Exhibit 99.3

PROPOSED BUSINESS COMBINATION Nano Dimension + Infinite Epigenetics Forming a publicly traded AI - powered company to redefine how chronic disease is predicted, detected and prevented with epigenetics. 01

DISCLAIMER Forward - looking statements & disclaimer. Forward Looking Statements Additional Information and Where to Find It Participants in the Solicitation 02

Contents 19 Healthcare Provider Market Opportunity 20 Additional Market Opportunities 21 Commercial Applications 22 Market Precedents 23 The Infinite Portfolio 24 Leadership 25 Our Partners 27 Our Investors 28 Key Takeaways 30 Reference Glossary 04 Transaction Overview 07 What This Creates 09 The Problem 11 Infinite Epigenetics Overview 12 Why Now 14 How The Test Works 15 Our Proprietary Model 16 Our Data Flywheel 17 The Market Size 18 Performance vs. Existing Diagnostics 03

NANO DIMENSION BRINGS Strong capital base and Nasdaq listing A Nasdaq listing, a strong capital base, and the strategic flexibility to fund growth. + INFINITE EPIGENETICS BRINGS A revenue - generating, biological AI platform A vast, proprietary biological dataset, deep IP, and biological AI foundation model. = THE COMBINED COMPANY Infinite Epigenetics, on Nasdaq A focused public company at the intersection of AI, epigenetics, and diagnostics. New ticker: IEAI The proposed transaction marks the culmination of Phase 3 of Nano Dimension's previously announced three - phase strategic plan, d eveloped to maximize long - term shareholder value. Epigenetics: the control layer switching genes on/off, shifting with age, diet & disease · Foundation model: broadly - trained AI adaptable to many specific tasks 04 TRANSACTION OVERVIEW Deploying capital into a high - growth healthcare AI AI opportunity.

TRANSACTION OVERVIEW Summary of potential opportunities review. review. 05 Nano Dimension engaged Guggenheim Securities, LLC (“Guggenheim”) and Houlihan Lokey (“Houlihan”) to support the Nano Dimension’s Board of Directors in conducting a thorough and disciplined evaluation of a comprehensive range of strategic alternatives with the objective of maximizing shareholder value, including a review of its product lines, core technologies, market dynamics and competitive positioning. Guggenheim supported Nano Dimension in evaluating and executing opportunities to monetize its product lines. Houlihan supported Nano Dimension in evaluating a focused set of alternatives with respect to the Nano Dimension’s financial resources and public company platform. Possible alternatives included, a strategic merger, a reverse merger, or other strategic transactions intended to maximize shareholder value in 2026 and beyond. Nano Dimension identified multiple potential counterparties and actively engaged in discussions under a range of potential transaction structures. During the process, approximately 20 companies responded, 14 companies submitted indications of interest, of which several were interviewed, six face - to - face company meetings were conducted, and a smaller group of four companies were included in the short list of preferred companies in the process. Nano Dimension has conducted due diligence on Infinite with the assistance of multiple consultants in the healthcare space. The Nano Dimension Board of Directors approved the Infinite transaction term sheet.

TRANSACTION OVERVIEW Summary of key terms. terms. 06 Signed Term Sheet: June 15, 2026 Definitive Agreement expected to be executed before July 31, 2026 The combined company is expected to operate under the Infinite Epigenetics name and continue trading on the Nasdaq Capital Market under the proposed ticker symbol “IEAI” Key Terms: Stock - for - stock merger valuing Infinite Epigenetics at $875 million Exchange ratio determined based on the stated value for Nano Dimension shares that reflects a 20% premium to Nano Dimension’s estimated net cash at closing Existing Nano Dimension shareholders expected to retain meaningful minority ownership in the combined company Management and Board of Directors Composition: Matt Dawson, current CEO of Infinite, will lead the combined company as CEO Following the closing, the combined company Board of Directors would consist of seven members Infinite Epigenetics shall have the right to designate up to 5 directors, including 3 independent directors Infinite Epigenetics plans to nominate Brad Keywell, Matt Dawson, and Rocky (Raquel) Bono to the Board of Directors Transaction subject to negotiation and execution of definitive agreement and will require a subsequent Nano Dimension Shareholder vote Transaction expected to close by the end of the year.

WHAT THIS CREATES An AI - powered preventive health and diagnostics company on company on Nasdaq. The proposed combination would bring Infinite Epigenetics, its proprietary biological AI platform and revenue - generating diagnos tics operations, to the public market under the ticker IEAI. Commercial stage company CLIA - certified lab; established sales org with 7,500+ providers in our network; live revenue today. Robust IP portfolio & dataset 11 patent families; one of the largest private DNA - methylation datasets globally. Proprietary biological AI model An epigenetics - anchored foundation model that compounds with every test. Four lead disease programs COPD, Type 2 Diabetes, Cardiovascular Disease, and MASLD (Fatty Liver) from one at - home blood test. Experienced leadership team Co - founded by Dr. Matthew Dawson, Dr. Michael Mallin, and Brad Keywell, Original Investor & Board Member of Tempus AI (Nasdaq: TEM). Many channels, one engine Current: Healthcare Providers, Research, Commercial, Consumer. Future: Employer & Enterprise, Medicare Advantage, Life Insurance, Pharma, Military. DNA methylation: a chemical tag that switches genes on/off; the signal we read · CLIA - certified: the lab meets U.S. federal standards to run diagnostic tests on patients · MASLD / MASH: metabolic - associated fatty liver disease and its advanced form (formerly NAFLD / NASH) 07

EVERY 11 SECONDS Someone in the world dies from COPD. EVERY 9 SECONDS Someone in the world dies of diabetes. EVERY 2 SECONDS Someone in the world dies of cardiovascular disease. Sources: WHO, “Chronic Obstructive Pulmonary Disease (COPD),” 2026; WHO, “Cardiovascular Diseases,” 2026; International Diabe tes Federation, “IDF Diabetes Atlas,” 2025. 08

THE PROBLEM Chronic diseases cause ~75% of deaths worldwide. worldwide. Today's diagnostics are failing us. They are reactive, confirming disease after symptoms appear, often years after the biolog y h as already changed. The cost of that delay is measured in trillions, and in countless lives. >4 Billion People worldwide live with one of these diseases. Type 2 Diabetes Cardiovascular Disease MASLD (Fatty Liver Disease) Chronic Obstructive Pulmonary Disease (COPD) $500B Saved by scaling proven interventions. interventions. >7 Years Years Average time from disease onset to to diagnosis. $4.5T Annual health care expenditures for for chronic and mental health conditions. Sources: WHO, “Noncommunicable Diseases,” 2025; CDC, “Fast Facts: Health and Economic Costs of Chronic Conditions,” 2026; McK ins ey Health Institute, “The Health of Nations: Stronger Health, Stronger Economies,” 2026. Boers et al., “Global Burden of COPD Through 2050,” 2023; Global Burden of Cardiovascular Diseases and Risks 2023 Colla bor ators, “Global, Regional, and National Burden of Cardiovascular Diseases and Risk Factors in 204 Countries and Territories,” 2025; Younossi et al., “The Global Epidemiology of NASH,” 2023; International Diab ete s Federation, “IDF Diabetes Atlas,” 2025. Gopalan et al., “Prevalence and Predictors of Delayed Clinical Diagnosis of Type 2 Diabetes,” 2019; Manikat et al., “Peri - Complication Diagnosis of NAFLD,” 2025; Larsson e t al., “Impact of COPD Timing on Clinical and Economic Outcomes,” 2019. 09

What if you could predict or diagnose these diseases with remarkable precision , years before symptoms arise? 10

INFINITE EPIGENETICS OVERVIEW We built the platform that makes it possible. Infinite's proprietary biological AI model is trained on the most information - dense biological signal that exists: the epigenome . Until AI, no one could interpret it at scale. Now, we can predict disease years earlier and more precisely than traditional d iag nostics. The body’s most data - rich biological layer Standard labs measure ~50 biomarkers. We measure over 1 million epigenetic signals in every drop of blood. + One of the world’s largest biological datasets 120,000+ samples. 50+ peer - reviewed validation studies. + A proprietary biological AI platform to translate it 1,500+ algorithms. AUCs of 0.85 - 0.96 (strong disease discrimination). = Disease caught years earlier, like never before Earlier detection. Better prediction. Care personalized to you. Every test expands the dataset that trains the AI model Epigenome: the full set of these on/off instructions — the body's operating system · Biomarker: a measurable biological sign al of health, risk or treatment response · AUC (Area Under the Curve) measures how well a test separates people who have a condition from those who do not. Sources: TruDiagnostic Bioinformatics, “Illumina EPIC - Xtra (XTRACoRSIV1) Array — Probe Composition Reference,” 2026. 11

WHY NOW For the first time, AI can interpret epigenetics at scale. Two forces are arriving at once. Epigenetics has become a validated, dynamic readout of the body, and AI has become powerful and cheap enough to interpret it at scale. Infinite sits at the intersection. EPIGENETICS IS NO LONGER EXPERIMENTAL Epigenetics is the science of gene expression, shaped by lifestyle, aging, stress, and environmental factors. DNA is 20% of your health. Epigenetics is approximately 80%. Supports earlier risk detection, before late - stage disease, enabling true prevention, not just detection. 50+ peer - reviewed studies and 80+ partnerships with top institutions have validated the science. ARTIFICIAL INTELLIGENCE & FALLING COMPUTE COSTS AI is now powerful enough to make sense of vast health data. The cost of AI compute has fallen 5x to 10 × over the past several years. Foundation model improves as its dataset grows with every test. One of the world’s largest DNA methylation databases used to train the foundation model. Sources: Gundlach et al., “The Price of Progress: Price Performance and the Future of AI,” 2025; Rappaport, Stephen, “Genetic Fa ctors Are Not the Major Causes of Chronic Diseases,” 2016; Walker et al., “Data Resource Profile: Whole - Blood DNA Methylation Resource in Generation Scotland (MeGS),” 2025. 12

MORE ADOPTION MORE DATA SMARTER MODELS DEEPER INSIGHTS 13 ONE - LINER We read the operating system of the body – and use AI to translate it into earlier diagnosis and better care.

HOW THE TEST WORKS A simple at - home blood collection powers millions of health insights. 01 At - Home Blood Collection A small blood sample, collected at home or in clinic. 02 Lab Processing Our CLIA - certified lab reads 1M+ epigenetic signals from a single sample. 03 AI Translation Our foundation model translates the raw signals into clear health insights. 04 Clinical Guidance Risk and disease insights empower physician consults that are preventive and personalized. 1M+ + Epigenetic signals read per sample. Every test expands the dataset that trains the model Sources: TruDiagnostic Bioinformatics, “Illumina EPIC - Xtra (XTRACoRSIV1) Array — Probe Composition Reference,” 2026. 14

OUR PROPRIETARY MODEL How the proprietary AI model works. Infinite Epigenetics pairs one of the world's largest epigenetic datasets with a biological AI foundation model trained on bi lli ons data points - redefining how disease is predicted, detected, and prevented. Methylation array: the lab test that reads methylation from a blood sample · Multi - omic: several layers of biological data c ombined into one model · CpG site: a spot on DNA where methylation is measured; the array reads ~1M per sample Illustrative of the indication menu read from a single methylation array. The billions of data points are derived from 120,00 0+ samples processed, each measuring between 200,000 - 1 million CpG sites. 15 Blood - based epigenetic signals 1M+ epigenetic signals (via CpG sites) Diverse, longitudinal cohorts 120K+ samples and growing Multi - omic + clinical data Clinical context today; multi - omic on the roadmap. Proprietary algorithms & insights Compounding network effects Proprietary AI model trained on billions of data points Type 2 Diabetes COPD Cardiovascular Disease MASLD (Fatty Liver)

OUR DATA FLYWHEEL Why it’s hard to replicate . Most diagnostics companies have an AI chatbot. We have a flywheel – with five years of patent filings, proprietary know - how, and a compounding data asset – widening the gap between us and any future competitor. 120K + samples collected. Every one made the model smarter. 1,500 + algorithms built on biology no one else has access to. 1M + biological signals per test. Standard labs read 50. 80 + research partnerships. The people who built this field are building it with us. THE COMPOUNDING LOOP More valuable, and more defensible, at scale. 01 More tests 03 Smarter models 02 More data 16 “The most valuable healthcare AI platforms will be built on proprietary proprietary biological data .” Brad Keywell

THE MARKET SIZE Starting with four large, underdiagnosed populations . Our initial focus is on four large chronic disease markets where novel diagnostic technologies can drive the biggest impact, wit h a clear roadmap for future entry into additional disease markets beyond these four. Cardiovascular Disease #1 U.S. cause of death ~919K deaths/yr 5 YEAR PREDICTOR Type 2 Diabetes ~115M ~80% unaware (incl. prediabetes) 5 YEAR PREDICTOR MASLD (Fatty liver) ~100M ~99% undiagnosed DIAGNOSTIC COPD ~30M ~80% undiagnosed >$50B burden DIAGNOSTIC Platform optionality. Beyond the four initial diseases, the same foundation model reads biological age, additional disease proxies, and new indicat ion s at near - zero incremental cost. Biological age: the body's age from epigenetic signals, vs. years lived Sources: COPD Foundation, “COPD Prevalence, Disease Burden Varies Significantly by State,” 2025; Le et al., “Estimated Burden of MASLD in US Adults,” 2025; Kaiser Permanente, “Many Adults May Be Unaware That They Have Liver Disease,” 2025; American Lung Association, “COPD in Your State,” 2026; CDC, “National Diabetes Statistics Report,” 20 26; CDC, “Heart Disease Facts,” 2024. Ho et al., “Under - and over - diagnosis of COPD,” 2019. Lamprecht B, et al. "Determinants of Underdiagnosis of COPD in National and International Surveys." Chest. 2015. CD C, “Diabetes in the US,” 2026. 17

PERFORMANCE VS. EXISTING DIAGNOSTICS Strong performance versus standard tools across four major chronic diseases. Across major chronic diseases, our models show AUCs (area under the ROC curve) of 0.85 – 0.96. AUC measures how well a model separ ates people with a condition from those without it: 0.50 is no better than chance, 1.00 is perfect discrimination. MASLD (Fatty liver) 0.96 Type 2 Diabetes 0.92 COPD (Chronic pulmonary obstructive disease) 0.91 Cardiovascular Disease 0.85 AUC: how well a test separates people with a condition from those without (0.5 chance, 1.0 perfect) · ROC curve: the plot of true vs. false positives that AUC is derived from “AUC = area under the ROC curve (disease - state discrimination). Comparator values are published literature estimates that vary b y population, endpoint, and time horizon and require same - cohort confirmation before use. 18 PUBLISHED COMPARATOR RANGES — SEPARATE COHORTS, NOT HEAD - TO - HEAD COMPARISONS MASLD (detect) 0.96 vs FIB - 4 ~0.76 - 0.85 · CVD (predict) 0.85 vs PREVENT ~0.76 - 0.79 · T2D (predict) 0.92 vs FINDRISC ~0.75 · COPD (detect) 0.91 vs symptom - based case - finding ~0.70

HEALTHCARE PROVIDER MARKET OPPORTUNITY $94B prevalence TAM today. today. INDICATION PREVALENCE TAM WHAT WE DETECT Type 2 Diabetes $42.9B 5 - year T2D risk in prediabetes and metabolic - risk adults. Cardiovascular Disease $22.3B 5 - year ASCVD risk for intermediate - risk primary - prevention adults. MASLD (Fatty Liver) $20.9B Blood - based stratification for ≥F2 liver fibrosis in metabolic - risk adults. COPD $7.8B Pre - spirometric diagnostic aid for symptomatic, undiagnosed adults. Total Addressable Market $94B B ASCVD: atherosclerotic cardiovascular disease; the standard 10 - year heart - risk category; Prevalence TAM is calculated as full US addressable population x ASP (Avg. Sales Price) Source: Company estimates based on CDC, “Trends in the Prevalence of COPD,” 2023; Ho et al., “Under - and Over - diagnosis of COPD, ” 2019; CDC, “Type 2 Diabetes,” 2024; Unalp - Arida and Ruhl, “Prevalence of MASLD and Fibrosis Defined by Liver Elastography,” 2025; NIH, “Diabetes Statistics,” 2024; CDC, “Diabetes in the US,” 2026. Vega, Wang and Grundy, “Prevalence and Significance of Risk Enhancing Biomarkers in the US Population at Intermediate Risk for Atherosclerotic Disease,” 2022. US Census Bureau, “Exploring Age Groups in the 2020 Censu s,” 2023. 19

ADDITIONAL MARKET OPPORTUNITIES Near - zero incremental cost for new markets. The same finger prick that catches diabetes early can also enrich a pharma trial and screen a military unit. Healthcare Providers Providers CURRENT MARKET DTC & Commercial Partnerships Partnerships CURRENT MARKET Research & Institutional Institutional CURRENT MARKET SaaS & Software Software that helps turn complex methylation results into clear, usable insights that labs and health systems could license. FUTURE MARKET Military & Gov't Health Health A chance to bring earlier health insights to vulnerable service members and veterans, a large, well - funded system with urgent unmet needs in areas like mental health. FUTURE MARKET At - Risk & Enterprise Health plans and employers that pay for outcomes have a built - in reason to adopt earlier detection, since catching disease sooner can help lower the long - term cost of care. FUTURE MARKET Life Insurance Insurance Insurers and investors price longevity for a living; biological - age insights could help them do it more accurately, in a way that's distinct from traditional genetic testing. FUTURE MARKET Pharma & Data Data Drug developers increasingly rely on large biological datasets, and Infinite’s testing and data could support their biomarker, trial, and partnership work. FUTURE MARKET 20

COMMERCIAL APPLICATIONS The possibilities of what we can learn are infinite . Our proprietary biological AI model is designed to support earlier disease - risk detection, treatment - response modeling, biologic al - age measurement, and other applications on one shared model. Each test expands the dataset available for future model development. Healthspan: years lived in good health, distinct from total lifespan 21 Early disease detection Earlier risk detection, before late - stage disease. Biological age & longevity Protocols for optimal healthspan Treatment response Predict responders before trial - and - error Mental health Neurocognitive and nervous system markers Fertility & maternal Preconception, IVF, pregnancy, postpartum Drug discovery & targets Signatures that reveal what to target Trial enrichment Select patients by biology, not diagnosis code The Foundation One biological foundation model, with a roadmap to multi - omic inputs

MARKET PRECEDENTS Three companies with multi billion - dollar validations. Infinite does all of it, from one platform. Exact Sciences proved diagnostics can scale in the public market. GRAIL proved methylation works. Tempus proved data plus AI is a platform. Infinite Epigenetics is where all three converge. Exact Sciences PROVEN Molecular diagnostics can scale in the public markets with a single chronic disease test. GRAIL PROVEN Methylation can power multi - disease detection from blood. Tempus PROVEN Proprietary clinical data + AI is a public - market platform. Infinite Epigenetics has the same science across multiple chronic diseases. Infinite Epigenetics owns one of the world’s largest methylation datasets. Infinite Epigenetics has built a proprietary biological AI platform trained on biology. Named companies are category precedents only. No valuations or side - by - side claims are made. 22

THE INFINITE PORTFOLIO One data engine, multiple brands . Infinite Epigenetics powers clinical diagnostics and longevity solutions across its portfolio with one biological data engine . E very test that TruDiagnostic and Tally run expands the shared biological data asset, so the entire platform gets smarter, and more valuable, ov er time. OPERATING COMPANY · CLINICAL A commercial diagnostics platform and methylation data engine, TruDiagnostic has collected 120,000+ epigenetic samples, supported 80+ research studies and trials with pharma and academic partners, and is validated by 50+ peer - reviewed publications. 120k+ SAMPLES 50+ PUBLICATIONS 80+ PARTNERSHIPS OPERATING COMPANY · CONSUMER Co - founded by Dr. David Sinclair, a Harvard Medical School professor, Tally is a professor, Tally is a consumer longevity and biological - age testing company company with 15+ peer - reviewed publications validating the science. Built for science. Built for anyone trying to slow aging and improve healthspan. healthspan. TIME - seq TALLYAGE 15+ PUBLICATIONS 23

LEADERSHIP A team that has done this before . Proven operators paired with the scientists who authored the field, with $20B+ in combined exits behind the founding team. CO - FOUNDER Matt Dawson, MD Chief Executive Officer Six - time healthcare founder with multiple exits Author of two medical textbooks and dozens of book chapters National award for Innovation in Healthcare Sought - after speaker on precision medicine, AI in healthcare, and the future of diagnostics CO - FOUNDER & CURRENT CHAIR Brad Keywell Board Member EY World Entrepreneur of the Year Original Investor and Board Member of Tempus AI Raised $4B+ in capital over the last decade Serial entrepreneur with multiple $1B+ exits, including Groupon, Tempus AI, and Echo Global Logistics CO - FOUNDER Mike Mallin, MD Chief Science Officer Two - time successful healthcare founder Author of 35 peer - reviewed publications Renowned educator on genomics, longevity, and systems - based health Track - record figures reflect the founders' prior ventures. 24 Founded 10+ companies $20B+ in total exits Clinical physicians and educators National awards for innovation 50+ peer - reviewed studies published

OUR PARTNERS Built with leading institutions . Relationships span research collaborations, data - use agreements, and licensed IP across leading institutions. PEER - REVIEWED STUDIES 50 + DUAS & COLLABORATIONS 80 + DUA: data - use agreement governing how a partner's data may be accessed and used Relationships include research, data, processing, licensing, and advisory collaborations. Logos do not imply endorsement, con tra ct value, or commitment. 25

OUR PARTNERS Science, clinical, and governmental advisors. VADM (Ret.) Rocky Bono, MD Former CEO, Defense Health Agency David Shulkin, MD 9th Secretary, U.S. Veterans Affairs Gen. (Ret.) Michael Garrett U.S. Army Gen. (Ret.) Paul Funk U.S. Army Gen. (Ret.) Ed Daly U.S. Army MG (Ret.) Dennis LeMaster U.S. Army MILITARY & GOVERNMENTAL AFFAIRS SCIENTIFIC RESEARCH BOARD Jessica Lasky - Su, PhD Harvard Raghav Sehgal, PhD Yale Michael Corley, PhD Cornell Andrew Teschendorff, PhD Cambridge Wanding Zhou, PhD Van Andel Institute CLINICAL ADVISORY BOARD Helen Messier MD, PhD Sanjeev Goel MD, FCFP (PC), CAFCI Vincent C. Giampapa MD, FACS Edwin Lee MD, FACE Pamela W. Smith MD, MPH, MS MD, MBA Jeffrey Gladden MD, FACC Paul Savage MD, FACEP, FAARM Darshan Shah MD Joseph Raffaele MD No governmental, military, VA, or DoD endorsement, relationship, or procurement pathway is implied. 26

27 Brad Keywell AI in healthcare will not be defined by chatbots alone. We believe the most valuable healthcare AI platforms will be built on proprietary biological data. Infinite Epigenetics has the opportunity to bring that platform logic to epigenetics, one of the most powerful and dynamic data layers in medicine. We see epigenetics and longevity as one of the most compelling long - term opportunities in healthcare — with the potential to reshape how health is measured, managed, and optimized. Infinite, with TruDiagnostic and Tally Health, has the scientific depth, data infrastructure, and ambition to scale it. Joe Craft The best investments I have ever made are the ones that are good business and good for people at the same time, and this is one of them. Infinite Epigenetics uses their proprietary algorithms and biological foundation model to not only diagnose serious disease but also predict it years before any symptom shows up. This is the kind of company I intend to help build for the long run. OUR INVESTORS The capital backing the platform. A founder - aligned cap table spanning consumer, growth, and technology investors.

KEY TAKEAWAYS Why shareholders should support this transaction. transaction. 01 A proprietary biological AI foundation model 02 Proprietary IP & a vast dataset that can't be replicated 03 A live, revenue - generating diagnostics business today 04 Clear use of capital to scale validation, data, and commercialization Methylation probe: proprietary tools that read methylation efficiently 28

NASDAQ: NNDM → IEAI THE THESIS, ONE LAST TIME One proprietary AI platform. Many clinical answers. A compounding biological data asset. 29

REFERENCE Glossary. y. ASCVD AUC Biological Age Biomarker CLIA - certified CpG site DNA Methylation DUA Epigenetics Epigenome Foundation Model Healthspan MASLD / MASH Methylation Array Methylation Probe / Probe Set Multi - Omic ROC curve Term Sheet 30