The O.D.E.S.S.A. Framework is a proprietary methodology developed by Saverio Canepa Advisory to structurally integrate artificial intelligence into Mergers & Acquisitions processes. The name is acronym of the six operational layers composing a complete M&A operation on which AI today can generate differential value: Origination, Due Diligence, Evaluation, Strategy, Stakeholder, Audit. It was presented publicly in 2026 with a dedicated article and represents one of the first Italian methodologies in which AI is operationally integrated into M&A processes rather than used as generic support tool.
Origination — the first layer — addresses the buyer and seller scouting problem. AI accelerates buyer universe mapping through massive parsing of transactional databases (Mergermarket, Pitchbook, Dealflower, Reuters), identification of sectoral consolidation patterns not yet visible to public data, predictive analysis of potential buyers based on acquisitive track record, financial capacity, and declared strategic thesis. For a sell-side mandate, where a traditional advisor maps 50-80 buyers in 4-6 weeks, AI integration allows bringing mapping to 150-250 names in 2-3 weeks with superior prioritization quality.
Due Diligence — the second layer — is where AI has the most tangible and immediate impact. Document analysis of a VDR (Virtual Data Room) for a mid-market deal typically comprises 800-2,500 documents between commercial contracts, detailed financial statements, legal disputes, patents, certifications. With AI specialized in contract review and document intelligence, first-pass times reduce from classic 4-6 weeks to 7-12 days, and identification quality of problematic clauses, contractual anomalies, hidden exposures is quantitatively superior to junior human work. The senior advisor maintains final decision but operates on a radically richer analytical base.
Evaluation — the third layer — applies AI to financial modeling and scenario simulation. Multi-variable sensitivity analysis, Monte Carlo simulation on 10,000+ scenarios, automatic identification of critical assumptions in DCF: all operations that required days of analyst work and are now automated. AI added value is not replacing the senior’s valuation — which remains based on strategic judgment — but increasing robustness of the proposed number through systematic stress tests.
Strategy — the fourth layer — is where AI supports building the strategic case toward buyers. Generation of synergy scenarios personalized for specific acquirers (based on analysis of their operational structure and public P&L), simulation of post-merger integration roadmap, predictive calculation of time-to-value of synergies. For the seller, this translates into a much more persuasive and personalized information memorandum toward short-list top buyers.
Stakeholder — the fifth layer — manages massive and personalized communication toward multiple buyers during a competitive process. When an advisor simultaneously manages 8-12 active buyers in due diligence phase, each with specific questions and different timelines, AI accelerates preparation of coherent responses, maintains traceability of information disclosed to whom, identifies buyers cooling their interest before they become explicitly disengaged.
Audit — the sixth and final layer — is the qualitative factor: automatic log of every decision taken in the process, audit trail for compliance, generation of detailed reporting for the seller’s board. It is the least glamorous layer but the one allowing the deal to withstand post-closing disputes — increasingly relevant in an Italian regulatory context where union and selling director responsibility is increasing.
