Quantum-si Incorporated · NASDAQ:QSI
Quantum-si — Investor Day (November 2025)
79 slides from Quantum-si's investor day presentation, Nov 20, 2025
Slide 1: Quantum Si Investor & Analyst Day November 19, 2025
1 Quantum Si Investor & Analyst Day November 19, 2025
Slide 2: Investor Day Agenda
2 Investor Day Agenda 10:00–10:10 AMTackling the Complexity of the ProteomeJeff Hawkins, CEO 10:10–10:40 AM Proteus Program Update and Long-term Technology Roadmap Todd Rearick, CTO 10:40–11:05 AMThe Path to Detecting All 20 Amino AcidsJohn Vieceli, CPO 11:05–11:25 AMPost-translational Modification
Slide 3: Proteins Are the Core of Biological Discoveries Across Many End Markets
3 Proteins Are the Core of Biological Discoveries Across Many End Markets Academic Research Pharma + Biotech Industrial Defense Clinical Diagnostics Translational Research Agriculture
Slide 4: Proteome Complexity
4 Proteome Complexity GENOME TRANSCRIPTOME Alternative Promoters Alternative splicing mRNA editing Post-translational Modifications ~20–25,000 GENES ~100,000 TRANSCRIPTS PROTEOME >1,000,000 PROTEOFORMS
Slide 5: The Study of Proteoforms Extends to Many Disease Areas and Thousands of Unique Proteins
5 The Study of Proteoforms Extends to Many Disease Areas and Thousands of Unique Proteins Human Proteoform Project: https://www.science.org/doi/10.1126/sciadv.abk0734 Complete coverage of the proteome would require hundreds of thousands or more unique, site- specific affinity reagents Only single-mo
Slide 6: Proteoforms Are Not Limited to a Single PTM Type
6 Proteoforms Are Not Limited to a Single PTM Type They are far more diverse, even within a single protein Source: J. Proteome Res. 2025, 24, 6, 2916–2925 Brains Tau Immunoprecipitation 0N3R 1N3R, 0N4R 1N4R Intact Tau isoforms/proteoforms
Slide 7: Proteoforms Also Include Single Amino Acid Variants
7 Proteoforms Also Include Single Amino Acid Variants, Which Can Be Critical to Understanding Disease GluGluPro GluValPro Healthy Sickle Cell Disease Variant Protein sequence Adapted from Ramadas N and Sparkenbaugh EM (2023). The APC-EPCR-PAR1 axis in sickle cell disease. Front. Med. 10:1141020.
Slide 8: Specialized Platforms With High Capital Costs Limit Adoption Outside of Core Labs
8 Specialized Platforms With High Capital Costs Limit Adoption Outside of Core Labs in Proteomics Many specialized platforms needed to fully interrogate the proteome Technical tradeoffs when selecting between the breadth of protein coverage and depth of insights High capital costs with the top end i
Slide 9: Moving Beyond the Core Lab: Proteus Will Enable Deep Protein Analysis
9 Moving Beyond the Core Lab: Proteus Will Enable Deep Protein Analysis and Accelerate the Field of Proteomics Automation simplifies laboratory workflow, increases throughput, and minimizes the need for specialized staff Affordable, allowing any lab — anywhere — to be a proteomics core lab Single-mo
Slide 10: Themes of Today's Presentations
10 Themes of Today’s Presentations Proteus performance data and long-term technology roadmap The path to detecting all 20 amino acids A diverse set of tools to enable generalizable PTM analysis Road to Proteus launch and 2026 milestones
Slide 11: Proteus Program Update
QUANTUM SI Proteus” € Program Update
Slide 12: Proteus Next-generation Architecture
12 Proteus Next-generation Architecture Platinum® Pro + 2M Chip • Integrated semiconductor consumable • Benchtop instrument with manual workflow Proteus + KinetIQ Array • Simple, passive consumable • Benchtop instrument with imaging system • Workflow automation
Slide 13: KinetIQ Array
13 KinetIQ Array Simple, passive consumable • Low-cost fused silica die • 80M wells per device • Architecture scales to billions of wells Simple packaging • Inexpensive plastic assembly • Four flow cells, each with 20M wells • Features to support automation
Slide 14: Proteus Instrument
14 Proteus Instrument Optical module • High-performance custom optical design • High resolution and large field of view • Supports simple passive consumable Liquid handling • Full workflow automation • More advanced workflows, deeper insights
Slide 15: Proteus Program Status
15 Proteus Program Status Key technical risks retired or substantially reduced Critical system components matured through several prototypes Integrated system design complete — building first systems now
Slide 16: Sequencing Workflow Automation is More Reproducible Than Current Manual Workflow
16 Sequencing Workflow Automation is More Reproducible Than Current Manual Workflow Integrated System Liquid Handling • Same architecture as integrated product design • Entire sequencing workflow fully automated Prototype Liquid Handling Subsystem Data Automated vs manual workflow alignments
Slide 17: KinetIQ Array Fabrication and Post-processing Processes are Established
17 KinetIQ Array Fabrication and Post-processing Processes are Established Wafer fabrication process established Well structure optimized Efficient packaging processWafer-scale post-processing Product intent die size + geometry
Slide 18: Prototype Imaging System and New Dyes Validate Transition from Lifetime to Color Ratio
18 Data from Prototype Imaging System and New Dyes Fully Validates Transition from Lifetime to Color Ratio • Same architecture as product design • Commercial off-the- shelf components • Product-intent image sensors • Reduced field of view • New color-space dye set • Demonstrated up to 8 dyes • Room
Slide 19: Successful Dynamic Sequencing Runs Completed in Q3
19 Successful Dynamic Sequencing Runs Completed in Q3 Substantial de-risking new system elements Consumable, dyes, optical system, software L 87.4% 0.89 E 65.2% 0.5 Q 72.3% 1.5 A 96.3% 1.07 Q 67.1% 8.15 Q 30.2% 6.24 I 69.2% 0.24 R 71.4% 0.53 L 70.2% 0.71 Q 50.2% 0.86 A 57.8% 0.71 E 19.7% 0.33 A 25.5
Slide 20: Proteus Has Superior Sequencing Output Per Well Compared to Platinum
20 Proteus Has Superior Sequencing Output Per Well Compared to Platinum Proteus routinely produces more alignments with the same number of wells Proteus produces more long alignments compared to Platinum Alignments per well (normalized to Platinum) Long-read fraction (normalized to Platinum)
Slide 21: Proteus Consistently Sequences Deep into Peptides
21 Proteus Consistently Sequences Deep into Peptides Unique capability for long-range structural information Access to PTMs and variants deep into reads Sequencing depth expected to continue to improve with increased coverage and further optimization Sl19_V_IL6(87–120)—IIT: 439 alignments 30.1% I 89
Slide 22: Proteus Has Superior SNR and Short Pulse Detection Compared to Platinum
22 Proteus Has Superior SNR and Short Pulse Detection Compared to Platinum Better SNR • More high-quality alignments • Better accuracy • More sensitive for PTMs and variants More sensitive short pulse detection • Increased motif coverage with the same binders • Software not optimized for improved da
Slide 23: Proteus Sequencing Performance is on Track to Far Exceed Platinum at Launch
23 Proteus Sequencing Performance is on Track to Far Exceed Platinum at Launch Proteus data is already superior to Platinum data Data generated to date is without optimization Current algorithms | Current V4 binder set | Current cutters and chemistry Additional improvements expected before launch
Slide 24: Integrated System in Development
24 Integrated System in Development First Integrated System Expected 1Q26 • Full integration of imaging and workflow automation • Product-like consumables • Full field of view supporting 20M wells
Slide 25: Proteus Program Summary
25 Proteus Program Summary Transition to new architecture is proven — team is executing towards product launch for YE2026 Proteus architecture shows significant improvement over Platinum in the quantity and quality of sequencing output Platform launch is aligned with improvements in biochemistry and
Slide 26: Long-term Technology Roadmap
26 Long-term Technology Roadmap
Slide 27: Proteus Architecture Supports Our Long-term Platform Roadmap Requirements
27 Proteus Architecture Supports Our Long-term Platform Roadmap Requirements Proteus 2.0 (up to 10B) Proteus (80M+) Proteus Plus (up to 320M) Consumable architecture scales to billions of wells 10× scaling from assay improvements alone Future instruments capable of up to 10B reads
Slide 28: Super Poisson Loading Increases Sequencing Output per Run by Approximately 3×
28 Super Poisson Loading Increases Sequencing Output per Run by Approximately 3× Super Poisson Loading • Peptides are loaded in a way that prevents multiple loading • Only one peptide can be loaded in most wells Poisson Loading • Peptides randomly loaded into wells • Maximum single-molecule loading
Slide 29: Faster Sequencing Roadmap + Field Upgrades Could Drive Output Up to 320M
29 Faster Sequencing Roadmap + Field Upgrades Could Drive Output Up to 320M and Increase Samples per Run Proteus (80M) Sequencing time reductions allow more chips to be run in same timeframe as original 80M Upgrade to drawer/stage and consumable to increase chips/run Proteus Plus (up to 320M)160M 32
Slide 30: The Path to Billions of Reads Requires Controlled Cutting
30 The Path to Billions of Reads Requires Controlled Cutting Current Sequencing Chemistry Cutting happens randomly Residue duration is not uniform Time/residue is slower on average Controlled cutting would define the amino acid boundaries + enable a scanning system
Slide 31: Successfully Demonstrated a Controlled Cleavage Version of Our Sequencing Chemistry
31 We Have Successfully Demonstrated a Controlled Cleavage Version of Our Sequencing Chemistry Enables scanning system Amino acid boundaries are known Residue duration is controlled and uniform Time/residue is much faster on average Controlled Cleavage Chemistry Defined Cutting Points
Slide 32: Combining Controlled Cleavage with High-speed Scanning Scales to Billions of Reads
32 Proteus 2.0 can incorporate high-speed scanning and microfluidic delivery system Scanning system enables billions of reads Multiple imaging locations within one flow cell Efficient usage of device area Enabled by controlled cleavage chemistry Combining Controlled Cleavage with High-speed Scanning
Slide 33: The Path to Detecting all Amino Acids
33 The Path to Detecting all 20 Amino Acids John Vieceli, Chief Product Officer November 19, 2025
Slide 34: Recognizer Vision for Twenty Canonical Amino Acids on Proteus
34 Develop a set of N-terminal amino acid recognizers for twenty canonical amino acids on Proteus Vision
Slide 35: Recognizer Roadmap
QUANTUM SI Recognizer Roadmap
Slide 36: Sequencing Technology Overview
36 Sequencing Technology Overview Recognizers bind amino acids in sequence Recognition events produce kinetic signatures R L I F 6005004003002001000 0.24s 3.23s 0.23s 0.97s TIME (min) Kinetic signature plot Excitation ‘R’ Sequenced ‘L’ Sequenced ‘I’ Sequenced ‘F’ Sequenced
Slide 37: Amino Acid Recognizers in Sequencing Kit V4
37 Amino Acid Recognizers in Sequencing Kit V4 Recognition for 14 of 20 amino acids using 6 recognizers DEGASFYW LIV R NQ
Slide 38: Software Improvements Enable More Amino Acids
38 Software Improvements Enable More Amino Acids Q4 software release with Library Prep Kit V3 will increase to 15 amino acids DEGASFYW LIV R NQM Peptide from Programmed Death-Ligand 1 Peptide from Hepatocyte Growth Factor DL Q A A V Y R C M I Q F NC M SL W F P S
Slide 39: Path to Amino Acids with Recognizers
39 Path to 20 Amino Acids with 8 Recognizers Detection of 18 amino acids demonstrated with campaigns for C and T underway DEGAFYW LIV P TSRHK NQMC LN Ⓗ V A V F A Ⓚ LA AF SⓅ NI LF
Slide 40: Recognizer Roadmap Supported on Proteus
40 450 0 400 350 300 250 200 150 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 IN T E N S IT Y COLOR RATIO Recognizer Roadmap Supported on Proteus Intensity and color ratio space supports 8+ dyes 4Cy3B C6C 4ATR6G 4GGN C2CFRET 3BGN 4C53ONS Eight dyes have been demonstrated on Proteus prototype system Additiona
Slide 41: Recognizer Development Pipeline
Recognizer Development Pipeline
Slide 42: Recognizer Evolutionary Tree
42 Recognizer Evolutionary Tree 6 recognizers in Sequencing Kit V4 were derived from 4 starting proteins FYW LIV GASAS R NQ D DE FYW2 FYW1 FYW1FYW1 A. Tumefaciens | ClpS2 LIV1 T. Elongatus | ClpS1 R1 K. marxinus | UBR1 AS1 H. sapiens | cIAP1–BIR3 NQ1 H. sapiens | NTAQ1 + mutations D1 LIV2 LIV3 LIV4
Slide 43: Quantum-Si N-terminal Amino Acid Recognizer Data
43 Quantum-Si N-terminal Amino Acid Recognizer Data Kinetic DataStructural DataBinding Data ~300~100~40~800~3,500~107 Labeled amino acid sequence data for binding N-terminal amino acids AI model refinement Predicted N-terminal amino acid binder
Slide 44: Protein Databank Mining for N-terminal Binders
44 Protein Databank Mining for N-terminal Binders Used for scaffold generation and model training High-quality events 7,588 71.214kExposed Single receptor 15.479k 238.674k Ordered and complete atomic representation 287.848k N-terminal binding interactions
Slide 45: AI Model Refinement Enabled By Academia and Industry
45 AI Model Refinement Enabled By Academia and Industry Ligand message- passing neural network Evolutionary scale modeling GPU hardware acceleration
Slide 46: 4× Scale-up of Recognizer Development Pipeline
46 4× Scale-up of Recognizer Development Pipeline Utilize AI, rational, and combinatorial design approaches to generate candidates for screening pipeline Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Spectral analyzer Expression Dye label Bulk kinetics 96/week 16/week Validation Production Combinatorial
Slide 47: X-ray Crystallography with Combinatorial and AI Strategies Yielded the GAS Recognizer
47 X-ray Crystallography with Combinatorial and AI Strategies Yielded the GAS Recognizer Crystal structure of NQ recognizer with GAKL peptide Several modifications in the pocket lead to G, A, and S binding, while not allowing for N and Q Info from combinatorial screening + AI
Slide 48: Proline Recognizer from AI and Combinatorial Methods
48 Proline Recognizer from AI and Combinatorial Methods Parent protein 18 mutations P I Single mutant knockouts P /I B IN D IN G R A T IO AMINO ACID POSITION
Slide 49: Summary of the Path to Twenty Amino Acids
49 Summary of the Path to Twenty Amino Acids Recognizer development program is being scaled 4× to achieve detection of all canonical amino acids in 2026 and release on Proteus in 2027 Efforts in artificial intelligence utilize Quantum-Si screening data to refine deep learning and language models, in
Slide 50: PTM Analysis Solutions
50 PTM Analysis Solutions Brian Reed, PhD Head of Research
Slide 51: Agenda
51 Agenda PTM Solutions on Proteus Advantages of single-molecule detection for PTMs1 PTM applications on the path to Proteus launch3 Broad access to PTMs on Proteus2
Slide 52: PTMs and Proteoforms are the Next Frontier in Human Health
52 Su P G Me Methylation (Lys/Arg) Phosphorylation (Ser/Thr/Tyr) Palmitoylation (Cys) Sumoylation (Lys) Ubiquitination (Lys) Citrullination (Arg) AC Pal Ub Glycosylation (Ser/Thr/Asn) Acetylation (Lys) Translation Cit A post-translational modification (PTM) is a chemical change to an amino acid made
Slide 53: Challenge to Detecting PTMs With Existing Technologies
53 Challenge to Detecting PTMs With Existing Technologies Mass spectrometry • Quantification difficult • Ambiguity in modification site assignment • Multi-site combinations extremely challenging • Workflow and analytical complexity (limits clinical adoption) Affinity-based platforms • Detect protein
Slide 54: Advantages of Single-molecule Detection for PTMs
54 Advantages of Single-molecule Detection for PTMs • Quantitation straightforward due to direct counting of molecules • Direct PTM site identification • Access to multi-site PTM combinations • Simple workflows for broad PTM proteome coverage; clinical compatibility • Universal PTM detection reagent
Slide 55: Single-molecule Detection Enables Broad PTM Coverage
55 Single-molecule Detection Enables Broad PTM Coverage NGPS unlocks broad and universal access to PTMs with three complimentary approaches | Can be used in combination to address the most challenging needs in PTM detection Kinetics PTM detected via kinetic changes at upstream AAs Pre-recognition PT
Slide 56: Kinetic Detection of PTMs
56 Kinetic Detection of PTMs • Kinetic response to PTMs is a universal feature of NAA recognizers—when the chemical makeup of the peptide changes, the kinetics change. No extra reagents or processing steps needed • Examples: phospho-, methyl-, acetyl-, oxidation, citrullination • Customers are using
Slide 57: Pre-recognition of PTMs
57 Pre-recognition of PTMs • PTM detection at any position regardless of peptide length • Parallel detection of multiple PTMs • E.g., Pan-phospho kit: Comprehensive detection of pS/pT/pY in one assay • Extreme sensitivity to PTM stoichiometry due to the clear pulsing pattern from PTM recognition
Slide 58: Direct N-terminal Detection of PTMs
58 Direct N-terminal Detection of PTMs Direct NAA detection • N-terminal PTM recognizer included in sequencing assay • Can be standard NAA recognizer or custom • Enables reference-free/de novo PTM discovery • Suitable for very complex sequence contexts and multisite PTM/variant arrangements
Slide 59: Kinetics: Influence of Downstream pY on NAA Recognizers
59 Kinetics: Influence of Downstream pY on NAA Recognizers Unmodified peptide • R pulse duration decreases from 1.3 to 0.5 sec. • L pulse duration increases from 2.5 to 3.5 sec. • Y is no longer recognized Used to detect tropomyosin proteoforms pY modified peptide R L pY F I R L Y F I https://pubs.a
Slide 60: Kinetics: Influence of Citrulline on NAA Recognizers
60 Kinetics: Influence of Citrulline on NAA Recognizers RFLR RFLCit FLCit FLR LCit LR R Cit Arginine (R) Citrulline (Cit) Unmodified peptide Cit-modified peptide How citrulline influences recognizer kinetics in this peptide • F pulse duration decreases from 3.49 to 2.65 seconds • L pulse duration in
Slide 61: Kinetics: Multiple Kinetic Parameters Inform PTM Detection
61 Kinetics: Multiple Kinetic Parameters Inform PTM Detection Arginine (R) Citrulline (Cit) Citrulline and other PTMs influence multiple kinetic parameters • Pulse duration: the lifetime of the recognizer-NAA bound state • Interpulse duration: the time between recognizer binding events • Recognition
Slide 62: Pre-recognition: pY Detection at Any Peptide Location
62 Pre-recognition: pY Detection at Any Peptide Location An anti-phosphotyrosine antibody detects phosphotyrosine at any peptide location — N-terminal, internal, and C-terminal linker adjacent — independent of sequence context pY recognition Sequencing Y N-terminal pY Internal pY Internal pY pY adja
Slide 63: Pre-recognition: Carna Biosciences Kinase Panel
63 Pre-recognition: Carna Biosciences Kinase Panel pY recognition Sequencing Analysis 50% 12% 13% 16% 11% Alignments with pY recognition . . . Y PYK2B PTM position ID and relative abundance quantitation Phosphorylation is a key determinant of activity for protein kinases used in drug discovery appli
Slide 64: Direct NAA Detection: Methionine Oxidation
64 Direct NAA Detection: Methionine Oxidation Methionine sulfoxide Methionine Pulse duration distinguishes the modified and unmodified forms of methionine The NQM recognizer directly detects N-terminal methionine sulfoxide at position Met91 in IKBA NF-kappa-B inhibitor alpha (IKBA) Unmodified methio
Slide 65: We Have a Clear Path to Broad PTM Coverage on Proteus
65 We Have a Clear Path to Broad PTM Coverage on Proteus Recognizer development Recognizers for all 20 amino acids will ensure maximum protein coverage and kinetic information available for PTM detection with all three methods Higher output on Proteus Enables deeper and more sensitive PTM detection
Slide 66: The Road to Proteus Launch
QUANTUM SI The Road to Proteus € Launch
Slide 67: From Platinum to Proteus — Market Learnings Inform Proteus Requirements and Commercial Strategy
67 From Platinum to Proteus — Market Learnings Inform Proteus Requirements and Commercial Strategy General technology first; defined applications second Sample prep-agnostic Broad marketing to all segments at launch Defined applications first; general technology second Sample-to-report workflows for
Slide 68: The Customer Data is Clear
68 The Customer Data is Clear Researchers need a breadth of capabilities to answer their biological questions Number of Unique Applications One Two Three or more Number of PTMs Required One Two Three or more More than 50 detailed study proposals submitted by prospective customers >50% require three
Slide 69: A Look Inside an Academic Medical Center
69 A Look Inside an Academic Medical Center Basic Research Lab Core Lab Translational Lab Clinical Lab Academic Medical Center • Wide range of application interests • Limited infrastructure • Lower utilization • Many technologies in use in one lab • Significant infrastructure • High utilization pote
Slide 70: Platinum Case Study — The Academic Medical Center
70 Platinum Case Study — The Academic Medical Center Basic Research Lab Core Lab Translational Lab Clinical Lab Academic Medical Center Good value prop but most users are low- utilization Limited to reflex testing downstream of mass spec Adoption limited by current technology capabilities Not access
Slide 71: Increased Sequencing Output and Lower Costs of the Nanowell Array
71 The Increased Sequencing Output and Lower Costs of the Nanowell Array is Broadly Enabling More samples per run with 40× the output per consumable compared to Platinum Pro Deep analysis of a single sample to address complex mixtures or rare events like variants or PTMs Multiplexing samples to achi
Slide 72: Accelerating the Core Sequencing Technology and Analytics to Unlock the Highest-value Applications
72 Accelerating the Core Sequencing Technology and Analytics to Unlock the Highest-value Applications Robust PTM detection and multi-PTM profiling Single-amino acid variant detection Sequencing of variable regions of antibodies Biothreat detection and surveillance
Slide 73: Proteus Automation Greatly Simplifies the Sequencing Workflow
73 Proteus Automation Greatly Simplifies the Sequencing Workflow and Makes New Lab Startup Even Easier A single reagent module per run — simply unbox and load Pipette your sample(s) into the cartridge and hit Run Over 30 individual reagent tubes to handle to process four samples Over 100 pipetting s
Slide 74: Building a Partner Ecosystem to Accelerate Application Development
74 Building a Partner Ecosystem to Accelerate Application Development + Deliver Sample-to-report Workflows Sample Prep + Enrichment Application Development Applications of AI for Data Analysis
Slide 75: New Industry Partnerships in PTMs and Ultra-low-abundance Protein Panels
75 New Industry Partnerships in PTMs and Ultra-low- abundance Protein Panels • Carna Biosciences is a leading provider of assay-grade kinase proteins to biopharma for drug discovery and profiling • Carna Biosciences is evaluating the use of QSI technology to assess and validate phosphorylation profi
Slide 76: Proteus Will Increase the Depth of Penetration in Academic Medical Centers
76 Proteus Will Increase the Depth of Penetration in Academic Medical Centers Compared to Platinum Single-molecule protein sequencing will remain a useful tool for basic research High-value application capabilities + increased throughput = first-line platform Expanded PTM capabilities + high-value t
Slide 77: Proteus Will Enable Single-molecule Protein Sequencing Across a Broad Range of End Markets
77 Proteus Will Enable Single-molecule Protein Sequencing Across a Broad Range of End Markets Academic Research Pharma + Biotech Industrial Defense Clinical Diagnostics Translational Research Agriculture
Slide 78: Milestones on the Path to Proteus Launch in 2026
78 Milestones on the Path to Proteus Launch in 2026 External customer collaborations initiated (summer 2026) End-to-end sequencing on fully integrated systems (Q2) Platinum upgrade program released (Q3) Instrument list price released (Q2) Internal V&V (Q4) Sequencing on Proteus prototype Fully integ
Slide 79: QSI is Well-positioned to Build Upon Our First-to-market Advantage
79 QSI is Well-positioned to Build Upon Our First-to-market Advantage and Extend Our Leadership into the Future Extend our technology lead through best-in- class R&D innovation + execution Execute on development roadmap to deliver a compelling Proteus launch Build a partner ecosystem to accelerate a