Disclaimers This presentation and any accompanying discussion and documents contain information that includes or is based upon "forward-looking statements" within the meaning of the Securities Litigation Reform Act of 1995. These forward-looking statements are based on our current expectations, estimates and projections about our industry and our company, management's beliefs and certain assumptions we have made. The words “plan,” “anticipate,” “believe,” “continue,” “estimate,” “expect,” “intend,” “may,” “will” and similar expressions are intended to identify forward-looking statements. Forward-looking statements made in this presentation include outcomes and benefits expected from the Tempus partnership, including our ability to leverage the datasets acquired through the license agreement into increased machine learning capabilities and accelerate clinical trial enrollment; outcomes and benefits expected from the Enamine partnership; our planned expansion of the BioHive supercomputer capabilities; outcomes and benefits from licenses, partnerships and collaborations, including option exercises by partners and additional partnerships and ability to house tools on the BioNeMo Marketplace; the potential for additional partnerships and making data and tools available to third parties; advancements of our Recursion OS, including augmentation of our dataset; outcomes and benefits expected from the Large Language Model-Orchestrated Workflow Engine (LOWE); the occurrence or realization of any near- or medium-term potential milestones; the initiation, timing, progress, results, and cost of our research and development programs and our current and future preclinical and clinical studies, including timelines for data readouts, the potential size of the market opportunity for our drug candidates; our ability to identify viable new drug candidates for clinical development and the accelerating rate at which we expect to identify such candidates; our expectation that the assets that will drive the most value for us are those that we will identify in the future using our datasets and tools, and many others. Forward-looking statements made in this presentation are neither historical facts nor assurances of future performance, are subject to significant risks and uncertainties, and may not occur as actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. For a discussion of factors that could affect our business, please refer to the "Risk Factors" sections in our filings with the U.S. Securities and Exchange Commission, including our Annual Report on Form 10-K for the Fiscal Year ended December 31, 2023. This presentation does not purport to contain all the information that may be required to make a full analysis of the subject matter. We undertake no obligation to correct or update any forward-looking statements, whether as a result of new information, future events or otherwise. Certain information contained in this presentation relates to or is based on studies, publications, surveys and other data obtained from third-party sources and the company’s own internal estimates and research. While the company believes these third-party sources to be reliable as of the date of this presentation, it has not independently verified, and makes no representation as to the adequacy, fairness, accuracy or completeness of, any information obtained from third-party sources. In addition, all of the market data included in this presentation involves a number of assumptions and limitations, and there can be no guarantee as to the accuracy or reliability of such assumptions. Finally, while the company believes its own internal research is reliable, such research has not been verified by any independent source. Any non-Recursion logos or trademarks included herein are the property of the owners thereof and are used for reference purposes only. 2

What is L(earnings) and why are we starting this practice now? Traditional Earnings Scripted, Boring, Hard to access L(earnings) Authentic, Adaptive, Easy to access 3 vs.

TechBio Origins - One Decade Ago 4

There is a formula for mapping and navigating complex systems using technology Digital (bits) Data Aggregate and organize data to create digital maps of reality 2 2 Real (atoms) 1 Profile Systems Capture high-dimensional data to create a digital record of reality (things, places, preferences, etc.) 1 Algorithms Navigate digital maps to predict novel relationships, then try them in reality 3 3 5

Data roadblocks made mapping and navigating biology difficult Reproducibility Crisis Multiple studies have shown that the vast majority of published academic literature cannot be recapitulated Analog Standard The fax machine is alive and well in medicine, while in biopharma, study results from CROs are still often reported as PDFs or scanned printouts Siloed Data in Pharma Biopharma has 100s of petabytes of scientific data stored on a project-by- project basis without the meta-data or annotation needed to relate it to other projects or questions in biology ! ! ! ! ! ! ! ! ! ! Trademarks are the property of their respective owners and used for informational purposes only. Baker, M. Irreproducible biology research costs put at $28 billion per year. Nature (2015). https://doi.org/10.1038/nature.2015.17711 6

AI Expert Systems given way to Modern AI Automation Automation tools enable massive scale Storage 1M-Fold Decrease In Costs over 40 years Compute 1M-Fold Increase in Compute over 40 years Bio Tools Tools like CRISPR allow CONTROL of Biology Why was the early-2010s the time for a step- function change in biotech? 7

Fast Forward to Today 8

Data Each week we digitize millions of our own experiments across multiple layers of biology from cell to animal Improved and scaled clinical pipeline We are building and aggregating the right datasets to map and navigate biology Recursion OS 9 Algorithms We own and operate one of the fastest supercomputers on earth, allowing us to train LLMs & FMs fit for the purpose of drug discovery Profile Systems We have built and continue to scale among the world’s most prolific automated wet labs

The Recursion OS combines many tools to industrialize drug discovery 10

PIPELINE • First Generation: Five Phase 2 programs enrolling or soon to enroll patients focused in niche rare disease indications • Second Generation: Multiple preclinical programs and dozens of discovery stage programs focused in precision oncology PARTNERSHIPS • Bio: Large discovery collaborations with Roche/Genentech and Bayer in Neuroscience and Oncology • Tech: Large data collaboration with Tempus, compute collaboration with NVIDIA and chemistry collaboration with Enamine PLATFORM • >50 Petabytes of proprietary biological and chemical data spanning cells to animals to patients • Fastest supercomputer wholly owned and operated by any biopharma • >2M experiment/week capacity spanning multiple-omics layers 11 Leading in TechBio in 2024

2023 Year in Review 12

(Toronto) (Montréal) • Enhance the optimization of Recursion’s compounds for efficacy while minimizing liabilities • Rapidly advance the diversification and discovery of novel chemical matter • Enables mechanism of action deconvolution and generative chemistry • Enable acceleration of generative design of new molecules, DMPK predictions, and more • Combined data generation will support work on building foundation models • Will become a center for cutting-edge applied AI/ML research across chemistry and biology 13 May – Platforms: Acquisitions bolster digital chemistry and generative AI capabilities

June – Pipeline: REC-994 for CCM Phase 2 Completed Enrollment • First therapeutic candidate advanced to an industry-sponsored Phase 2 trial (SYCAMORE) for CCM • Fully enrolled ahead of schedule in June 2023 with 62 patients across 3 arms in a 1:1:1 randomization • Majority of patients treated with REC-994 for ≥ 12 months continue to opt into LTE portion • Favorable safety and tolerability profile in Phase 1 dose-escalation with no DLTs and no SAEs • First-in-disease potential with ODD granted in US and EU Phase 2 Readout Q3 2024 Safety, preliminary efficacy, and pharmacokinetics 14 Cavernomas in the brain and spinal cord

Trademarks are the property of their respective owners and used for informational purposes only. • Partnership on advanced computation (e.g., foundation model development) • Priority access to compute hardware or DGXCloud Resources “If we apply the same methodology that we use in computer-aided chip design, the world of drug discovery could go from computer-aided drug discovery to computer-aided drug design.” “If I were to start from nothing I would do it the way Recursion does it, the systematic way of generating data, I think it's an excellent method which is the reason why we're an investor. I think it's smart approach.” Jensen Huang Founder and CEO, NVIDIA 15 July – Partnership: Our NVIDIA Partnership Announcement $50M Equity Investment • Potential to house Recursion Tools on NVIDIA’s BioNeMo Marketplace • Released Phenom-Beta, a phenomics foundation model in January 2024

~36 Billion Compounds from the Enamine Real Space ~80,000 predicted binding pockets from ~15,000 human proteins ~2.8 Quadrillion potential protein-ligand interactions computed and stored Recursion partnered with to integrate and optimize MatchMaker (ac quired via ) for massive scale GPU-based computation​ on BioHive-1 and the DGXCloud This tool was deployed to predict protein- ligand interaction for ~36 Billion compounds from the Enamine Real Space, less than 90 days post-acquisition of Cyclica and less than 30 days post-partnership with NVIDIA Recursion will use the predicted interactions as a data-layer in its multiomics dataset for honing mechanistic predictions from its wet-labs and for accelerating SAR cycles through better predictions for its internal pipeline and within its partnerships​ Computation at Scale Computation at Speed Computation as a Data-Layer 16 August – Platform: Bridging Protein and Chemical Space with Massive Protein-Ligand Interaction Predictions

September – Pipeline: Phase 1 Study for REC-3964 Complete • REC-3964 was safe and well tolerated at multiple doses up to 900 mg • No SAEs observed​ and no discontinuations related to treatment • Favorable PK profile with exposures (AUC) increasing approximately dose-proportionally • REC-3964 exposures were comparable between healthy elderly subjects and those aged ≤ 65 years • No clinically relevant changes in hematology, chemistry, ECG, or vital signs post REC-3964 doses Proof-of-Concept Study Phase 2 Initiation in 2024 Prevention of recurrent C. difficile infection 17

The combination of scaled data generation and accelerated computing is a key to advancing biological ML 18 September – Platform: Recursion built Phenom-1, the world’s largest phenomic foundation model

Computational Tools Expand BioHive-1 from: • 320 NVIDIA A100s… …to include an additional • 504 NVIDIA H100s With operations beginning H1 2024 Likely to be the highest performing compute cluster owned and operated by any biopharma company on earth and among the top 50 compute clusters on the Top500 list. Thanks to our priority access, the H100s have arrived! 19 November – Platform: BioHive expansion with ambition to be #1 supercomputer in pharma

• Roche exercises its Small Molecule Validated Program Option • Hit series identified using fit-for-purpose oncology map • Recursion will continue to take the lead in advancing the program, leveraging the Recursion OS and its suite of digital chemistry tools with the support and collaboration of Roche Genentech and Roche’s partnership with Recursion exemplifies the power of leveraging large-scale data using advanced computational methods, and the possibilities that come to fruition when several organizations work together.* *Roche ”Scaling up Drug Discovery” article, Sept 2022 20 October – Partnership: Roche exercises its option on the first program under our collaboration “Through collaborations, we maximize the opportunity to nucleate and advance novel insights towards medicines” - Barbara Lueckel, Head of Research Technologies, Roche Pharma Partnering September 22, 2022 October 2, 2023

+ • $160M paid by Recursion to Tempus in cash or equity, at our election, in increasing annual increments over five years, beginning with $22M of equity to be issued later this year • Expected to accelerate model deployment, linking molecular data with outcomes • Expected to enhance program translation as well as identification and enrollment of patients with higher probability of clinical response • Provides preferential access to DNA / RNA sequencing datasets tied to clinical records for >100,000 patients for the purpose of training causal AI models for therapeutic development Proposed accelerates clinical platform capabilities with ~50 PB of proprietary biology, chemistry, and translational precision medicine data purpose-built for AI / ML 21 November – Partnership: Recursion partners with Tempus

“The methodology in which Recursion uses artificial intelligence (AI) in drug discovery, could be one of the most disruptive technologies of our time... As our collaboration and the usage of AI continue to evolve, we look forward to continuing to work with industry innovators to identify novel targets for oncology indications.” — Juergen Eckhardt, M.D. Member of the Executive Committee of Bayer’s Pharmaceuticals Division Head of Business Development, Licensing & Open Innovation and Head of Leaps by Bayer. 22 November – Partnership: Update of existing Bayer collaboration towards strategic interest in precision oncology Companies may initiate up to 7 new oncology programs Go-Forward Collaboration Recursion is eligible to receive potential, success-based future payments of up to $1.5 billion plus royalties on net sales Designed to leverage advancements in Recursion OS platform since partnership inception

Next StepsFurther Confidence Reversal of Fibrocyte Differentiation Assay Identify a potential first-in-class therapeutic NCE with a novel MOA capable of reversing disease-related fibrotic processes Recursion-generated hits show concentration-dependent rescue in a disease relevant human PBMC assay and phenomimic genetic KO of Target Epsilon Compelling efficacy demonstrated in a gold standard animal model of a fibrotic disease with significant unmet need Now entering IND-enabling studies + Pentraxin-2 • Differentiation of human PBMCs into fibrocytes can be reversed by Pentraxin-2, a tissue repair protein, to mimic a healthy state • Phenotypic features of healthy state can be replicated by small molecule rescue REC-1169575 demonstrated concentration dependent rescue in the human fibrocyte phenotypic assay 11 REC-1169575 mimicked CRISPR-KO of Epsilon at low doses and validated in a target Epsilon engagement assay 2 0.25 µM 0.1 µM Epsilon 2 Similar Opposite REC-1169575 significantly reduced collagen in a gold standard animal model of fibrotic disease 33 1. Disease Score of 1.0 reflects “disease state” while disease score of 0.0 reflects “healthy state.” 2. Target Epsilon NanoBRET assay. 3. REC-1169575 administered 50 mg/kg BID PO. Differences between groups analyzed using Kruskal-Wallis test (*p< 0.05). 23 December – Pipeline: Novel Approach for Fibrotic Diseases in-licensed from Bayer Insight From OSGoal Diseased State Healthy State

Q4 – Neuro iPSC production slide? Worlds largest producer 24 December – Platform: Over 1 trillion hiPSC- derived neuronal cells produced since 2022

25 More than a dozen discovery and research programs in oncology or with our partners All populations defined above are US and EU5 incidence unless otherwise noted. EU5 is defined as France, Germany, Italy, Spain, and UK. (1) Prevalence for hereditary and sporadic symptomatic population. (2) Annual US and EU5 incidence for all NF2-driven meningiomas. (3) Prevalence for adult and pediatric population. (4) Our program has the potential to address several indications. (5) We have not finalized a target product profile for a specific indication. (6) Incidence for US only. (7) 2L drug-treatable population. (8) 2L drug-treatable population comprising ovarian, prostate, breast, and pancreatic cancers with no HRR mutations. Program Indication Target Patient Population Preclinical Phase 1 Phase 2 Phase 3 REC-994 Cerebral Cavernous Malformation Superoxide ~ 360K1 REC-2282 Neurofibromatosis Type 2 HDAC ~ 33K2 REC-4881 Familial Adenomatous Polyposis MEK ~ 50K3 REC-3964 Clostridioides difficile infection TcdB ~730K Epsilon Fibrotic Diseases Undisclosed ~ 50K4,5,6 REC-4881 AXIN1 or APC Mutant Cancers MEK ~ 65K7 RBM39 HR-Proficient Ovarian & Solid Tumors RBM39 ~ 200K8 R ar e & O th er O n co lo gy Our pipeline reflects the scale and breadth of our approach Ph2 readout in Q3, 2024 Ph2 safety and preliminary efficacy readout in Q4, 2024 Ph2 safety and preliminary efficacy readout in H1, 2025 Ph2 initiation in 2024 Ph2 safety and preliminary efficacy readout in H1, 2025

The Future of TechBio 26

TechBio Origins: Point Solutions Most BioTech companies have built a point solution - they’ve developed a tool, process, model or analysis to accomplish an important step in drug discovery. This is how we started too. But discovering and developing medicines requires hundreds of steps… 27

As these point solutions evolve they increase in complexity and scale We manipulate human cells with CRISPR/Cas9- mediated gene knockouts, compounds, and other reagents Phenom-1 Groundbreaking models trained on >1 billion images and hundreds of millions of parameters learn to extract biologically meaningful signals from cell images FOUNDATION MODELS Diverse biological and chemical inputs PROFILING SYSTEMS Our highly automated wet-labs systematically capture images of human cells in response to different perturbations High-throughput screening AUTOMATION Maps of Biology & Chemistry DIGITIZATION >50 human cell types ~2M physical compounds Whole-genome CRISPR knockouts Models infer relationships between all possible combinations of genes and compounds, recapitulating known biology and revealing novel insights across multiple biological and chemical contexts >5 trillion relationships conducted every week 2.2M experiments Phenomics Up to 28

To truly industrialize drug discovery, point solutions must be integrated as modules across many diverse steps 29

Each module is complex, and we continuously improve them Prioritize compound synthesis for compounds predicted to have high likelihood of suitable pharmacokinetics DMPK In Vivo Validation Establish in vitro-in vivo and in silico-in vivo correlations to minimize experimental toil. ANIMAL PHARMACOKINETICSPre-synthesis Evaluation ENRICH FOR QUALITY A highly automated DMPK module executes 3 critical assays across human and rat contexts. HT ADME Experiments WET LAB Leverage Recursion’s power for structure-based prediction of in vitro assays and in vivo compound profiles Predictive Models LEARNING CYCLES 30

Utilizing each module requires specialized teams and expertise InVivomic prioritization Digitized data collection yields real-time, continuous, and non-invasive data recorded in the animal’s home cage. Data generates high-dimensional assays, and ML connects studies for productivity. Overall, there is a drastic reduction in time, labor, and cost. Industrialized program progression GOING DIGITAL Compound optimization DETERMINING DOSAGE Not tolerated Tolerated ML evaluation of mice against >10 liabilities. Rat and mouse studies with ML-based selection of optimal compound and dose from video. Speed to insight, including tolerability liability Faster readouts for critical studies SPEED & EFFICIENCY 31

We continuously add new modules to improve the Recursion OS The Tempus data is computed and ML oncology models run on BioHive-1, Recursion’s in-house supercomputer. BioHive-1 will be expanded into a top 50 supercomputer in 2024 in partnership with Nvidia. ML trained on Tempus data BioHive-1 supercomputer COMPUTE The Tempus partnership provides Recursion with preferential access to multi-modal data for >100,000 oncology patients totaling over 20 PB. >20 PB of real-world patient data DATASET We are using Tempus’ scaled multimodal real-world patient data to train AI models for target discovery, biomarker development, and patient selection. Combining forward & reverse genetics APPROACH 32

The result is a palette of ever-evolving sophisticated modules 33

The Recursion OS is now more than a collection of point solutions accessible to expert users …it is increasingly integrated and accessible via a Discovery User Interface that can be used by any of our scientists from the comfort of their laptop… 35

• Potential for additional INDs • HR-Proficient Cancers RBM39 in H2 2024 • In-licensed program from Bayer (Target Epsilon) for a novel target in fibrotic diseases now entering IND- enabling studies • Expected Ph2 trial starts • Ph2 FPI for AXIN1 or APC mutant cancers program expected in Q1 2024 • Ph2 initiation for C. difficile Infection program in 2024 • Expected Ph2 readouts for AI-discovered programs • CCM readout expected in Q3 2024 • NF2 safety & prelim efficacy expected Q4 2024 • FAP safety & prelim efficacy expected H1 2025 • AXIN1 or APC mutant cancers safety & prelim efficacy expected H1 2025 What to Watch for from Recursion: Potential Near-Term Milestones • Potential for option exercises for map building initiatives and partnership programs • Potential for additional partnership(s) in large, intractable areas of biology (CV/Met) • Potential to make some data and tools available to biopharma and commercial users Strong Financial Position $392M in cash YE 2023 Cash refers to cash and cash equivalents at the end of Q4 2023 36

Questions?