[{"data":1,"prerenderedAt":609},["ShallowReactive",2],{"blog-en-ma-tech-circle-paris-september-2026":3,"blog-related-en-ma-tech-circle-paris-september-2026":295},{"id":4,"title":5,"author":6,"body":7,"coAuthors":278,"date":281,"description":282,"detail":283,"extension":284,"featured":283,"image":285,"imageSize":286,"meta":287,"navigation":288,"path":289,"railTitle":286,"seo":290,"stem":291,"summary":286,"tags":292,"unlisted":283,"updatedAt":286,"video":286,"videoWebm":283,"__hash__":294},"blog\u002Fblog\u002Fen\u002Fma-tech-circle-paris-september-2026.md","AI in M&A: lessons from Clipperton and Edmond de Rothschild","Pierre-Louis Corteel",{"type":8,"value":9,"toc":261},"minimark",[10,14,17,21,25,30,38,41,47,50,53,56,60,63,66,71,77,80,83,86,90,95,98,101,105,108,149,153,158,161,164,167,175,179,184,187,190,193,197,202,205,208,211,214,218,223,226,229,233,236,239,243,246,254],[11,12,13],"p",{},"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.",[11,15,16],{},"Here is our recap of the Paris edition, held on 23 September 2026 at Entropia's offices.",[18,19],"blog-gallery",{":images":20},"[{\"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}]",[22,23],"section-label",{"label":24},"Announcements",[26,27,29],"h2",{"id":28},"entropias-partnerships-with-claude-anthropic-rogo-and-model-ml","Entropia's partnerships with Claude (Anthropic), Rogo and Model ML",[11,31,32,33],{},"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). ",[34,35,37],"a",{"href":36},"\u002Fresources\u002Fentropia-mcp-server","Learn more",[11,39,40],{},"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.",[11,42,43,44],{},"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. ",[34,45,37],{"href":46},"\u002Fblog\u002Fmost-capable-data-room-mcp",[11,48,49],{},"Those capabilities make all the difference for teams that work with AI every day.",[11,51,52],{},"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.",[22,54],{"label":55},"Panel",[26,57,59],{"id":58},"edmond-de-rothschild-x-clipperton","Edmond de Rothschild x Clipperton",[11,61,62],{},"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.",[18,64],{":images":65},"[{\"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}]",[67,68,70],"h3",{"id":69},"how-to-choose-an-ai-platform","How to choose an AI platform",[11,72,73],{},[74,75,76],"em",{},"Choices that are anything but final.",[11,78,79],{},"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.",[11,81,82],{},"Clipperton built its own environment, with Claude as its main platform, and handles orchestration, connections and skills itself.",[11,84,85],{},"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.",[67,87,89],{"id":88},"rolling-out-ai-in-an-ma-team-what-takes-time","Rolling out AI in an M&A team: what takes time",[11,91,92],{},[74,93,94],{},"Structuring knowledge, making methods explicit, training the teams.",[11,96,97],{},"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.",[11,99,100],{},"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.",[67,102,104],{"id":103},"the-ai-use-cases-that-work-in-investment-banking","The AI use cases that work in investment banking",[11,106,107],{},"On use cases, Manon Elbaz and Olivier Combaudou agreed on the essentials. Their teams already use AI every day across many use cases:",[109,110,111,119,125,131,137,143],"ul",{},[112,113,114,118],"li",{},[115,116,117],"strong",{},"Sourcing and buyer identification",": quickly finding prospects, potential buyers and sector data.",[112,120,121,124],{},[115,122,123],{},"Sparring",": challenging an approach, exploring scenarios, finding angles nobody had thought of.",[112,126,127,130],{},[115,128,129],{},"Knowledge management",": building knowledge bases on specific topics. One example at Clipperton is comparables: building lists of multiples to use as benchmarks.",[112,132,133,136],{},[115,134,135],{},"First drafts",": bankers still write the final version of an investment thesis themselves, but save significant time on the first one.",[112,138,139,142],{},[115,140,141],{},"Checking",": spotting typos and inconsistencies between the sections of a document.",[112,144,145,148],{},[115,146,147],{},"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.",[67,150,152],{"id":151},"what-banks-dont-want-to-automate","What banks don't want to automate",[11,154,155],{},[74,156,157],{},"You can ask AI to write an IM, but you shouldn't.",[11,159,160],{},"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.",[11,162,163],{},"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.",[11,165,166],{},"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.",[11,168,169,170,174],{},"Automating deliverables is probably more within reach for mature companies in standardised markets, such as the accounting-firm build-up Aesus Advisory presented at ",[34,171,173],{"href":172},"\u002Fblog\u002Fma-tech-circle-paris","the previous edition of the M&A Tech Circle",".",[67,176,178],{"id":177},"how-to-measure-the-roi-of-ai-in-ma","How to measure the ROI of AI in M&A",[11,180,181],{},[74,182,183],{},"Ask a better question.",[11,185,186],{},"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.",[11,188,189],{},"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.",[11,191,192],{},"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.",[67,194,196],{"id":195},"will-ai-reduce-junior-hiring-in-investment-banking","Will AI reduce junior hiring in investment banking?",[11,198,199],{},[74,200,201],{},"No, but it changes what is expected of them.",[11,203,204],{},"The short answer: nothing points that way today. Neither bank has changed its hiring.",[11,206,207],{},"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.",[11,209,210],{},"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.",[11,212,213],{},"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.",[67,215,217],{"id":216},"the-investment-bankers-job-in-ten-years","The investment banker's job in ten years",[11,219,220],{},[74,221,222],{},"The bank's added value doesn't change.",[11,224,225],{},"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.",[11,227,228],{},"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!",[26,230,232],{"id":231},"cocktails","Cocktails",[11,234,235],{},"The conversations went on late into the evening, sparking many introductions and plenty of new projects.",[18,237],{":images":238},"[{\"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}]",[26,240,242],{"id":241},"in-the-room","In the room",[11,244,245],{},"A big thank you to everyone who joined us:",[247,248,251],"callout",{"color":249,"icon":250},"neutral","i-lucide-users",[11,252,253],{},"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",[255,256],"matc-credits",{":entropiaHeight":257,":partners":258,"entropiaHref":259,"label":260},"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}]","\u002F","Organized by",{"title":262,"searchDepth":263,"depth":263,"links":264},"",2,[265,266,276,277],{"id":28,"depth":263,"text":29},{"id":58,"depth":263,"text":59,"children":267},[268,270,271,272,273,274,275],{"id":69,"depth":269,"text":70},3,{"id":88,"depth":269,"text":89},{"id":103,"depth":269,"text":104},{"id":151,"depth":269,"text":152},{"id":177,"depth":269,"text":178},{"id":195,"depth":269,"text":196},{"id":216,"depth":269,"text":217},{"id":231,"depth":263,"text":232},{"id":241,"depth":263,"text":242},[279,280],"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.",false,"md","\u002Fblog\u002Fma-tech-circle-paris-202609.png",null,{},true,"\u002Fblog\u002Fen\u002Fma-tech-circle-paris-september-2026",{"title":5,"description":282},"blog\u002Fen\u002Fma-tech-circle-paris-september-2026",[293],"insights","yai296bp24vD8FZo8-mALt7dyEGNL5pZNUpVbM6uQ1Y",[296,358,534],{"id":297,"title":298,"author":299,"body":300,"coAuthors":343,"date":345,"description":346,"detail":283,"extension":284,"featured":288,"image":347,"imageSize":286,"meta":348,"navigation":288,"path":349,"railTitle":350,"seo":351,"stem":352,"summary":353,"tags":354,"unlisted":283,"updatedAt":286,"video":286,"videoWebm":283,"__hash__":357},"blog\u002Fblog\u002Fen\u002Fentropia-model-ml-partnership.md","Entropia's Partnership with Model ML","Pierre-Louis",{"type":8,"value":301,"toc":341},[302,313,316,323,326,329,338],[11,303,304,305,312],{},"We are pleased to announce a partnership with ",[34,306,311],{"href":307,"rel":308,"target":310},"https:\u002F\u002Fmodelml.com",[309],"nofollow","_blank","Model ML",", the agentic operating system for financial services, used by some of the world's largest banks, asset managers and advisory firms.",[11,314,315],{},"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.",[11,317,318,319,322],{},"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 ",[34,320,321],{"href":36},"the same tools"," as Entropia's own AI, at the same depth.",[11,324,325],{},"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.",[11,327,328],{},"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.",[330,331,332],"blockquote",{},[11,333,334,337],{},[74,335,336],{},"\"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.",[11,339,340],{},"The integration is available to joint customers with active Entropia data rooms, starting today.",{"title":262,"searchDepth":263,"depth":263,"links":342},[],[344],"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":298,"description":346},"blog\u002Fen\u002Fentropia-model-ml-partnership","Bankers working in Model ML can now reach their live Entropia data rooms without leaving the platform.",[355,293,356],"solution","changelog","kK2K-94dhw-zgjseKWuJZTpyWx8Opweq-b7x5ozqIYM",{"id":359,"title":360,"author":299,"body":361,"coAuthors":286,"date":524,"description":525,"detail":283,"extension":284,"featured":283,"image":526,"imageSize":286,"meta":527,"navigation":288,"path":528,"railTitle":286,"seo":529,"stem":530,"summary":286,"tags":531,"unlisted":283,"updatedAt":532,"video":286,"videoWebm":283,"__hash__":533},"blog\u002Fblog\u002Fen\u002Fmost-capable-data-room-mcp.md","The data room built for teams who work with AI",{"type":8,"value":362,"toc":518},[363,367,381,388,391,395,398,401,404,407,410,413,417,425,428,467,470,473,489,493,508,511],[26,364,366],{"id":365},"ma-teams-increasingly-work-from-ai-platforms","M&A teams increasingly work from AI platforms",[11,368,369,370,375,376,380],{},"M&A professionals are no longer using AI to tidy up emails. They use AI to do the work: build the EBITDA bridge, draft the LOI, prepare the red flag report, assemble the Q&A. ",[34,371,374],{"href":372,"target":310,"rel":373},"https:\u002F\u002Fwww.economist.com\u002Fbusiness\u002F2026\u002F08\u002F30\u002Fwill-anybody-use-ai-as-much-as-coders-do",[309],"The Economist"," (\"Will anybody use AI as much as coders do?\", 30 August 2026) names finance as one of the three candidates to follow software engineering as a runaway application, and notes that Rogo added a hundred enterprise customers in a quarter while growing recurring revenue by 50%. (read our ",[34,377,379],{"href":378,"target":310},"\u002Fblog\u002Fentropia-rogo-partnership","partnership announcement",")",[11,382,383,384,387],{},"We see the same thing inside deals. At a recent ",[34,385,386],{"href":172,"target":310},"M&A Tech Circle"," in Paris, Gabriel d'Agay of Aesus Advisory demoed five deliverables from a live buy-side build-up, from pre-LOI analysis to due diligence preparation, all produced from an AI platform connected to our data room. Our own number: on 40% of Entropia data rooms, admins have connected their AI platform over MCP, the Model Context Protocol, the open standard that lets an AI platform call another software's tools directly.",[11,389,390],{},"This changes the test for every vendor in the M&A stack. Software is now judged on how it behaves inside a chat window. Deal teams ask whether a tool connects to their platform before they ask what its interface looks like. And the real question becomes how well it connects.",[26,392,394],{"id":393},"the-deal-information-should-be-accessible","The deal information should be accessible",[11,396,397],{},"The pre-LOI report from the Aesus demonstration drew on three years of accounts, a budget, a legal org chart and payroll data, all in the data room. It also drew on call notes, the firm's valuation guidelines, its due diligence templates and its graphic charter. None of that belongs in a data room. Widen the frame and the list grows: sector reports, comparables, VDD reports, management meeting transcripts.",[11,399,400],{},"Two consequences.",[11,402,403],{},"A data room's own AI cannot produce M&A deliverables alone, however good it is, because it only sees the data room. We build agentic workflows inside Entropia and we are confident in them. They still only know what is in the data room.",[11,405,406],{},"A bank's AI platform cannot produce it either if the data room gives it a narrow pipe. The platform can hold the firm's precedents, skills, templates and transcripts and still fail on a change of control clause analysis because it cannot search the data room properly, or cannot read past the first page of a contract, or cannot see the Q&A, etc.",[11,408,409],{},"That is the state of the VDR market. Most data rooms expose no MCP server at all. Among the few that do, including the largest names, the tools are thinner than what the same vendor keeps for the AI layer it sells separately: partial reads, weak or absent search, no write, no source display, no Q&A, no audit. Sometimes that is because their teams are technically limited. But more structurally, it is often a commercial decision: a vendor charging a licence fee for its own AI has no reason to let a competing AI do the job properly.",[11,411,412],{},"Deal teams tell us in private that the in-house AI those licences pay for is not the one they want. They have chosen their platform, built skills in it and put the firm's knowledge next to it. Being asked to leave it, and to pay for the privilege, is a poor trade.",[26,414,416],{"id":415},"the-best-of-both-worlds","The best of both worlds",[11,418,419,420,424],{},"Entropia has another strategy. A \"focused on the user\" strategy. The ",[34,421,423],{"href":422,"target":310},"\u002Fresources\u002Fentropia-mcp-server#tools","tools"," our own AI uses inside the data room are the tools your AI platform gets, at the same depth, with nothing held back for a paid tier.",[11,426,427],{},"The details matter for your teams to be able to work properly:",[109,429,430,440,446,455,461],{},[112,431,432,435,436,439],{},[115,433,434],{},"Reading."," Page-range reads across PDFs, Word documents, slide decks and images, so an agent works through a two-hundred-page agreement in sections. Spreadsheets read sheet by sheet as tables. A document opens at a given page inside the conversation, with the cited passage highlighted, so the reviewer checks the source rather than a transcription of it.",[437,438],"br",{},"Every read comes back marked readable, unreadable or redacted, and only the first may be reported as what the document says. An agent that cannot read a file is told so in terms it cannot paper over. That is the difference between a tool a deal team can rely on and one that writes confident prose about a page it never saw.",[112,441,442,445],{},[115,443,444],{},"Searching."," Full-text search across the entire data room with fuzzy matching, returning path, page number and excerpt. A reference like 1.2.3 resolves to the actual file, so analyst and agent talk about the same document in the same terms.",[112,447,448,451,452,454],{},[115,449,450],{},"Q&A, in full."," The Q&A is where a deal team spends its evenings, and it is usually the first thing a connector drops. Ours exposes the whole workflow: a search index over threads (stream, author, question number, message content), each conversation in order with roles and authors, the counterparty group behind each stream, and the ability to compose a proposed answer.",[437,453],{},"On that last tool, precision matters. The proposed wording lands as an editable draft in the reply composer of the answering side. The asking side never sees it. The tool cannot post or publish. A human reads, edits and sends in the application, and no configuration skips that step.",[112,456,457,460],{},[115,458,459],{},"Writing, narrowly and reversibly."," Reorganise the index, tag documents, compose a group's access before inviting it. Sending to the bin is reversible. Write access is opt-in per connection, and your AI client can allow, block or require confirmation on each tool separately.",[112,462,463,466],{},[115,464,465],{},"Access and activity."," Read the effective permission matrix over a folder subtree, including descendants whose access differs from their parent. Diff two counterparty groups to see what each can reach that the other cannot, with exact counts. Aggregate over the audit log by date range, event family, group, role, user or free text, to see who read what and what nobody opened.",[11,468,469],{},"This works from both sides of the deal. A sell-side adviser runs the data room from their platform. If allowed, a bidder analyses the data room from its own platform, inside its own permissions, seeing exactly what it was given access to. The server only lists the data rooms where the user's group has been granted AI access, which each data room's administrators control.",[11,471,472],{},"Every MCP tool call executes with the rights of the person who authorised the connection, never beyond them, and is recorded in the audit log under their name like any other action. A seller buys a data room to control and prove disclosure. An AI connection that weakened that guarantee would defeat the product. Ours strengthens the record: an agent's every read lands in the same log as a human's.",[11,474,475,476,480,481,484,485,488],{},"Entropia has a native connector in ",[34,477,479],{"href":478,"target":310},"\u002Fblog\u002Fclaude-mcp-directory","Claude",", ",[34,482,483],{"href":378,"target":310},"Rogo",", Model ML and ",[34,486,487],{"href":36,"target":310},"others",". Connecting your AI platform to your Entropia data room costs nothing on top of your subscription.",[26,490,492],{"id":491},"four-questions-for-your-current-provider","Four questions for your current provider",[494,495,496,499,502,505],"ol",{},[112,497,498],{},"Does it expose an MCP server at all?",[112,500,501],{},"If it does, can the connection read a whole document, search the entire data room, work the Q&A, and show the audit trail? Read tools only, or write and display too?",[112,503,504],{},"Is the deepest tooling available to your AI platform, or reserved for the AI layer they want to sell you?",[112,506,507],{},"What does the connection cost?",[11,509,510],{},"The answers sort providers into two groups. Only one is helping you work where you already work.",[11,512,513,517],{},[34,514,516],{"href":515,"target":310},"\u002Fbook-a-demo","Book a demo"," and we will connect your AI platform to a live Entropia data room, with your team in control.",{"title":262,"searchDepth":263,"depth":263,"links":519},[520,521,522,523],{"id":365,"depth":263,"text":366},{"id":393,"depth":263,"text":394},{"id":415,"depth":263,"text":416},{"id":491,"depth":263,"text":492},"2026-09-02","M&A teams increasingly run their deals from their own AI platforms. Entropia gives those platforms the most advanced toolset in the market: the same tools our own AI uses, at the same depth, at no extra cost.","\u002FMCP\u002Fmcp-vignette-with-logos.jpg",{},"\u002Fblog\u002Fen\u002Fmost-capable-data-room-mcp",{"title":360,"description":525},"blog\u002Fen\u002Fmost-capable-data-room-mcp",[293],"2026-09-03","62NtUbusxeTRzkl_TMYV-AZaAeMRvDBcNAEYxLkA7Bc",{"id":535,"title":536,"author":6,"body":537,"coAuthors":286,"date":598,"description":599,"detail":283,"extension":284,"featured":288,"image":600,"imageSize":286,"meta":601,"navigation":288,"path":602,"railTitle":603,"seo":604,"stem":605,"summary":606,"tags":607,"unlisted":283,"updatedAt":286,"video":286,"videoWebm":283,"__hash__":608},"blog\u002Fblog\u002Fen\u002Fentropia-arx-partnership.md","Entropia x Arx: the deal pipeline and the data room, connected",{"type":8,"value":538,"toc":592},[539,542,545,559,563,566,570,573,577,580,584,587],[11,540,541],{},"A deal never lives in one tool. It starts in the CRM, where the banker tracks the mandate, the buyer list and the state of the relationship. It plays out in the data room, where the documents, the permissions and the Q&A live.",[11,543,544],{},"Between those two places, most teams work by hand. The buyer list gets retyped. The NDA is signed, someone remembers to grant access two days later.",[11,546,547,548,553,554,558],{},"We worked with the ",[34,549,552],{"href":550,"rel":551},"https:\u002F\u002Farx.deals",[309],"Arx"," team to close that gap. The integration between Arx, the CRM built for M&A advisors, and Entropia, our ",[34,555,557],{"href":556},"\u002Fproduct","data room",", is live.",[26,560,562],{"id":561},"create-the-pre-data-room-or-the-data-room-from-the-crm","Create the pre-data room or the data room from the CRM",[11,564,565],{},"From the opportunity in Arx, the team opens a pre-data room, complimentary, and starts collecting documents while the deal is still taking shape. No setup call. Once the mandate is signed, they switch to the full data room.",[26,567,569],{"id":568},"sign-in-with-your-arx-credentials","Sign in with your Arx credentials",[11,571,572],{},"Your Arx login opens Entropia. No second account to create, no extra password to manage across the team.",[26,574,576],{"id":575},"activity-comes-back-into-the-crm","Activity comes back into the CRM",[11,578,579],{},"Buyer engagement in the data room is visible from Arx as the deal runs. The banker reads it in the same place they track the rest of their pipeline, and the history stays attached to the counterparty for the mandates that follow.",[26,581,583],{"id":582},"getting-started","Getting started",[11,585,586],{},"If your firm already uses Arx and Entropia, the connection is made from Arx, by the data room administrator. It takes a few minutes and applies to the deals you choose.",[11,588,589,591],{},[34,590,516],{"href":515}," to see the integration running on your own deals.",{"title":262,"searchDepth":263,"depth":263,"links":593},[594,595,596,597],{"id":561,"depth":263,"text":562},{"id":568,"depth":263,"text":569},{"id":575,"depth":263,"text":576},{"id":582,"depth":263,"text":583},"2026-08-28","Open a pre-data room or a full data room from Arx, sign in with your Arx credentials, and read buyer engagement back in the CRM.","\u002Fblog\u002Farx-entropia-2.png",{},"\u002Fblog\u002Fen\u002Fentropia-arx-partnership","Arx integration",{"title":536,"description":599},"blog\u002Fen\u002Fentropia-arx-partnership","The integration between Arx and Entropia is live: open a data room from the CRM, sign in with your Arx credentials, and follow buyer engagement in Arx.",[355,293,356],"ff9iziM9fM0iqK7jqnW6GeMFVDFwNCIREl876E_4-CA",1793087452029]