuper, en organique comme en payant. Merci à Nicolas pour ce décryptage. L'article complet est en commentaire. #GEO #RetailMedia #IA #Retail #Meikai Jean-Baptiste Pringuey Yannick Galatol Lucas Reis Mohamed OUADAH Anthony Sendra Arnaud Kyriacos Marion Raith Youssra E. Garti Christian Guinot Ben Sharpington Luca Aiello
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Jean-Baptiste Pringuey a republié ceciJean-Baptiste Pringuey a republié ceciSi les consommateurs français ne demandent pas forcément Amazon, les assistants IA se chargent de le leur proposer lorsqu'ils sont en phase de recherche. C’est l’un des enseignements du premier baromètre Open Garden × Meikai, qui analyse plus de 94 000 conversations retail en français. Dans 82,5% des échanges, l’utilisateur ne cite aucune des 95 enseignes suivies. Il cherche un téléphone à moins de 200 euros, compare des vélos ou demande un conseil. Le besoin est exprimé, le distributeur reste à choisir. L’assistant introduit une enseigne dans seulement 3,3% de ces conversations. Mais lorsqu’il le fait, Amazon apparaît dans 20,3% des réponses, loin devant Leboncoin (9%), Carrefour (8,7%) et Decathlon (8,5%). Amazon ne figure pourtant pas parmi les huit enseignes les plus citées dans les demandes initiales, un classement dominé par Carrefour. De quoi rappeler aux retailers que leur notoriété auprès des consommateurs ne leur garantit pas la même place dans les réponses des assistants. Et que toutes les formes de visibilité ne se valent pas. Un second volet du baromètre soumet 7 500 questions issues de conversations réelles à ChatGPT, Gemini, Perplexity et Copilot. Amazon y représente 10,3% des mentions textuelles d’enseignes suivies… mais 30% des apparitions d’enseignes identifiées dans les cartes produit, ces modules qui présentent directement une offre et un marchand. Les bases de calcul diffèrent. Reste que son poids est particulièrement élevé là où l’assistant propose concrètement un vendeur. Autre résultat qui mérite l’attention : les médias et contenus éditoriaux représentent 49,3% des liens cités dans ce test. Les tests et comparatifs conservent donc une place dans l’information mobilisée par les IA. Sans garantie, pour leurs éditeurs, de récupérer le clic. Pour les retailers, suivre un score global de "visibilité IA" risque de masquer l’essentiel : être cité dans une réponse, apparaître dans une source et être proposé comme marchand sont trois positions bien différentes. Le baromètre mesure ces présences, pas les ventes qu’elles génèrent. Mais il permet déjà de voir qui occupe le terrain. Lien vers l'article : Merci à l'équipe Meikai (Rachid Ait Addi, Jean-Baptiste Pringuey et tout particulièrement Lucas Reis obrigadooooo)
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Jean-Baptiste Pringuey a republié ceciJean-Baptiste Pringuey a republié ceci82,5% des conversations retail avec une IA commencent sans qu'aucune enseigne soit nommée. Le consommateur exprime un besoin. Pas encore un distributeur. Avec Nicolas JAIMES et Open Garden, nous avons analysé plus de 94 000 conversations retail en français et testé 7 500 questions réelles sur ChatGPT, Gemini, Perplexity et Copilot. C'est le premier baromètre Open Garden × Meikai, et quelques résultats m'ont vraiment surpris : - Sur ces conversations sans enseigne, seules 3,3% débouchent sur une réponse qui en cite une - Quand l'IA introduit elle-même un distributeur, Amazon apparaît dans 20,3% des cas, loin devant leboncoin (9%) et Carrefour (8,7%) - Dans les cartes produit, l'écart se creuse : 30% pour Amazon, 10,4% pour Fnac - ChatGPT cite une enseigne dans 46,6% de ses réponses, Perplexity dans 22,5% - Les médias pèsent près de la moitié des liens cités, les sites d'enseignes à peine 20% Pour un retailer, la conséquence est simple : être cité dans une réponse ne garantit pas d'être proposé comme vendeur. Et un score global de "visibilité IA" masque des réalités très différentes entre le texte, les liens et les modules shopping. L'espace est ouvert. Il reste à l'occuper, en organique comme en payant. Merci à Nicolas pour ce décryptage. L'article complet est en commentaire. #GEO #RetailMedia #IA #Retail #Meikai Jean-Baptiste Pringuey Yannick Galatol Lucas Reis Mohamed OUADAH Anthony Sendra Arnaud Kyriacos Marion Raith Youssra E. Garti Christian Guinot Ben Sharpington Luca Aiello
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Jean-Baptiste Pringuey a partagé ceciDoing GEO seriously at scale is a hard problem and requires sophisticated data science and engineering. At Meikai, even the strongest coding models we use struggle to help us improve the performance of our agents. Building systems that learn from feedback takes a lot of work. The harness matters: how you run agents, evaluate their outputs and measure whether changes actually improve them. Our harness skills are now much bigger than our production prompts and code. Our evaluation grids cover dozens of dimensions, with models from both OpenAI and Anthropic acting as judges. Recent research explores similar ideas. Mind Reader, published at ACL 2026, studies how understanding the intent behind queries can improve content visibility in AI answers. Turning research into reliable results at scale is a substantial engineering challenge. If you’re into software engineering and interested in AI, invest in mastering harness engineering, it will become a critical skill ! Rachid Ait Addi Mohamed OUADAH Arnaud Kyriacos Luca Aiello Ben Sharpington Youssra E. Garti Marion Raith Lucas Reis Yannick Galatol Anthony Sendra Christian Guinot
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Jean-Baptiste Pringuey a partagé ceciSuper proud to see Meikai becoming a world leader in GEO for enterprise (ask ChatGPT to compare Meikai to other big GEO tools and you will see) working with some of the best companies in the world. We have a lot more great news coming up soon! Marion Raith Mohamed OUADAH Rachid Ait Addi Yannick Galatol Arnaud Kyriacos Ben Sharpington Youssra E. Garti Luca Aiello Lucas Reis Anthony Sendra Christian Guinot LET'S GO 🚀🚀🚀🚀Jean-Baptiste Pringuey a partagé ceciHow can fragrance brands stand out as discovery moves into AI? ✨ Interparfums partnered with us to explore how ChatGPT Ads could strengthen brand visibility within AI-driven experiences. Together with Meikai, they compared visibility with and without ad triggers to understand how its brands appeared across relevant prompts. ✅ The results revealed stronger alignment with consumer conversations, new brand signals, and a level of total brand visibility its brands had never achieved before. Read the full story: https://lnkd.in/ekZMWNHX
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Jean-Baptiste Pringuey a partagé ceciAt Meikai we believe that GEO ( generative engine optimization ) and GEA ( generative engine advertising) needs to work together. We know this is the beginning of one of the largest transformation in the open web and we are continuing to be laser focused on building the best product. We are happy and lucky to work with such great partners and customers. Let's Go team ! Marion Raith Rachid Ait Addi Mohamed OUADAH Lucas Reis Luca Aiello Ben Sharpington Youssra E. Garti Anthony Sendra Yannick Galatol Arnaud KyriacosJean-Baptiste Pringuey a partagé ceciCriteo published the Interparfums ChatGPT Ads case. Interparfums ran one of the first flights in Criteo’s ChatGPT Alpha this spring and we were the measurement partner. The results : +45.5% combined visibility when ads triggered and 16.6% share of ad space.
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Jean-Baptiste Pringuey a republié ceciJean-Baptiste Pringuey a republié ceciA citation used to be a link. Now it is a source you can explain. Last month the IAB published its framework for measuring visibility in the AI era. One of its four pillars is Portrayal: not whether an assistant mentions your brand, but how it describes you. That raises the obvious next question. Where does the portrayal come from? Assistants build their answers from the pages they cite. Most brands now know which pages get cited. Almost none know what those pages actually are. So we built it. Page Classification is live in Meikai. For every page an AI cites, we read it and classify it for your brand: whether it is editorial, sponsored or affiliate-funded, what kind of page it is, how central you are to it, and whether you are portrayed positively, neutrally or negatively. The IAB is blunt that sentiment is where AI visibility tools are least reliable, and that providers should be able to show their work. So every label comes with the exact quote from the page that supports it. When the evidence is not there we say unknown instead of guessing. And your team can correct any label. The negative filter is the one I would not skip. If an assistant keeps citing a page that criticises you, that page is writing part of the answer about you. Now you can find it in seconds. I break it down in the slides. #GEO #AIVisibility #GenerativeAI #Meikai Jean-Baptiste Pringuey Yannick Galatol Lucas Reis Mohamed OUADAH Arnaud Kyriacos Luca Aiello Anthony Sendra Ben Sharpington Marion Raith Christian Guinot Manano Omata
Jean-Baptiste Pringuey a commenté un post
2 j.
Un grand merci Paulina Jonquères d'Oriola pour ce super post !
Chez Meikai, nous sommes très fiers d’accompagner les médias, nos clients et nos partenaires dans l’une des transformations les plus importantes depuis la création du Web.
Tu connais ma conviction : les contenus de qualité, les informations et les perspectives uniques apportées par des humains, avec l’aide de l’IA, resteront essentiels.
Ce n’est bien entendu que le début ! Et nous sommes aussi fiers d’avoir toute notre équipe d’ingénieurs en France. Cocorico ! 🇫🇷
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Jean-Baptiste Pringuey a aimé ceciJean-Baptiste Pringuey a aimé ceciThere are exactly 0 FDA-approved therapies for the hundreds of millions of people suffering from diseases like POTS, Long COVID, MECFS or hEDS. We created ChronicleBio to change this. By building the deepest dataset on these conditions and leveraging AI, we will understand what the biology behind the symptoms is. From there, we can map the right drugs to the right patients. Thanks Forbes for featuring the work of our amazing team. https://lnkd.in/giPjpkurFormer OpenAI Exec Fidji Simo’s $20 Million Plan To Solve Her Chronic Disease And OthersFormer OpenAI Exec Fidji Simo’s $20 Million Plan To Solve Her Chronic Disease And Others
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Jean-Baptiste Pringuey a aimé ceciJean-Baptiste Pringuey a aimé ceciBack in December 2022, Yuma was the first company to put AI agents in production for ecommerce customer support. Almost 4 years later, we have had a pretty great run pushing that idea to its limits. But after 4 years building on top of a technology evolving this fast, something had to change... We call that change Yuma 2.0. One AI agent. One set of rules. Every customer. Every channel. Inbound and outbound. That is really the idea: a single, unified platform to run your entire CX operation. When we started Yuma, the challenge was getting an AI to reliably solve a customer support ticket. We had to do all kinds of gymnastics to get the models to behave, stay within the right boundaries and reliably take actions. Today, models are dramatically more capable. It has also never been easier to spin up a basic AI support agent. Give someone Claude or ChatGPT and they can probably get a convincing demo running in a few days. But a demo is one thing. Building something a company can trust to run at scale is another. More importantly, our customers are asking us for much more now. As I keep telling the team, bringing the most value to our customers is paramount. Today, CX teams are still spread across too many tools. One for support. One for voice. One for social. Another for outbound marketing. Different rules. Different context. Different levels of trust. I think that era is over. Our customers increasingly want to consolidate their customer experience around a single core system they can trust. So after almost 4 years of building Yuma, it was time to make another big leap. Part technological leap, part leap of faith, part founder instinct ;) Because I still deeply believe we are only seeing the very early glimpse of what AI will let us achieve. So with Yuma 2.0: • A single, unified set of rules ✅ • Inbound support across email, chat, social, reviews and voice ✅ • Outbound campaigns, from proactive service notifications to marketing and re-engagement ✅ • A deep understanding of every customer across every interaction ✅ • Public social engagement across Facebook and Instagram ✅ • Pre-sales conversations that help customers buy and increase conversion ✅ All powered by the same underlying AI agent. And that last detail matters: • Not a voice product bolted onto support. • Not a separate agent doing outreach. • Not 5 systems trying to understand the same customer. 👉 One agent, operating across the entire customer experience. We have baked almost 4 years of work, mistakes, customer feedback and learnings into this new version of Yuma. It is more powerful, more accurate, and lets our customers do things that simply were not possible when we started. I think this is where CX is going. And just like we did back in 2022, we want to be early in showing what that future can look like. That is Yuma 2.0. Come talk to us and see the mind-blowing things you can build today. Cheers to the next 4 years 🥂
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Jean-Baptiste Pringuey a aimé ceciJean-Baptiste Pringuey a aimé ceci[#SALON]📍L'équipe Axys vous attend sur le salon PRODURABLE 2026 ! Comment transformer ses ambitions RSE en résultats concrets et durables ? C’est l’un des défis majeurs auxquels font face les organisations aujourd’hui, et c’est précisément le sujet que nous avons à cœur d’aborder lors de cette nouvelle édition de Produrable. 🚀Tout au long de l’événement, retrouvez-nous sur le stand 111 (niveau 3) pour échanger avec nos équipes sur vos enjeux de transformation, de performance durable et de mise en œuvre opérationnelle de votre stratégie RSE. 🎯Venez partager vos projets, vos défis et découvrir comment nous accompagnons les organisations pour faire de la durabilité un véritable levier de performance. À très vite sur notre stand ! Frédérique WINCKEL, Hélène Métras, Clément LAURENT, Florent Jouanny, Marc Mironneau, Paulyn Jovet #Produrable #RSE #DéveloppementDurable #Transformation #PerformanceDurable #Axys
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Jean-Baptiste Pringuey a aimé ceciJean-Baptiste Pringuey a aimé ceciI have come to the decision to retire from full-time work. I have enjoyed my career and have been blessed with meeting wonderful people. I also met challenging people, but other than a select few, I have been able to joyfully work with them. Over the years I have been blessed to be part of initial work for things that are really old nowadays. For instance, I was part of the team at Toronto-Dominion Bank in 1979 to implement the first ATM in Toronto. Now, these are everywhere, but in a cashless place now, they are only used to actually getting cash. I was also part of a project at Abbott Laboratories in Illinois where we created the first web site through the firewall, and also was part of the first email through the firewall, back in 1998. I was fortunate to be part of the first project to move Model N from being local to the client, to being online and remotely held by Model N (this is called Powered by N). I was part of the first set of Validata being implemented in Model N. All great experiences and I treasure them all. It is mainly the people I will remember, including you, who have been in contact with me over the years and have remained friends. Since the pandemic, I have worked from home only. I am still willing to help out part-time and remote for you friends if you need any short-term assistance. Until then, I am going to continue to enjoy my life and keep in touch with you all! I will still keep in touch personally with my friends. Have a wonderful Halloween, Thanksgiving, Christmas and New Year 2027! And thank you for being great people who I had the privilege of working with! Note - I will always call you “teammates” even if we are not working together! Bruce Wood
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Jean-Baptiste Pringuey a aimé ceciJean-Baptiste Pringuey a aimé ceciShoppers are already turning to ChatGPT to decide what to buy this holiday season. Is your Q4 strategy ready to meet them there? 🎁 Join us for a webinar with Stacey B. from OpenAI and our own Camille Lemercier and Michael Rasmussen to explore how shoppers are planning for the holidays and what six months of running ChatGPT Ads has taught us about what marketers need to do now to capture demand in AI-driven environments during Q4. 📅 Thursday, October 8 ⏰ 9 AM ET / 3 PM CET 🔗 Register now: https://lnkd.in/emTA_mcf
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Jean-Baptiste Pringuey a aimé ceciJean-Baptiste Pringuey a aimé ceciLundi, je vous parlais de clients pionniers. La marque Interparfums en fait partie : elle a testé la pub dès l'alpha lancée par Criteo, premier partenaire adtech d'OpenAI. Eux achetaient les annonces et Meikai regardait ce qu'elles changeaient dans les réponses. Et comment on mesure une pub dans ChatGPT ? On pose toujours les mêmes prompts et on regarde trois choses : la place de la marque dans la réponse, sa place dans l'encart sponsorisé et le doublon quand elle est aux deux endroits. Les deux additionnées, moins le doublon, ça donne la visibilité combinée. C'est ça, le vrai gain d'une campagne. Ce que j'aime dans cette méthode, c'est qu'elle relie les deux sujets qu'on travaille. Le GEO (Generative Engine Optimization), c'est votre visibilité organique, ce que votre marque gagne dans les réponses sans payer. Le GEA (Generative Engine Advertising), c'est la publicité dans ces mêmes IA. Quand on sait où votre marque est déjà citée, on sait où allouer le budget média pour lui apporter de la présence supplémentaire. Depuis fin août, les annonces sont ouvertes en Europe. Ce qu'on a fait aux US avec Interparfums, Inc., on peut maintenant le faire ici. Lien vers le case study en commentaire. #GEO #GEA #ChatGPT #Advertising #LLM Meikai Criteo Interparfums
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Jean-Baptiste Pringuey a aimé ceciGreat news for Meikai and strong recognition! More to come!Jean-Baptiste Pringuey a aimé ceciWe are proud to announce that Meikai has been selected as a finalist for the CMA CGM Startup Awards 2026. Out of hundreds of international applications, we are honored to be among the few startups recognized by CMA CGM Group and ZEBOX for our innovation in Next-Generation Media. This global competition highlights groundbreaking technologies shaping the future of shipping, logistics and media. On September 24, we will pitch our solution to CMA CGM Group’s top decision- makers during the AIM event in Marseille, stay tuned for the results! A huge thank you to the CMA CGM and ZEBOX teams for this opportunity to showcase our solution and connect with leading innovators from around the world. #CMACGMStartupAwards #ZEBOX #Innovation #TechForImpact #AI #Logisticsm #Shipping #Media Rachid Ait Addi Arnaud Kyriacos Mohamed OUADAH Lucas Reis Luca Aiello Marion Raith Christian Guinot Yannick Galatol Anthony Sendra Ben Sharpington Youssra E. Garti Jean-Baptiste Pringuey
Expérience et formation
Licences et certifications
Brevets
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ENHANCED MULTI-COMPONENT OBJECT-BASED DESIGN, COMPUTATION, AND EVALUATION
Émis le US 20190050777
In an example, a method comprises defining an object comprising a plurality of discrete components, each of which comprises a set of discrete formulas having a predefined order. The method initiates an evaluation of each discrete component by looping over each formula of that discrete component to produce a result set according to the predefined order by evaluating without specifying a dimensionality to produce the result set with a single row, or evaluating the formula with a specified…
In an example, a method comprises defining an object comprising a plurality of discrete components, each of which comprises a set of discrete formulas having a predefined order. The method initiates an evaluation of each discrete component by looping over each formula of that discrete component to produce a result set according to the predefined order by evaluating without specifying a dimensionality to produce the result set with a single row, or evaluating the formula with a specified dimensionality to produce the result set with a plurality of rows. The method displays a calculation user interface, determines that an action exists that is associated with at least one formula of at least one discrete component, displays a user-selectable element corresponding to the action, and automatically pauses computation of at least a portion of the evaluation until input selecting the user-selectable element is received.
Autres inventeursVoir le brevet -
ARCHITECTURES AND TECHNIQUES FOR RECORD PROTECTION AND FIELD MANAGEMENT
Émis le US 20170344353
Voir le brevetArchitectures and Techniques for Record Protection and Field Management. A software package having one or more custom metadata types is installed. The software package has computer-executable code that causes one or more processors to perform at least accessing the one or more custom metadata types. One or more protected records are accessed within the one or more custom metadata types. For the protected records, code in the installed package can read the protected records and can return the…
Architectures and Techniques for Record Protection and Field Management. A software package having one or more custom metadata types is installed. The software package has computer-executable code that causes one or more processors to perform at least accessing the one or more custom metadata types. One or more protected records are accessed within the one or more custom metadata types. For the protected records, code in the installed package can read the protected records and can return the records whether protected or not. If the custom metadata types are in a separate base package, code in the base package can also read the records. Returned information is stored in the one or more custom metadata records that has been accessed.
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ADVANCED SEARCHING OF RELATIONAL DATA VIA A MOBILE DEVICE
Émis le US 20160034526
A system, method and apparatus for providing for searching of relational data via a mobile communications device are provided. Information identifying searchable tables containing fields is received using a metadata application program interface (API). The metadata API provides information about a schema of the fields and a relationship of at least one of the fields to its corresponding object. Information for generating a view of relational data is provided to the mobile communications device.…
A system, method and apparatus for providing for searching of relational data via a mobile communications device are provided. Information identifying searchable tables containing fields is received using a metadata application program interface (API). The metadata API provides information about a schema of the fields and a relationship of at least one of the fields to its corresponding object. Information for generating a view of relational data is provided to the mobile communications device. The view is based on at least one of the fields of at least one of the searchable tables, and the relationship between the at least one of the fields and its corresponding object. A set of user inputs is received based on the relationship presented in the view. A query definition corresponding to the set of user inputs for searching the relational data in accordance with the set of user inputs is created and stored.
Autres inventeursVoir le brevet
Cours
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Admin 201
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Dev 401
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Facilitative consultant (http://www.leadstrat.com/)
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Project Management (7 keys)
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Projets
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Week end projects
Co-founder of multiple side projects : kaddoz.com and ayoudo.com which went from 0 to 10K monthly active users.
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Infinite Views salesforce1 - Hackathon
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Voir le projetSalesforce1 advanced search application part of a salesforce contest. I reached finals out of 100's of submissions.
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