[{"data":1,"prerenderedAt":621},["ShallowReactive",2],{"blog-nl-ma-tech-circle-paris":3,"blog-related-nl-ma-tech-circle-paris":197},{"id":4,"title":5,"author":6,"body":7,"coAuthors":180,"date":183,"description":184,"detail":185,"extension":186,"featured":185,"image":187,"imageSize":188,"meta":189,"navigation":190,"path":191,"railTitle":188,"seo":192,"stem":193,"summary":188,"tags":194,"unlisted":185,"updatedAt":188,"video":188,"__hash__":196},"blog\u002Fblog\u002Fen\u002Fma-tech-circle-paris.md","M&A Tech Circle Paris - June 2026","Pierre-Louis",{"type":8,"value":9,"toc":166},"minimark",[10,14,17,22,29,32,35,54,57,61,67,70,73,78,81,85,88,92,95,99,102,106,109,112,116,122,125,151,154,158],[11,12,13],"p",{},"On 3 June, at la maison.ai, we held the first edition of the M&A Tech Circle with Arx and Aesus Advisory. On the agenda: an ecosystem announcement, a concrete demonstration of deliverable automation, and cocktails to keep the conversation going.",[11,15,16],{},"The idea behind the M&A Tech Circle is to bring together M&A professionals who take AI seriously, to strengthen the ecosystem and explore how technology is transforming the profession through real cases and first-hand accounts. This first edition delivered on that promise, with two highlights.",[18,19,21],"h2",{"id":20},"entropia-arx-integration","Entropia × Arx integration",[11,23,24],{},[25,26],"img",{"alt":27,"src":28},"Julien Belon and Pierre-Louis on stage for the integration announcement","\u002Fblog\u002Fmatc-arx-stage.jpg",[11,30,31],{},"Arx's CRM module, connected to the M&A ecosystem, lets you manage deal tracking from sourcing through closing. But visibility stops the moment due diligence opens in the data room. And that is exactly where the seriousness of acquirers shows: the depth of analysis, by firm and by individual. The technical integration between Arx and Entropia closes that gap.",[11,33,34],{},"The integration, announced by Julien Belon (Arx) and Pierre-Louis (Entropia), will let Arx clients:",[36,37,38,47],"ul",{},[39,40,41,42,46],"li",{},"launch a data room, or a ",[43,44,45],"strong",{},"complimentary pre-data room",", in one click from Arx, keeping their Arx identity and passing users and groups across, with no double entry;",[39,48,49,50,53],{},"feed ",[43,51,52],{},"counterparty analytics"," tracked in the data room back into the CRM.",[11,55,56],{},"This integration is brought to you by the only two sovereign solutions, each in its own specialty (European companies, hosted on European cloud — Scaleway \u002F OVH), not only to give you better visibility on your deals, but also to strengthen the strategic independence of European M&A.",[18,58,60],{"id":59},"aesus-advisory-automating-ma-deliverables-for-real","Aesus Advisory: automating M&A deliverables, for real",[11,62,63],{},[25,64],{"alt":65,"src":66},"The demo projected on screen","\u002Fblog\u002Fmatc-aesus-stage.jpg",[11,68,69],{},"Gabriel d'Agay, founding partner of Aesus Advisory, walked through a real, anonymised case: a buy-side deal, the consolidation-led build-up of an accounting firm. The stack comes down to two pieces: the Entropia data room (notably its built-in agentic workflows and its MCP server enabling collaboration with Claude), connected to a Claude project equipped with instructions, in-house skills (graphic charter, acquisition terms, DD templates drawn from past deals) and files.",[11,71,72],{},"Five deliverables were produced, from pre-LOI analysis to Due Diligence preparation.",[74,75,77],"h3",{"id":76},"pre-loi-report","Pre-LOI report",[11,79,80],{},"From the data room (call notes, three years of accounts, budget, legal org chart, payroll data): a complete report with history, org chart, revenue breakdown, an EBITDA bridge from reported to adjusted, points of attention, and a valuation range aligned with the firm's house guidelines. Plus a ready-to-use Q&A.",[74,82,84],{"id":83},"financial-model","Financial model",[11,86,87],{},"P&L, balance sheet and cash flow over three years, an adjusted-EBITDA tab, a bridge, and a full LBO model: free cash flows, debt coverage, leverage.",[74,89,91],{"id":90},"letter-of-intent-loi","Letter of intent (LOI)",[11,93,94],{},"A complete document: scope, valuation, governance, purchase undertaking, liquidity, financing, warranties, exclusivity, signatories, down to the personal wealth dimension. The first version was corrected by hand (formatting, a request for a proper bridge), a useful reminder that the human stays in the loop to arbitrate and validate.",[74,96,98],{"id":97},"irl-checklist","IRL checklist",[11,100,101],{},"More advanced: an Entropia agentic workflow checks the data room's actual contents against the information requests sent, and flags what is missing. A check that used to be done by hand.",[74,103,105],{"id":104},"due-diligence-preparation-report","Due Diligence preparation report",[11,107,108],{},"Finally, a red flag report and Q&A preparation, again from the data room.",[11,110,111],{},"Across these demos, Gabriel walked through the setup in detail: how he assembled each of the skills used, the time it took to produce each deliverable, the importance of review and verification, and finally the impact on Aesus's productivity and its ability to raise the level of service it offers, especially to its small-cap clients.",[18,113,115],{"id":114},"cocktail","Cocktail",[11,117,118],{},[25,119],{"alt":120,"src":121},"Conversations over cocktails","\u002Fblog\u002Fmatc-ambient.jpg",[11,123,124],{},"The conversation carried on over cocktails with the banks and advisory firms present, all the richer for a room mixing MDs, AI taskforce leads and associates. Make or buy, productivity gains, sovereignty, opportunities for juniors: there was no shortage of topics.",[36,126,127,133,139,145],{},[39,128,129,132],{},[43,130,131],{},"Auditability."," Where it still breaks, and how to guarantee no error or omission.",[39,134,135,138],{},[43,136,137],{},"Productivity and quality."," How far quality can rise at constant fees.",[39,140,141,144],{},[43,142,143],{},"Maintenance and replicability."," The cost of maintaining the system and transposing it to a larger structure.",[39,146,147,150],{},[43,148,149],{},"Staffing."," What becomes of junior roles and how they learn the trade.",[11,152,153],{},"Thank you to the firms who joined us for this first edition:",[155,156],"matc-attendees",{"label":157},"In the room",[159,160],"matc-credits",{"cta-href":161,"cta-label":162,"cta-prefix":163,"entropia-href":164,"label":165},"\u002Fbook-a-demo","book a demo","To see Entropia on your case,","\u002F","Organized by",{"title":167,"searchDepth":168,"depth":168,"links":169},"",2,[170,171,179],{"id":20,"depth":168,"text":21},{"id":59,"depth":168,"text":60,"children":172},[173,175,176,177,178],{"id":76,"depth":174,"text":77},3,{"id":83,"depth":174,"text":84},{"id":90,"depth":174,"text":91},{"id":97,"depth":174,"text":98},{"id":104,"depth":174,"text":105},{"id":114,"depth":168,"text":115},[181,182],"Gabriel d'Agay","Julien Belon","2026-06-03","Entropia × Arx announcement, and Aesus Advisory demoing the production of a full chain of deliverables with the Entropia × Claude integration on a real deal.",false,"md","\u002Fblog\u002Fmatc-hero.png",null,{},true,"\u002Fblog\u002Fen\u002Fma-tech-circle-paris",{"title":5,"description":184},"blog\u002Fen\u002Fma-tech-circle-paris",[195],"insights","uCLrLOnTuV70Y1TSpWgk2tRTF3MaUcY5H3s7XCIlR8s",[198,295,564],{"id":199,"title":200,"author":201,"body":202,"coAuthors":280,"date":282,"description":283,"detail":185,"extension":186,"featured":190,"image":284,"imageSize":188,"meta":285,"navigation":190,"path":286,"railTitle":287,"seo":288,"stem":289,"summary":290,"tags":291,"unlisted":185,"updatedAt":188,"video":188,"__hash__":294},"blog\u002Fblog\u002Fen\u002Fentropia-jimini-partnership.md","Entropia connects the data room to Jimini AI","Pierre-Louis Corteel",{"type":8,"value":203,"toc":274},[204,215,219,222,226,229,233,241,245,248,258,266],[11,205,206,207,214],{},"We are pleased to partner with ",[208,209,213],"a",{"href":210,"rel":211},"https:\u002F\u002Fwww.jimini.ai",[212],"nofollow","Jimini AI",", the sovereign legal AI built for law firms and in-house legal teams. Legal professionals can now search, read, analyse or act on their Entropia data rooms directly from Jimini AI.",[18,216,218],{"id":217},"a-new-way-to-run-legal-due-diligence","A new way to run legal due diligence",[11,220,221],{},"Law firms, in-house legal teams and notaries working on M&A transactions spend days in the data room. Until now, to analyse a data room document in their legal AI, they had to download it from the data room first. With the Entropia connector, Jimini AI users can search and read the data room alongside the legal sources they already use in Jimini AI.",[18,223,225],{"id":224},"the-deal-documents-and-the-law-in-one-answer","The deal documents and the law, in one answer",[11,227,228],{},"In a single request, users can query the Entropia data room and legal sources together. They analyse contract clauses and check each one against the applicable law, with citations to the page in the data room and to the legal source. With the Analysis Grid, they apply the same questions to hundreds of data room contracts at once, each cell linked to the passage it came from.",[18,230,232],{"id":231},"entropia-tools-available-from-jimini-ai","Entropia tools, available from Jimini AI",[11,234,235,236,240],{},"The ",[208,237,239],{"href":238},"\u002Fresources\u002Fentropia-mcp-server","Entropia MCP server"," enables Jimini AI's Agent to browse the data room folders, run full-text searches, read documents and spreadsheets, and retrieve the questions and answers exchanged in Q&A threads. A clause to find, a seller's answer in the Q&A, a figure in a spreadsheet: legal teams simply ask Jimini AI.",[18,242,244],{"id":243},"under-the-rights-you-already-hold","Under the rights you already hold",[11,246,247],{},"Every request is initiated by a legal professional, scoped to their access rights in Entropia and logged under their name. Data room administrators decide which groups can use AI. Where the sell side allows it, the bidder's advisers work within their own permissions. Nothing reaches a counterparty from Jimini AI: a person reviews each drafted answer and sends it from Entropia. Both companies keep customer data under European control.",[249,250,251],"blockquote",{},[11,252,253,257],{},[254,255,256],"em",{},"\"Lawyers on a deal need the deal documents and the law side by side. Now they can work on both from the AI platform they have chosen,\""," said Pierre-Louis Corteel, CEO of Entropia.",[249,259,260],{},[11,261,262,265],{},[254,263,264],{},"\"Our ambition is to make Jimini AI the place where legal work gets done, seamlessly connected to the tools legal teams rely on. In M&A, that means bringing the data room directly into their workflow. With Entropia, lawyers can now manage the entire due diligence process within Jimini AI, from reviewing deal documents to drafting the final report. And as two European companies, we share a commitment to keeping sensitive deal data under European control,\""," said Raphaël Arroche, CEO of Jimini AI.",[11,267,268,269,273],{},"Discover Jimini AI at ",[208,270,272],{"href":210,"rel":271},[212],"jimini.ai",".",{"title":167,"searchDepth":168,"depth":168,"links":275},[276,277,278,279],{"id":217,"depth":168,"text":218},{"id":224,"depth":168,"text":225},{"id":231,"depth":168,"text":232},{"id":243,"depth":168,"text":244},[281],"Raphaël Arroche","2026-11-04","Legal teams can now search, read, analyse and act on their Entropia data rooms directly from Jimini AI, the sovereign legal AI.","\u002Fblog\u002Fjimini-partnership-cover.png",{},"\u002Fblog\u002Fen\u002Fentropia-jimini-partnership","Jimini AI partnership",{"title":200,"description":283},"blog\u002Fen\u002Fentropia-jimini-partnership","Legal teams can now search, read, analyse and act on their Entropia data rooms directly from Jimini AI.",[292,195,293],"solution","changelog","ZMbapJnn_5FTkBkQ6AGv1JLABeKfPZzMIMrcPHUS1cU",{"id":296,"title":297,"author":201,"body":298,"coAuthors":551,"date":554,"description":555,"detail":185,"extension":186,"featured":185,"image":556,"imageSize":188,"meta":557,"navigation":190,"path":558,"railTitle":188,"seo":559,"stem":560,"summary":561,"tags":562,"unlisted":185,"updatedAt":188,"video":188,"__hash__":563},"blog\u002Fblog\u002Fen\u002Fma-tech-circle-paris-september-2026.md","AI in M&A: lessons from Clipperton and Edmond de Rothschild",{"type":8,"value":299,"toc":537},[300,303,306,310,314,318,324,327,333,336,339,342,346,349,352,356,361,364,367,370,374,379,382,385,389,392,430,434,439,442,445,448,455,459,464,467,470,473,477,482,485,488,491,494,498,503,506,509,513,516,519,522,525,533],[11,301,302],{},"The M&A Tech Circle, hosted by Entropia, brings M&A professionals together every quarter to explore how technology is transforming the profession, through real cases and first-hand accounts.",[11,304,305],{},"Here is our recap of the Paris edition, held on 23 September 2026 at Entropia's offices.",[307,308],"blog-gallery",{":images":309},"[{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Froom-1.jpg\",\"alt\":\"The M&A Tech Circle room (1\u002F4)\",\"width\":2419,\"height\":3226},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Froom-2.jpg\",\"alt\":\"The M&A Tech Circle room (2\u002F4)\",\"width\":4898,\"height\":3265},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Froom-3.jpg\",\"alt\":\"The M&A Tech Circle room (3\u002F4)\",\"width\":3265,\"height\":4898},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Froom-4.jpg\",\"alt\":\"The M&A Tech Circle room (4\u002F4)\",\"width\":1348,\"height\":899}]",[311,312],"section-label",{"label":313},"Announcements",[18,315,317],{"id":316},"entropias-partnerships-with-claude-anthropic-rogo-and-model-ml","Entropia's partnerships with Claude (Anthropic), Rogo and Model ML",[11,319,320,321],{},"The evening opened with a look back at the partnerships Entropia recently signed with the leading AI platforms used by investment banks. Entropia was the first data room in the world with a native connector in Claude, Rogo and Model ML. M&A teams can connect Entropia to most AI platforms on the market: every one that supports MCP (Model Context Protocol). ",[208,322,323],{"href":238},"Learn more",[11,325,326],{},"It was also a chance to spell out Entropia's differentiation strategy. Some data room market leaders sell their own AI layer as a paid add-on and deliberately limit what their MCP server can do, when they have one at all. Yet their clients have already chosen their AI platform, built their skills on it and connected their sources. And even after paying for the add-on, they still lack essential tools, such as reading the full text of the documents in the data room.",[11,328,329,330],{},"Entropia sided with its clients: from their own AI platform, their teams work on the data room with far more complete tools, full document reading included, at no extra cost. ",[208,331,323],{"href":332},"\u002Fblog\u002Fmost-capable-data-room-mcp",[11,334,335],{},"Those capabilities make all the difference for teams that work with AI every day.",[11,337,338],{},"That is the case for the M&A teams at Edmond de Rothschild, who rolled out Rogo, and at Clipperton, who work with Claude. Manon Elbaz and Olivier Combaudou then took the stage to talk through both rollouts.",[311,340],{"label":341},"Panel",[18,343,345],{"id":344},"edmond-de-rothschild-x-clipperton","Edmond de Rothschild x Clipperton",[11,347,348],{},"Manon Elbaz, Chief of Staff at Edmond de Rothschild, and Olivier Combaudou, Partner at Clipperton, both lead the AI rollout at their bank. They came to share how it is going.",[307,350],{":images":351},"[{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fpanel-1.jpg\",\"alt\":\"The panel with Manon Elbaz and Olivier Combaudou (1\u002F5)\",\"width\":557,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fpanel-2.jpg\",\"alt\":\"The panel with Manon Elbaz and Olivier Combaudou (2\u002F5)\",\"width\":557,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fpanel-3.jpg\",\"alt\":\"The panel with Manon Elbaz and Olivier Combaudou (3\u002F5)\",\"width\":1254,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fpanel-4.jpg\",\"alt\":\"The panel with Manon Elbaz and Olivier Combaudou (4\u002F5)\",\"width\":618,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fpanel-5.jpg\",\"alt\":\"The panel with Manon Elbaz and Olivier Combaudou (5\u002F5)\",\"width\":624,\"height\":936}]",[74,353,355],{"id":354},"how-to-choose-an-ai-platform","How to choose an AI platform",[11,357,358],{},[254,359,360],{},"Choices that are anything but final.",[11,362,363],{},"Edmond de Rothschild uses Rogo, a platform specialised in financial analysis. Manon Elbaz detailed the criteria that tipped the balance. AI models move very fast, and Rogo lets teams switch from one to another without changing tools.",[11,365,366],{},"Clipperton built its own environment, with Claude as its main platform, and handles orchestration, connections and skills itself.",[11,368,369],{},"Both stressed that these choices are anything but final and may well change, because the bulk of the work does not lie in picking the platform. After all, if every bank works with the same tool, how do you stand out? For Clipperton, the first step was to write down its processes and its knowledge base.",[74,371,373],{"id":372},"rolling-out-ai-in-an-ma-team-what-takes-time","Rolling out AI in an M&A team: what takes time",[11,375,376],{},[254,377,378],{},"Structuring knowledge, making methods explicit, training the teams.",[11,380,381],{},"At Clipperton, the time went into the conditions of use more than into the technology. The biggest workstream is still the knowledge base: the partners wrote down methods, guidelines and processes that had never been formalised. That pushed them to think more explicitly about what makes them distinctive. The team also drafted a charter, and one rule sums up its spirit: \"The AI did it\" is never an excuse.",[11,383,384],{},"At Edmond de Rothschild, Manon Elbaz described a pilot phase in which the team is learning fast. The time goes into training, so people learn to use the tool and to challenge it, into defining the framework of use, into tracking usage and into working with internal \"champions\". Her goal is to measure how each person uses it, so that AI stays in the service of judgement. Usage varied widely at first. Today the whole team uses it, and real power users have emerged among the analysts. The challenge now is to make usage consistent.",[74,386,388],{"id":387},"the-ai-use-cases-that-work-in-investment-banking","The AI use cases that work in investment banking",[11,390,391],{},"On use cases, Manon Elbaz and Olivier Combaudou agreed on the essentials. Their teams already use AI every day across many use cases:",[36,393,394,400,406,412,418,424],{},[39,395,396,399],{},[43,397,398],{},"Sourcing and buyer identification",": quickly finding prospects, potential buyers and sector data.",[39,401,402,405],{},[43,403,404],{},"Sparring",": challenging an approach, exploring scenarios, finding angles nobody had thought of.",[39,407,408,411],{},[43,409,410],{},"Knowledge management",": building knowledge bases on specific topics. One example at Clipperton is comparables: building lists of multiples to use as benchmarks.",[39,413,414,417],{},[43,415,416],{},"First drafts",": bankers still write the final version of an investment thesis themselves, but save significant time on the first one.",[39,419,420,423],{},[43,421,422],{},"Checking",": spotting typos and inconsistencies between the sections of a document.",[39,425,426,429],{},[43,427,428],{},"Q&A",": preparing answers to buyers' questions. Olivier Combaudou walked through Clipperton's setup, the tools connected to Claude and the in-house skills, then the Q&A skill applied to a recent mandate. The whole team uses it.",[74,431,433],{"id":432},"what-banks-dont-want-to-automate","What banks don't want to automate",[11,435,436],{},[254,437,438],{},"You can ask AI to write an IM, but you shouldn't.",[11,440,441],{},"Both speakers draw the same line. Negotiations and direct exchanges with clients stay entirely human: the relationship, the nuance and reading what goes unsaid cannot be delegated.",[11,443,444],{},"As for automating key deliverables such as the IM, the tests have not been conclusive. Bankers get generic text, while the IM is one of the documents where a bank most wants to stand out. The variety of sources and formats also makes the AI's job harder.",[11,446,447],{},"Olivier Combaudou pointed to the difficulties that come with the nature of Clipperton's mandates, mostly with tech companies, where you price a vision more than an EBITDA multiple.",[11,449,450,451,273],{},"Automating deliverables is probably more within reach for mature companies in standardised markets, such as the accounting-firm build-up Aesus Advisory presented at ",[208,452,454],{"href":453},"\u002Fblog\u002Fma-tech-circle-paris","the previous edition of the M&A Tech Circle",[74,456,458],{"id":457},"how-to-measure-the-roi-of-ai-in-ma","How to measure the ROI of AI in M&A",[11,460,461],{},[254,462,463],{},"Ask a better question.",[11,465,466],{},"The ROI of AI is still hard to put a number on. You can get a rough idea by dividing the annual cost by the number of pitches and mandates. You can try to estimate the time saved per person and per grade, but a complete costed simulation is not realistic at this stage. The cost of AI is far from neutral and keeps rising, current prices probably don't reflect the real cost of these tools, and nobody knows what they will be in six or twelve months.",[11,468,469],{},"Above all, it isn't really the right question to ask for now. Nobody measured the ROI of the internet or of laptops overnight, but everyone saw the way people work change profoundly.",[11,471,472],{},"M&A processes will evolve and teams will work differently. Both speakers agreed that the best bankers will pull further ahead thanks to AI. The point is to raise the quality of deliverables, not so much productivity. The ROI will become clear over time.",[74,474,476],{"id":475},"will-ai-reduce-junior-hiring-in-investment-banking","Will AI reduce junior hiring in investment banking?",[11,478,479],{},[254,480,481],{},"No, but it changes what is expected of them.",[11,483,484],{},"The short answer: nothing points that way today. Neither bank has changed its hiring.",[11,486,487],{},"Edmond de Rothschild is still observing. For Manon Elbaz, even as AI lifts every level, interns must keep mastering the fundamentals on real cases: building a business plan, a DCF, a valuation, calculating a WACC. A junior who has never built a DCF by hand cannot challenge the AI, just as a manager must know how to do what their team does.",[11,489,490],{},"Clipperton is not cutting its hiring at all, but it is looking for slightly different profiles, and its expectations of juniors have risen markedly. Olivier Combaudou doesn't want \"prompt operators\" but analysts who can articulate a line of thought. He values new skills: in the past, a tedious task done well was enough, and the senior brought the thinking afterwards. Once that task can be automated, the bank expects the junior to deliver a first layer of added value.",[11,492,493],{},"The question is how to use AI to augment every member of the bank, not how to automate the interns' work. Comparing an analyst's productivity with a model's only holds for certain tasks. And a bank that hired fewer juniors would deprive itself of its future associates, managers and partners.",[74,495,497],{"id":496},"the-investment-bankers-job-in-ten-years","The investment banker's job in ten years",[11,499,500],{},[254,501,502],{},"The bank's added value doesn't change.",[11,504,505],{},"What is becoming a commodity is the exploration and analysis of large amounts of information: the first layer of market analysis, summaries of public data, data structuring. Differentiation will therefore come down to judgement, vision, the ability to ask the right questions and see what others miss, and knowledge of markets, sectors and players.",[11,507,508],{},"The job stays competitive: a client comes looking for the best deal and the right investor. An investment bank's deliverables are a means to that end, not the end itself. If part of the work becomes a commodity, the bank's added value doesn't change. Bankers will be able to spend more time advising, and the bank will be able to take more risks. Execution speeds up, but deciding what to do with it remains an in-house craft. And AI only works on part of a deal's raw material: the data, provided it is well organised!",[18,510,512],{"id":511},"cocktails","Cocktails",[11,514,515],{},"The conversations went on late into the evening, sparking many introductions and plenty of new projects.",[307,517],{":images":518},"[{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fcocktail-1.jpg\",\"alt\":\"Cocktails after the panel (1\u002F6)\",\"width\":1105,\"height\":737},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fcocktail-2.jpg\",\"alt\":\"Cocktails after the panel (2\u002F6)\",\"width\":557,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fcocktail-3.jpg\",\"alt\":\"Cocktails after the panel (3\u002F6)\",\"width\":557,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fcocktail-4.jpg\",\"alt\":\"Cocktails after the panel (4\u002F6)\",\"width\":557,\"height\":836},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fcocktail-5.jpg\",\"alt\":\"Cocktails after the panel (5\u002F6)\",\"width\":624,\"height\":936},{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fcocktail-6.jpg\",\"alt\":\"Cocktails after the panel (6\u002F6)\",\"width\":1348,\"height\":899}]",[18,520,157],{"id":521},"in-the-room",[11,523,524],{},"A big thank you to everyone who joined us:",[526,527,530],"callout",{"color":528,"icon":529},"neutral","i-lucide-users",[11,531,532],{},"2A Capital · ABN Amro · Adviso Partners · Amala Partners · Arcéane · Ardian · Atout Capital · BNP Paribas · Bucéphale Finance · CA CIB · Cambon Partners · Clipperton · D&A Corporate Finance · Edmond de Rothschild · Eight Advisory · EY M&A Advisory · EY Parthenon · Forvis Mazars · Fournel Advisory · Groupama · in Extenso · Indosuez CF · Inflection Point Technology Partners · Investec · Klutch Capital · Largillière Finance · Leuwen Euroland · M&A Advisor · Mansartis · Maupiti Partners · Mazarine Partners · MBA Capital · Priscus Finance · Raisers Partners · Rochefort & Associés · Rydge Conseil · Sanofi · Spayne Lindsay · Tevali Partners · TTS Group · Training You · Trialis · Windome Banking",[159,534],{":entropiaHeight":535,":partners":536,"entropiaHref":164,"label":165},"19","[{\"src\":\"\u002Fblog\u002Fmatc-202609\u002Fclipperton-logo-dark.png\",\"alt\":\"Clipperton\",\"href\":\"https:\u002F\u002Fwww.clipperton.net\u002F\",\"height\":14},{\"src\":\"\u002Fcustomers\u002Fedmond-de-rothschild.png\",\"alt\":\"Edmond de Rothschild\",\"href\":\"https:\u002F\u002Fwww.edmond-de-rothschild.com\u002F\",\"height\":56}]",{"title":167,"searchDepth":168,"depth":168,"links":538},[539,540,549,550],{"id":316,"depth":168,"text":317},{"id":344,"depth":168,"text":345,"children":541},[542,543,544,545,546,547,548],{"id":354,"depth":174,"text":355},{"id":372,"depth":174,"text":373},{"id":387,"depth":174,"text":388},{"id":432,"depth":174,"text":433},{"id":457,"depth":174,"text":458},{"id":475,"depth":174,"text":476},{"id":496,"depth":174,"text":497},{"id":511,"depth":168,"text":512},{"id":521,"depth":168,"text":157},[552,553],"Manon Elbaz","Olivier Combaudou","2026-09-23","Clipperton and Edmond de Rothschild on their AI rollouts: their setups, what works, what takes time. ROI, the impact on staffing, and where the job is heading.","\u002Fblog\u002Fma-tech-circle-paris-202609.png",{},"\u002Fblog\u002Fen\u002Fma-tech-circle-paris-september-2026",{"title":297,"description":555},"blog\u002Fen\u002Fma-tech-circle-paris-september-2026","Clipperton and Edmond de Rothschild on their AI rollouts in M&A.",[195],"zt0P3BZtR3s6mzIU4VCukGs4nwFjha6syVSRNrrog3U",{"id":565,"title":566,"author":6,"body":567,"coAuthors":608,"date":610,"description":611,"detail":185,"extension":186,"featured":190,"image":612,"imageSize":188,"meta":613,"navigation":190,"path":614,"railTitle":615,"seo":616,"stem":617,"summary":618,"tags":619,"unlisted":185,"updatedAt":188,"video":188,"__hash__":620},"blog\u002Fblog\u002Fen\u002Fentropia-model-ml-partnership.md","Entropia's Partnership with Model ML",{"type":8,"value":568,"toc":606},[569,579,582,589,592,595,603],[11,570,571,572,578],{},"We are pleased to announce a partnership with ",[208,573,577],{"href":574,"rel":575,"target":576},"https:\u002F\u002Fmodelml.com",[212],"_blank","Model ML",", the agentic operating system for financial services, used by some of the world's largest banks, asset managers and advisory firms.",[11,580,581],{},"Model ML builds custom and off-the-shelf agents which create, review and verify complex, document-heavy workflows for global investment banks, private equity houses, consulting firms and other major financial institutions.",[11,583,584,585,588],{},"Entropia was designed to support M&A professionals with AI, and that design extends beyond our own walls. A user connected from Model ML gets ",[208,586,587],{"href":238},"the same tools"," as Entropia's own AI, at the same depth.",[11,590,591],{},"Bankers working in Model ML can reach their Entropia data rooms without leaving it. From Model ML, a banker can search the data room, read documents, presentations and spreadsheets page by page, browse the folder structure, follow Q&A threads, check who has access to what, and act: create folders, tag documents, set permissions, draft Q&A answers that a human reviews and sends.",[11,593,594],{},"Each request is initiated by the user, scoped to the access rights they already hold, and logged in the data room audit trail under their name. Nothing reaches a Model ML user that they could not open in Entropia directly, and nothing reaches a counterparty from Model ML: a drafted answer is reviewed and sent by a human in Entropia, and the access of an active group in the data room cannot be changed from outside it.",[249,596,597],{},[11,598,599,602],{},[254,600,601],{},"\"Our partnership with Entropia is a meaningful addition to the Model ML platform for our M&A users. Access to Entropia's agentic data rooms directly in the Model ML platform means that our users can harness the full power of Entropia's agent-native platform without disrupting their existing workflows,\""," said Chaz Englander, CEO at Model ML.",[11,604,605],{},"The integration is available to joint customers with active Entropia data rooms, starting today.",{"title":167,"searchDepth":168,"depth":168,"links":607},[],[609],"Chaz Englander","2026-09-10","Bankers working in Model ML can now search, read and act on their live Entropia data rooms without leaving the platform, under their own access rights.","\u002Fblog\u002Fmodel-ml-partnership-cover.png",{},"\u002Fblog\u002Fen\u002Fentropia-model-ml-partnership","Model ML partnership",{"title":566,"description":611},"blog\u002Fen\u002Fentropia-model-ml-partnership","Bankers working in Model ML can now reach their live Entropia data rooms without leaving the platform.",[292,195,293],"RrYTYx7Q0M0_Gs5IBSEzgqXbk-fckPrjcrUqIT3yuA8",1794484474920]