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SYM · Symbotic Inc.

Industrial - Machinery · mkt cap $31.5B · calls: Q2 FY2026 vs Q1 FY2026
48.0 conviction · conf-adj 48

conf 3/10 partial

enthusiasm:21.0 · trend:8 · quantifies:0 · impact:0 · under_radar:0 · credibility:12 · business_impact:8 · disruption:0 · commitment:-4 · confirmation:3

Enthusiasm latest 7 / prev 6 (rising)

Symbotic frames its AI story as “physical AI”: a single software platform orchestrating a growing, LiDAR- and vision-equipped autonomous bot fleet, with quantified fleet scale and ~25% per-bot productivity gains—not generative AI. Enthusiasm rose modestly from Q1 to Q2 via explicit edge-data/“teach the bots locally” language and supply-chain AI integration, but management still does not tie AI to discrete revenue or margin lines. Credibility rests on operational metrics (miles, cases, transactions/bot) and installed autonomy; forward claims (full chain connectivity, arms, hospital delivery) remain mostly aspirational and acquisition-dependent.

GROUNDED NEXT-FY IMPACT vs CONSENSUS

Grounded on actual base — revenue $2.2B · net income $-0.0B · net margin -0.8% · diluted EPS -0.16

These are next-fiscal-year annual uplift estimates, not next-quarter numbers.

Aggregate next-FY est. rev uplift: % · next-FY EPS uplift: % · vs analysts: inline · priced in: high · confidence: 3/10

ClaimFigureArithmeticNext-FY Rev %Next-FY EPS %
SymBot productivity +25% YoY (miles & transactions per bot/day)
productivity · soft		over 25% increase YoYPer-bot throughput +25%; no $ opex, backlog, or revenue-per-bot disclosed. Symbotic recognizes revenue on system builds, not per-mile/per-transaction, so a 25% per-bot gain does not map to a revenue line. Aids gross margin (18.8%) but no anchored $ to size. Unanchored.
Operational systems processed >2B cases (CY2025)
engagement · soft		over 2 billion casesThroughput-scale KPI for customers' goods; Symbotic is not paid per case. $2,246.9M/2.0B = $1.123/case is descriptive only, not an uplift. No YoY case base or take-rate disclosed -> no rev/EPS delta. Scale proof point.
Autonomous SymBot ~200M miles (CY2025)
engagement · soft		nearly 200 million milesFleet-scale / training-data metric; no $ mapping (not monetized per mile). Run-rate denominator only, not next-FY revenue. Supports data-flywheel narrative. Unanchored.
Daily fleet 1M autonomous miles/day (current)
engagement · soft		1 million miles a day1M mi/day x 365 = 365M mi/yr run-rate vs 200M CY2025 = +82.5% scale (mixes fleet expansion + productivity). No $/mile or revenue conversion disclosed -> no next-FY rev_uplift_pct. Operational only.
BreakPack bot does 2x work vs prior generation
productivity · soft		twice as much work in the same timeHard 2x throughput per bot, but direction on Symbotic revenue is ambiguous (fewer bots/system = lower hardware revenue, offset by higher ASP). No units, ASP, bot count, or margin base disclosed -> cannot size $. Margin-positive over time but unanchored.
Walmart orders ~40 BreakPack bots per site (pipeline)
revenue · soft		orders for 40 in every siteClosest bookings anchor, but NO disclosed BreakPack unit price and NO disclosed site count -> incremental bookings/revenue uncomputable. Bookings != revenue, and here even the bookings dollar is undisclosed. Cannot size next-FY revenue. Unanchored.
Trailer sequencing: 2,600 cases vs 22 pallets of 125
other · soft		2,600 cases / 22 palletsCapability illustration of case-level sequencing (2,600/125 ~ 20.8 pallet-equiv vs 22). No $, share-of-wallet, or adoption % attached -> no revenue bridge. Qualitative differentiation only.
SKU coverage ~94-95% + stretch bot +2-3%
other · soft		additional 2% or 3%Incremental addressable SKUs of 2-3%; mapping to revenue requires both proportional-revenue conversion AND a rollout rate, neither disclosed. Y modeled 2.5% x 40% FY26 rollout = 1.0% rev (~$22.5M; @18.81% GM ~$4.2M pretax, ~7.5% of consensus NI), but the 40% phasing is not in the inputs -> uncomputable from disclosed figures. Unanchored.

Assumptions: All claims adopter-side (AI improves Symbotic's own robotics/software, not selling third-party AI compute). Next-FY = FY2026 (Sep 2026). Incremental margin: company net margin is negative (-0.75% GAAP) so unusable; consensus is non-GAAP/adjusted (swing to positive, ~$56.5M NI / $0.51 EPS). Tax 21% unused (no anchored cost saving). Phasing: no claim provides a dollar figure phaseable into next FY. Symbotic recognizes revenue on system construction/installation milestones, NOT per-case/per-mile, so operational-scale metrics do not flow to a revenue line. Stretch-bot SKU bridge requires an invented rollout assumption, so left null/soft. Bookings (Walmart 40/site) not converted without site count and ASP. No supplier-side AI revenue in claims.

Top line: Every quantified AI claim is an operational-scale or per-bot productivity metric (>25% YoY per-bot throughput; ~200M bot-miles and >2B cases CY2025; 1M miles/day -> 365M mi/yr run-rate vs 200M; 2x BreakPack throughput; 94-95%+stretch SKU coverage) — none is a dollar revenue figure for Symbotic, which recognizes revenue on system builds rather than per-case/per-mile. The deployment anchor (Walmart '40 BreakPack bots per site') lacks both a disclosed unit price and a site count, so it cannot be sized. The stretch-bot +2-3% SKU coverage is the only candidate revenue bridge but requires an undisclosed rollout/conversion assumption (Y's 1.0%/~$22.5M relies on an invented 40% FY26 rollout), so no anchored upside is computable -> est_rev_uplift_pct = null. These efficiencies are directionally consistent with consensus's +24.5% FY26 revenue ramp ($2.247B->$2.798B, +$551M) but quantify no upside beyond it.

Bottom line: Symbotic is GAAP loss-making (net income -$16.9M, EPS -$0.16), so any EPS-uplift % is mathematically meaningless (tiny/negative denominator) -> est_eps_uplift_pct = null per the loss-making guardrail. Consensus already models a swing to positive adjusted EPS (+$0.51 FY26 on ~$56.5M NI). Productivity claims (+25% per bot, 2x BreakPack throughput) should support gross margin (currently 18.8%) but are unanchored to any disclosed dollar saving/cost base, so no bottom-line increment is computable.

[impact n/m (all claims soft/unanchored); EPS uplift n/m (loss-making base)] Consensus already embeds the AI flywheel: FY26 revenue $2.798B vs $2.247B = +24.5% (+$551M; Street +25.4%), FY27 +28.2% to $3.588B, and a swing from -$0.16 GAAP EPS to +$0.51 adjusted (~$56.5M NI). Management claims are productivity/scale proof points that justify this ramp but carry no incremental dollar anchor above it — the one candidate revenue bridge (stretch-bot SKUs) is only ~1.0% (~$22.5M) under an invented 40% rollout, ~4% of the implied growth increment, not a step-change above the Street. Forward AI (SyMicro, APD, M&A, connected supply chain) is unquantified. The AI story reads as priced into the existing growth ramp.

MODEL CONSENSUS (impact)

partial

Agree on verdict (inline, priced_in high, adopter, EPS null). Differ only on stretch-bot SKU revenue bridge; took conservative null since Y's phasing was invented.

Conflicts reconciled
FieldOpus 4.8GPT-5.5
Rev uplift %––
EPS uplift %––
Priced inhigh–
vs analystsinline–
Confidence3–
Top lineEvery quantified AI claim is an operational-scale or per-bot productivity metric (>25% YoY per-bot throughput; ~200M bot-miles and >2B cases in CY2025; 1M miles/day; 2x BreakPack work-rate; 94-95%+stretch SKU coverage) — none is a dollar revenue figure for Symbotic, which recognizes revenue on system builds rather than per-case/per-mile. The only deployment-pipeline anchor (Walmart '40 BreakPack bots per site') lacks both a disclosed unit price and a site count, so it cannot be sized. With no anchored incremental Symbotic-revenue dollar available, est_rev_uplift_pct = null. These efficiencies are directionally consistent with consensus's +24.5% FY26 revenue ramp ($2.247B -> $2.798B, +$551M) but quantify no upside beyond it.–
Bottom lineSymbotic is GAAP loss-making (net income -$16.9M, EPS -$0.16), so any EPS-uplift % is mathematically meaningless (tiny/negative denominator) — est_eps_uplift_pct = null per the loss-making guardrail. Consensus already models a swing to positive adjusted EPS (+$0.51 FY26 on ~$56M NI). The productivity claims (25% more transactions/miles per bot, 2x BreakPack throughput) should support gross margin (currently 18.8%) but are unanchored to any disclosed dollar saving, so no bottom-line increment is computable.–
ReasoningConsensus already embeds the AI flywheel: FY26 revenue $2.798B vs $2.247B = +24.5% (+$551M), FY27 +28.2% to $3.588B, and a swing from -$0.16 GAAP EPS to +$0.51 adjusted (~$56M NI). The management claims are productivity/scale proof points that justify this ramp but carry zero incremental dollar anchor above it (gap = $0 identifiable). No upside to consensus is quantifiable from the disclosed figures, so the AI story reads as priced into the existing growth-and-profitability-swing trajectory.–

Rows highlighted where the two models disagreed.

QUANTIFICATIONS
SymBot productivity — miles and transactions per bot per day: over 25% increase YoY (vs one year ago (Q1 FY2026 call), both)
“we have seen an over 25% increase in both the number of miles driven and the number of transactions per bot daily versus one year ago.”
Cases processed (operational systems): over 2 billion cases (calendar year 2025, topline)
“Symbotic operational systems processed over 2 billion cases for customers in calendar year 2025 inbound and outbound.”
Autonomous SymBot miles: nearly 200 million miles (calendar year 2025, both)
“our Symbots logged nearly 200 million miles alone in calendar year 2025.”
Daily autonomous fleet miles: 1 million miles a day (current (Q2 FY2026 call), both)
“Today, our bots are traveling 1 million miles a day.”
BreakPack bot throughput vs prior generation: twice as much work in the same amount of time (current rollout (Q2 FY2026), both)
“They can do twice as much work in the same amount of time as the old bots.”
BreakPack deployment scale (Walmart): orders for 40 of these in every site (forward deployment pipeline (Q2 FY2026), topline)
“Walmart has given us orders for 40 of these in every site.”
Trailer/case sequencing illustration: 2,600 cases; sequence every case vs ~22 pallets of 125 cases (capability example (Q1 FY2026), topline)
“if a trailer has 2,600 cases, we might and there was 125 cases on a pallet, we might put 22 pallets on a truck. But we could actually sequence every one of those 2,600 cases.”
SKU coverage — standard vs stretch bot: ~94–95% vs additional 2–3% (current fleet mix (Q2 FY2026), topline)
“we designed our bots to handle about 94%, 95% of the products. The stretch bot handles another 2% or 3%, which becomes very important to the customer.”
PAST (realized)
CURRENT (now)
FORWARD (guidance)
TRACK RECORD — PROMISE vs DELIVERY

74/100 track record   delivers  6 calls reviewed

Symbotic rarely says “AI” but does quantify autonomy/ML and deployment physics; judgeable track record is mostly positive on install-time and bot-throughput metrics, with partial slippage on Walmart ASR/APD prototype timing versus early-2026 guidance.

>30% faster install-to-accept vs historical Phase 1 (size-normalized) — promised Q2 FY2025
delivered Later calls stacked 20%+ Phase 2 gains, ~3 months off vs historical, ~10-month average, and an Exol site under 10 months.
ASR/APD first prototype installation to begin early calendar 2026 — promised Q3 FY2025
partial Q1 FY26 cited progress toward initial prototypes; Q2 FY26 still targeted first two store prototypes within six months with only a small ITC unit running—full install start slipped past early 2026.
ASR paid-development revenue to ramp over 8–12 quarters as prototypes build — promised Q2 FY2025
partial ASR/paid dev moved from mid/high-single-digit % of revenue to low-double-digit % by Q1 FY26, but the full multi-year ramp window is not complete.
Next-gen deployments to cut install-to-accept by more than half for equivalent case output — promised Q4 FY2025
partial Mgmt cited 2x Phase 1 scope and faster installs, but also asked for more time as next-gen mix scales; company-wide “half the time” norm not yet proven.
Install-to-accept trajectory toward ~10 months — promised Q1 FY2026
delivered Q2 FY26 reported Exol Atlanta install-start to acceptance in under 10 months.
First large-site day with zero manual case repositioning (ML path for teleops tasks) — promised Q3 FY2025
delivered Claimed achieved in Q3 FY25; not walked back in later calls.
PRICED-IN (REFINED)
HIGH (already in)

Est. revisions rising  ·  Fwd P/E 196.9  ·  EV/Sales 11.4x

AI claim maps to Operation Services, Software Maintenance And Support, Systems

Analyst sentiment has migrated up over the past six months (buys 6→9, holds 10→7) while consensus price targets stepped higher (last-quarter avg $70 vs last-year $62 vs all-time $54). Forward estimates embed steep growth (revenue ~$2.2B to ~$3.6B FY25–27; EPS ~$0.24 to ~$0.71), so AI/automation upside is already in the numbers. At ~197x next-FY P/E and ~11.4x EV/Sales, the market is paying a premium multiple typical of priced-in growth; AI claims map most plausibly to recurring Operation Services and Software Maintenance, with Systems as deployment scale.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
5Q1 FY20254Q2 FY20257Q3 FY20255Q4 FY20258Q1 FY20266Q2 FY2026

AI enthusiasm across 6 calls — trend ↗ rising

From vague innovation to Q3 ML repositioning, then physical-AI fleet metrics; peaked Q1 FY26, softened on product expansion.

RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY

8/10 qualitative impact   material  near-term · mixed evidence

Where AI matters: autonomous warehouse robotics platform and per-bot throughput

Physical AI (vision, LiDAR, edge learning, orchestration software) is the core product, not an overlay, with credible fleet-scale proof (+25% YoY per-bot miles/transactions, ~1M bot-miles/day, 2x BreakPack throughput) that should improve deployment economics and recurring ops value, but management ties no claim to discrete revenue or margin lines and Street already embeds a steep FY26–27 ramp.

Caveats: No dollar bridge from productivity metrics to revenue or gross margin; Growth and physical-AI narrative largely priced into consensus (~25%+ FY26 rev, premium multiples); BreakPack 2x throughput could reduce bot counts per site versus hardware bookings; Prototype/M&A slippage on SyMicro, APD, arms, and end-to-end chain connectivity

AI DISRUPTION / CANNIBALIZATION RISK  tailwind · 2/10

SYM monetizes warehouse automation capital and software/services, not billable labor hours GenAI would deflate; competitive catch-up from cheaper autonomy stacks is industry risk, not AI cannibalizing what they sell.

OPTIONS / MARKET STRUCTURE

option liquidity: fair

ATM IV
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TYPICAL BID-ASK
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OPEN INTEREST
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proxy inputs — dollar-ADV $82M · beta 2.04 · px $47.77

source: proxy (no options chain on FMP)
FMP /stable/ exposes no options-chain endpoint on this key, so ATM IV, bid-ask spread and open interest are unavailable. Liquidity below is a PROXY from dollar-ADV, beta and price level (a stand-in for option depth), not measured option-market data.

CONFIRMATION — INSIDERS · 13F · LANGUAGE
Mixed — insiders selling, institutions adding, management language 2/10 hedged.
INSIDERS selling 39 open-market sell(s) vs 0 buy(s) — net distribution
INSTITUTIONS (13F) adding as of 2026-03-31: 77 new / 73 closed positions; 218 increased / 104 reduced; institutional ownership -22.34pp; +0 net 13F holders
MGMT LANGUAGE 2/10 hedged No AI/ML cited; robotics/automation framed with goals, belief, and potential—not as a committed AI driver.
commit “we are also now deploying a larger version of our SymBot to handle a larger variety of SKUs”
commit “we continued to make progress on our SyMicro product for e-commerce order fulfillment and remained on track to install our first prototypes this calendar year”
hedge “We believe our continued investment in new bot technologies and enhancements will be a key enabler”
VERBATIM AI QUOTES
“The fact that our platform improves over time speaks to our leadership in the emerging category of what some call physical AI.”
— Rick Cohen, Q1 FY2026
“Specifically, for our SIM bots that move goods in customer distribution centers, we have seen an over 25% increase in both the number of miles driven and the number of transactions per bot daily versus one year ago.”
— Rick Cohen, Q1 FY2026
“Symbotic operational systems processed over 2 billion cases for customers in calendar year 2025 inbound and outbound. And our Symbots logged nearly 200 million miles alone in calendar year 2025. As best we can tell, this may be the most traveled fully autonomous vehicle fleet in the world.”
— Rick Cohen, Q1 FY2026
“we recently closed the acquisition of Fox Robotics, a leader in autonomous forklift solutions. This acquisition further enhances our strategy of utilizing our software to orchestrate robots that move goods through the supply chain from the dock door at the warehouse to the individual customer order from the store.”
— Rick Cohen, Q1 FY2026
“Matter of fact, what we do in the transfer deck in the structure is we might have 100 bots in a 400 by 24-foot wide. So a 10,000 square foot area. And the dock may only have like, 20 or 34 trucks. They're bigger. They're heavier. But the software that we're using and the evolution of what we're doing where they have vision, they have LIDAR, and they can avoid collision.”
— Rick Cohen, Q1 FY2026
“the bots now have eight cameras, and the bots will also have LiDAR on them, which is the newest thing we're installing. And so that allows us to use bots for our structure, but we'll be able to use bots for any part of the warehouse.”
— Rick Cohen, Q1 FY2026
“we're not fighting for with Google and ChatGPT for those chips. So we don't expect that kind of problem and we'll be able to upgrade when we're ready to upgrade. Right now, we can handle what we're doing with the chips that we have, but we actually think the new chips will be the new chips that we're looking at will be more powerful and either the same price or less expensive. So within what you're looking at in the battle going on with the big guys in AI, that's not the space that we're playing in. What we can do is much more moderate control on the bots. And then eventually, the bots will get smarter, but we're not building huge data centers here.”
— Rick Cohen, Q1 FY2026
“In the brake pack, they're much more free floating. And so that takes a lot of software to stop them from crashing into each other at high speed with LiDAR.”
— Rick Cohen, Q1 FY2026
“we can actually sequence every one of those 2,600 cases. That to a lot of people who are delivering small orders, is really interesting.”
— Rick Cohen, Q1 FY2026
“Within several of these verticals, a capability that is drawing strong interest is our systems' ability to sequence goods for route optimization.”
— Rick Cohen, Q2 FY2026
“the handling on those is where the software imagine comes about and then mixing those together, and we've cracked that code.”
— Rick Cohen, Q2 FY2026
“Today, our bots are traveling 1 million miles a day. We may have the largest autonomous fleet traveling today in the world. I'm not sure. But we're traveling a lot of autonomous miles. The bots are all being retrofitted with LiDAR.”
— Rick Cohen, Q2 FY2026
“Software is in place, allows us to actually sequence, which is interesting for route drivers, sequence itches and packages, and so for gig drivers who are doing multiple deliveries, BreakPack is a very interesting application.”
— Rick Cohen, Q2 FY2026
“We're very focused on leveraging the end-to-end supply chain and having -- whether it's AI, some of this will be, but just knowing where everything is in the system and setting up our robots and our software to be able to handle it is really what we're focused on.”
— Rick Cohen, Q2 FY2026
“There are a lot of people with a lot of names with a lot of high valuations that are talking about physical AI. We're the ones that are actually have the information and actually moving the products.”
— Rick Cohen, Q2 FY2026
“We've been managing so much data on the physical AI side about what -- how we teach the bots to handle data locally as opposed to sending it up to the cloud and what we need to send up to the cloud.”
— Rick Cohen, Q2 FY2026
“I'm like maniacally focused on this for 3 years.”
— Rick Cohen, Q2 FY2026
“robotic arms are interesting to us. There's a couple of companies out there that are doing it. It's not -- it's -- so we're looking at it.”
— Rick Cohen, Q2 FY2026
ANALYST QUESTIONS ON AI
Q (Q1 FY2026, Colin Rusch): If you move into multiple form factors here with the BOBS and start working through, you know, different generations of these bots. Can you talk a little bit about the potential for designing modular components and things that are common across these form factors to help optimize some of the cost structure?
A: Rick Cohen: Yeah. So that's exactly what we're planning on doing... the bots now have eight cameras, and the bots will also have LiDAR on them... that same software can control lots of different machines. So it's what we've always said. We want to create a software platform and then we want to have for me, they're just different apps. The bots are just different pieces of technology.
Q (Q1 FY2026, Ken Newman): When I listened to you all these new exciting developments that you've got, on the new generation of bots that you're developing, it sounds like those are gonna be requiring updated chipsets. So just talk a little bit about your ability to source those updated chips and if you think there's a way to price for those chips in a price cost positive way.
A: Rick Cohen: Yeah. So we'll probably upgrade to, at some point, to the next generation of NVIDIA chip or something like that... we're not fighting for with Google and ChatGPT for those chips... within what you're looking at in the battle going on with the big guys in AI, that's not the space that we're playing in... eventually, the bots will get smarter, but we're not building huge data centers here.
Q (Q2 FY2026, Colin Rusch): I'm curious about the evolution of the capabilities that you guys are thinking about as well as some of the increased integration with the supply chain. We're starting to see autonomous trucks hit the road in a little bit higher volume. I'm curious about some of the scheduling capabilities that you're thinking about and partnerships there as well as the potential to move into heavier objects or even into delivery into hospitals with robots that are integrating into a built environment already... how you'd be approaching that or whether from an acquisition or partnership perspective?
A: Rick Cohen: Yes. Good question... We want to connect the whole supply chain... schedule through our system, integrated with somebody else's system probably... We're very focused on leveraging the end-to-end supply chain and having -- whether it's AI, some of this will be, but just knowing where everything is in the system and setting up our robots and our software to be able to handle it is really what we're focused on. We will be acquisitive... We're going to go both upstream and downstream and may look at even more software acquisitions as part of how we connect our systems.
Q (Q2 FY2026, Colin Rusch): The second question is really around data management. We're seeing an escalation in kind of data transfer and management of management expenses. I'm just curious about how you guys are thinking about that if it's even registering at this point for you from a cost perspective and something you need to manage on a go-forward basis?
A: Rick Cohen: Yes, absolutely. We've been -- I'm like maniacally focused on this for 3 years... We're very focused on the data that we need... how we teach the bots to handle data locally as opposed to sending it up to the cloud and what we need to send up to the cloud... we're actually very focused on managing this variation.
Q (Q2 FY2026, Robert Jameson): When you look ahead, what are some of the other parts that you might look to invest in to further automate other parts of either the Symbotic system itself, BreakPack or the micro fulfillment system? Should we expect like ecosystem partnerships on the MSC side like adding cobot arms to -- or picking solutions that take another human out of the loop on the back end of those systems. I mean I'm just trying to understand what types of technologies are interesting to you at this point that would help you accelerate some of those efforts as you move kind of towards a so-called dark warehouse with the Symbotic solution.
A: Rick Cohen: Yes. You mentioned a bunch of things. I mean obviously, robotic arms are interesting to us. There's a couple of companies out there that are doing it. It's not -- it's -- so we're looking at it... We're very focused on micro fulfillment because we think that's a huge opportunity. That would lead us to eventually look at robotic arms... We really want to get the dock management working well. We want to understand the perishable world. Those are the things that we're really focused on right now.