Wednesday, November 11, 2026

@DOMOCAPITAL Oct 19 4 clicks

DOMO Capital Management, LLC on X

I think we can assume that $PESI lost money in Q3, but the most important indicator for me is the backlogs. If they can show a huge increase in backlogs that should indicate that they can be cash flow positive in Q4 and beyond. Stock will go $20+ if market takes the "equity raise" risk premium out - which it should - if management can give certainty on the cash flow front. Again, I think a focus on the backlogs would be the main indicator of this.

@calvinblissett Oct 19

Calvin Blissett on X

$TREE

@StableBread Oct 19 1 click

Fajasy on X

Just posted the $BRUN write-up here (you can read most of it for free):

@StableBread Oct 19 11 clicks

Fajasy on X

I first wrote up an AI data center company that rents out $NVDA GPUs to AI startup companies on April 15, 2026, when it still traded as a SPAC at $10.70/share, just above its ~$10.60 trust value. The merger was a success, and the stock peaked at $39.20/share on June 1st. Now it trades below its SPAC price. That company is Boost Run $BRUN, which has fallen to $8.89/share, down 77.3% from its peak, even after it announced its largest disclosed contract on October 6 (worth $525.6M). The three larger listed GPU clouds have fallen from their 2026 highs as well, through the October 16 close: → CoreWeave $CRWV: Down 55.5% to $61.39/share. → $IREN: Down 60.2% to $26.99/share. → Nebius $NBIS: Down 42.3% to $165.47/share. So $BRUN fell with the group, but further than all three. I’d blame the drop from $39.20 on two causes that have nothing to do with $BRUN’s core operations: (1) higher rates and borrowing costs, and (2) $BRUN’s float growing ~3.1x, which was expected once its lockup ended and its warrants were called. Yet the business carries less risk than it did as a SPAC: → Contracts: $1.61B with disclosed terms and TCV over $2.6B, including $1.43B signed since my April write-up. → Customers: Thinking Machines Lab (the AI startup founded by former OpenAI CTO Mira Murati) and Cohere make up 61.9% of the $1.61B on three- to five-year terms, after three customers made up 75.9% of 2025 revenue, led by RunPod, a GPU cloud platform, at 44.5%. → Year-end target: If Thinking Machines’ GPUs are fully running by December 31 and the June order starts on November 30, the five disclosed contracts running by year-end cover $300.6M (75.1%) of the $400M ARR target. → Merger: Closed on May 8, 2026, with zero redemptions. → Balance sheet: The merger proceeds paid off its short-term bridge loans, the going-concern language is gone, and pro forma cash is $191.8M, up from the $108M I used in my June 3 update, right after the merger. But $BRUN still has to get the GPUs bought, financed, and running by December 31: → To reach the $1.0-1.2B of GPU spending management expects for 2026, $BRUN has to deploy $663-863M of GPU servers in H2 2026, 2.3-3.0x its cash and contracted prepayments. → CFO Erik Guckel said on the Q2 call that $BRUN is working on new ways to finance the build, but I found no new facility, lender, or term sheet in its filings or press releases from August 14 to October 16. → $BRUN’s named customers are private AI startups without investment-grade ratings, so its contracts are harder to borrow against. → If lessors funded 70% of the H2 2026 build instead of 79.5% (as in H1 2026), $BRUN would need $199-259M of its own cash for the build, more than its $191.8M of pro forma cash. → Both 10-Qs came late, after notices of late filing on May 26 and August 14, and $BRUN still reports three material weaknesses, the most serious kind of gap in a company’s financial reporting controls. → Founder and CEO Andrew Karos controls 87% of the vote. At $8.89/share, $BRUN’s EV is $989.7M. That’s 2.5x its $400M target for year-end ARR, down from 5.4x at the $22.93 price in my August 16 update. At 2.5x, $BRUN trades below all three peers, including $IREN at 3.2x. So did the thesis break, or just the stock? That’s what I answer in my new ~5k-word update on $BRUN, including my bear, base, and bull cases (Excel model included).

@BlueDuckCap Oct 19 3 clicks

BDC on X

Don't see on Bloomberg yet but looks like billionaire health care investor Jorey Chernett has taken his stake in $XGN over 10%. Love the name also. Not advice.

@aleabitoreddit Oct 19 1 click

Serenity on X

Last major $SIVE disclosure was 100M CW DFB laser capacity Q4 2027. And a new foundry partner (that makes 2 including Win Semi). Expected $JBL revenue coming in H1 2027 (with lasers for Jabil's 1.6T LRO scaling up H2 2027). There's channel checks along the way like CIOE where Sivers was engaged with Chinese pluggable makers + laser ASPs being raised. 70mW/100mW ranges were the most tight to Chinese pluggable makers, which was surprising. Biggest industry read through was $LITE selling out into 2029, making agreements for 2030, and having hyperscalers pay for capacity expansion for 2031. I don't think anyone has enough information to do any sort of accurate modeling for $SIVE like you can for $AAOI given they don't release product breakdown + capacity targets by quarter. The 200mW NPO lasers Sivers is sampling is likely different ASP than your 70mW lasers shipped to pluggable makers. And your custom CPO lasers are different pricing too. Like all sampling/qualification players from $AEHR to $AAOI back in 2025, usually the risk/reward comes in whether qualifications convert and what new customers they have, which is always a risk. In a bull case, if $SIVE comes online with 300m laser supply (2:1 implied ratio, already has "tremendous" supply online from likely US fab) during a structural shortage. Pluggable players like $JBL, 6 other vendors. $GFS as the reference design laser for their CPO/NPO platform. Your minor players vendors like $POET, $AEVA and other players end up scaling. And all the other custom products they hinted they were working on in the past for CPO years back. I think the probability that they cook is higher since there's so many ongoing qualifications during a bottleneck. We've already seen ownership changes from Swedish investors to US/International retail from $SIVE shareholder disclosures. My guess is that trends institutional from retail before US listing next year amid the market correction. Think people forgot institutions have already financed their expansion, which was a 700M SEK round 100%+ ago (multiple times oversubscribed). And that $SIVE uses primarily external fabs, so it's not the same as a lot of the major financing concerns affecting Neoclouds. Anyway, up to management execution, I'm not running Sivers so no clue what other companies are working with them now, whether it's Cambridge or some other US player like Semtec. TLDR: - Just need to wait for earnings for more disclosures around qualifications + partners, only so much public can guess from channel checks and supplier mapping. Not quite the same as $LITE CEO where you can see the guy on Fox news or Bloomberg interviews every week (which is a good thing)

@calvinblissett Oct 18 1 click

Calvin Blissett on X

@rebv808 I believe I covered the first question, so I mean it when I say that’s a great question. You mean on the latter % of customers that $CCLD already has as RCM that don’t use EHR right?

@calvinblissett Oct 18 9 clicks

Calvin Blissett on X

$CCLD questions I have so far for Stephen Synder (CEO) interview if I am missing anything please let me know Charlie Munger famously talked about the importance of distinguishing between technological improvements where the economic benefits “stick to our ribs as owners” and those where “all of the advantages from great improvements are going to flow through to the customers.” (Stripe Press) I think it’s fair to say AI will lower costs overall for the RCM industry for those able to take advantage of it. McKinsey estimates that AI enablement of the revenue cycle could reduce cost to collect by 30% to 60%. (McKinsey & Company) We are already beginning to see this play out: roughly 20% to 40% of organizations report broad or enterprise-wide use of AI-enabled tools across different parts of the revenue cycle, while 70% to 90% of decision-makers expect to increase spending on AI-enabled RCM capabilities over the next three years. (Oliver Wyman) How is this playing out currently, and how do you see it progressing? More specifically, where do you think the economic benefits of AI ultimately accrue? Will AI make the strong stronger and the weak weaker—allowing scaled, technologically capable RCM providers to lower their costs faster and potentially furthering industry consolidation? Or, as AI tools become increasingly commoditized and accessible, could they instead level the playing field and erode some of CareCloud’s existing competitive cost advantage? A bit similar to the last question: Could AI change the dynamic of struggling companies not being able to upgrade products and or win clients. Allowing them to improve and compete hence lowering acquisition opportunities? How much growth aside from obviously inorganic acquisitions is existing customers expanding versus new clinics signing up? Do you think about size when acquiring or is it purely a factor of opportunity and fit. It would seem intuitive smaller acquisitions are easier and cheaper. Is there a pace or target you have in mind regarding acquisitions One shareholder asked for more metrics/metrics with news. Just granularity, Shareholder assumes it will be on earnings call but affects of data breach and portion if any that isn’t covered by insurance. What you’re seeing and anticipate seeing in terms of loss of current customers and momentum in future sales. A majority of the employees are in Pakistan which is currently going through a turbulent time and is basically a junta. Do you think there's any need to de-risk it? I believe the ROI from acquisition is at the midpoint of purchase multiple (.6-1x) and target contribution margin (25-30%) on a full year time frame after 9 months to get there to be About 34%. If your stock had the same FCF yield how would you weight buybacks vs acquisitions. Given the same assumed 34% full year after achieving targets on acquisition In Q2 2026, Hadi said: “OurAI and acquisition strategies have become a single, unified growth engine.” Does that mean that AI strategy/product development has similar economics or is it table stakes and has to be invested in merely to keep up?