Banzai’s Bold Bet: Microcap MarTech Player Eyes Revenue-Doubling Acquisition of ConnectAndSell

Banzai International (Nasdaq: BNZI) just made a move that could fundamentally reshape what the microcap marketing technology company looks like by summer — and the numbers tell a striking story.

The Austin-based AI marketing platform announced late last week that it has reached terms to acquire the assets of ConnectAndSell, an AI-powered sales acceleration platform serving B2B organizations across healthcare, financial services, and technology. The deal, structured around a non-binding letter of intent, is expected to close in early Q2 2026, pending a definitive agreement and customary closing conditions.

The strategic rationale is straightforward on paper: Banzai recorded approximately $10.65 million in revenue over the trailing twelve months ending Q3 2025. The ConnectAndSell acquisition is projected to add roughly $15 million in annual revenue — meaning the deal alone would more than double the company’s current revenue run rate if integration goes according to plan. For a company with a market cap hovering around $14 million, that kind of top-line expansion isn’t incremental — it’s transformational.

ConnectAndSell is not a startup. It is an established, profitable business with a track record of generating real revenue across enterprise and mid-market accounts. Its platform is designed to dramatically increase sales team productivity by maximizing time spent in live conversations with qualified decision-makers — a capability that sits at the highest-value stage of the go-to-market funnel. For Banzai, which already helps companies target, engage, and measure marketing outcomes, layering in sales execution capabilities creates an end-to-end revenue platform that few companies at this market cap can claim.

The deal follows Banzai’s acquisition of Superblocks in November 2025, an agentic AI platform for SEO-optimized website development. The pattern is becoming clear: Banzai is pursuing a deliberate build-out strategy, acquiring profitable, AI-native tools that are immediately accretive and strategically complementary rather than chasing speculative moonshots.

Cross-sell opportunity is a core part of the investment thesis here. Banzai’s existing customer base includes more than 140,000 organizations — among them RBC, Dell Technologies, New York Life, and Thermo Fisher Scientific. Introducing ConnectAndSell’s sales acceleration capability to even a fraction of that base could generate meaningful incremental revenue beyond the $15 million headline figure.

Still, investors should keep a few realities in check. The transaction remains at the letter of intent stage — no definitive agreement has been signed, and no purchase price has been disclosed, creating near-term financial transparency uncertainty. Banzai’s stock has also declined roughly 89% over the past year, sitting just below the $1 mark, which reflects a company that has been fighting uphill on the balance sheet even as it executes strategically. Management is scheduled to discuss the proposed acquisition in detail on a conference call March 31, 2026 at 4:30 p.m. Eastern Time, which will be the next critical data point for investors watching this deal develop.

For small and microcap investors, Banzai’s acquisition playbook is worth watching. In a market where platform consolidation is increasingly the path to survival and scale, companies that can string together profitable, AI-powered assets at reasonable valuations may be positioning themselves for an outsized rerating when the market conditions turn. Whether BNZI can execute on that vision is the question the rest of 2026 will answer.

NN (NNBR) – Moving Into Higher Return Verticals


Friday, March 20, 2026

Joe Gomes, CFA, Managing Director, Equity Research Analyst, Generalist , Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Data Centers. NN continues to grow its presence in the data center market, a key targeted growth market for the Company. The AI data center market fits precisely into NN’s decades of know-how in fluid management and Six Sigma quality levels. For NN, it is a strategic and straightforward application of existing know-how with managing gas, diesel, and hydraulic fluids and applying that know-how to managing cooling fluids.

Opportunity. NN has secured multiple new awards with a leading global provider of AI infrastructure and data center computing equipment. In response, NN is investing in a large installation of 17 next-generation high-speed, high-precision CNC machines that will meet and exceed requirements. This expansion and ramp-up is happening now across 2026. These machines will add to NN’s portfolio of over 100 of these similar machines already in-house.


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*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

Perfect (PERF) – Founder-Led Take-Private Proposal


Thursday, March 19, 2026

Patrick McCann, CFA, Research Analyst, Noble Capital Markets, Inc.

Michael Kupinski, Director of Research, Equity Research Analyst, Digital, Media & Technology , Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Take Private Proposal. Perfect Corp. received a preliminary, non-binding proposal from a consortium led by CEO Alice H. Chang and CyberLink to take the company private at $1.95 per share. The transaction would be funded through rollover equity, company cash, and potential debt. The board intends to form a special committee to evaluate the proposal, and there is no assurance that a transaction will be completed.

Ownership structure supports a high likelihood of completion. The consortium controls approximately 53.4% of shares and 81.2% of voting power. In our view, this significantly increases the likelihood of a transaction, subject to special committee approval.


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*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

SelectQuote (SLQT) – Launching Franchise-Based Distribution Channel


Thursday, March 19, 2026

Patrick McCann, CFA, Research Analyst, Noble Capital Markets, Inc.

Michael Kupinski, Director of Research, Equity Research Analyst, Digital, Media & Technology , Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

SelectQuote Local. SelectQuote announced SelectQuote Local, a new franchise model designed to complement its core telephonic insurance distribution platform by offering in-person sales and support. Management indicated the initiative leverages the company’s existing marketing, technology, and carrier relationships, positioning it as a natural extension of the platform rather than a shift in strategy.

Complementary model and TAM expansion. In our view, SelectQuote Local is unlikely to cannibalize the company’s core call center operations, as it targets a distinct subset of consumers who prefer in-person engagement. We believe the company can leverage excess lead flow and brand recognition to support early franchise success without significant incremental marketing investment. Additionally, we expect the in-person model could enhance cross-sell opportunities with Healthcare Services, as local relationships may improve customer engagement and trust.


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Equity Research is available at no cost to Registered users of Channelchek. Not a Member? Click ‘Join’ to join the Channelchek Community. There is no cost to register, and we never collect credit card information.

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

Nvidia CEO Doubles Down: $1 Trillion Is the Floor, Not the Ceiling

Jensen Huang doesn’t do small numbers. But the figure he dropped this week at Nvidia’s annual GTC conference in San Jose may be the most consequential projection in the history of the semiconductor industry — and the ripple effects extend well beyond one company’s balance sheet.

On Monday, Huang forecast that Nvidia’s flagship AI processors would generate $1 trillion in sales through 2027, citing computing demand that has increased “by 1 million times in the last two years.” Then on Tuesday he raised the stakes further, clarifying that the $1 trillion figure doesn’t even capture Nvidia’s full product portfolio. The company has “strong confidence of $1 trillion-plus,” Huang told an audience of analysts and investors, adding that Nvidia expects to close, book and ship more than $1 trillion in total business.

For context, Nvidia had previously forecast $500 billion in data center sales through the end of 2026. The new projection doubles that cumulative figure and extends the window another year — a signal that Huang sees no near-term ceiling on AI infrastructure demand.

Wall Street’s immediate reaction was measured. Nvidia shares jumped as much as 4.8% on Monday before leveling off, trading virtually unchanged by Tuesday afternoon. Some analysts flagged that extending the timeline to 2027 to reach $1 trillion doesn’t necessarily signal accelerating growth — it could simply mean a longer runway to the same destination.

But the more interesting story for small and microcap investors isn’t what happens to Nvidia’s stock. It’s what a $1 trillion AI buildout means for the hundreds of smaller companies that sit inside that ecosystem.

Huang used the conference to announce a significant expansion of Nvidia’s addressable market. The company is pushing deeper into central processing units — territory long dominated by Intel — and introduced semiconductors incorporating technology acquired from chip startup Groq. Nvidia also revealed it is developing chips designed specifically for data centers in outer space, opening an entirely new frontier for AI compute infrastructure.

Each of these moves creates downstream opportunities. CPU expansion pressures Intel and AMD but simultaneously creates openings for smaller, specialized chip designers and manufacturers. The Groq acquisition signals that Nvidia is willing to buy rather than build when speed to market demands it — a dynamic that historically elevates valuations across the small cap semiconductor and AI hardware landscape as larger players scout for targets.

On the capital allocation front, Nvidia’s CFO Colette Kress announced the company plans to direct approximately 50% of free cash flow toward buybacks and dividends in the second half of 2026, once current investment commitments are fulfilled. That shift from aggressive reinvestment toward shareholder returns is a maturity signal — one that typically pushes institutional capital to look further down the market cap spectrum for the growth rates that Nvidia itself once offered.

The AI infrastructure buildout is still in its early innings. A $1 trillion demand signal from the dominant player in the space is not just a headline — it is a directional marker for where capital, talent and M&A activity will flow for the next several years. Small cap investors who understand the supply chain beneath Nvidia stand to benefit most.

The picks and shovels are still selling fast.

Bitcoin Depot (BTM) – Wave of Regulatory Action Weighs on Outlook


Tuesday, March 17, 2026

Patrick McCann, CFA, Research Analyst, Noble Capital Markets, Inc.

Michael Kupinski, Director of Research, Equity Research Analyst, Digital, Media & Technology , Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Q4 results. Bitcoin Depot reported Q4 revenue of $116.0 million, above our estimate of $112.0 million, reflecting somewhat stronger transaction activity than anticipated despite emerging regulatory headwinds. Adj. EBITDA of $1.6 million was below our forecast of $2.5 million due to higher operating expenses during the quarter.

Initial steps toward revenue diversification. The company is beginning to expand beyond the core Bitcoin ATM network through new fintech initiatives. It recently acquired Kutt, a peer-to-peer social betting platform, and launched ReadyBucks, a merchant cash advance platform targeting small businesses and gig workers. Management indicated that both initiative are starting small and not expected to materially impact near-term revenue.


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Equity Research is available at no cost to Registered users of Channelchek. Not a Member? Click ‘Join’ to join the Channelchek Community. There is no cost to register, and we never collect credit card information.

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

Bit Digital (BTBT) – February Ethereum Metrics


Monday, March 09, 2026

Joe Gomes, CFA, Managing Director, Equity Research Analyst, Generalist , Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Data. Bit Digital reported its monthly Ethereum (“ETH”) treasury and staking metrics for the month of February 2026. As of month end, the Company held approximately 155,434 ETH versus 155,239 ETH at the end of January. Included in the ETH holdings were approximately 15,283 ETH and ETH-equivalents held in an externally managed fund. The Company’s total staked ETH was approximately 138,269, or about 89% of its total holdings as of February 28th.

Yield and Value. Staking operations generated approximately 314 ETH in rewards during the period, representing an annualized yield of approximately 2.7%. Based on a closing ETH price of $1,965, as of February 28, 2026, the market value of the Company’s ETH holdings was approximately $305.4 million.


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Equity Research is available at no cost to Registered users of Channelchek. Not a Member? Click ‘Join’ to join the Channelchek Community. There is no cost to register, and we never collect credit card information.

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

Anthropic-Pentagon Clash Puts AI Ethics — and Hype — Under the Small-Cap Spotlight

The escalating dispute between Anthropic and the U.S. Department of Defense is quickly becoming more than a policy debate. It’s a flashpoint for how artificial intelligence companies — public and private — balance rapid commercialization with ethical guardrails.

And for small-cap investors, the episode is a reminder that regulatory and reputational risk can reshape capital flows overnight.

Last week, the Trump administration ordered government agencies to stop using Anthropic’s chatbot, Claude, and labeled the company a supply chain risk after CEO Dario Amodei declined to loosen safeguards preventing use of its models in autonomous weapons and mass surveillance. Anthropic has indicated it plans to challenge the decision once formal notice is received.

The market reaction has been swift.

According to Sensor Tower, Claude surged past ChatGPT in U.S. app downloads over the weekend. Meanwhile, OpenAI faced consumer backlash after announcing a Pentagon agreement to replace Anthropic in classified environments. ChatGPT’s one-star reviews spiked sharply in Apple’s app store following the news, prompting CEO Sam Altman to acknowledge the rollout was mishandled.

The episode highlights a widening divide in AI strategy: aggressive government integration versus caution around high-stakes use cases.

But beneath the headlines lies a more structural issue — readiness.

Missy Cummings, director of the robotics and automation center at George Mason University and a former Navy fighter pilot, recently argued that generative AI systems should not control or guide weapons due to persistent reliability issues. Large language models, she noted, are prone to “hallucinations” and remain unsuitable for environments where errors could cost lives.

Anthropic’s leadership has echoed similar concerns, stating that frontier AI systems are not yet reliable enough to power fully autonomous weapons.

For investors, particularly in small- and mid-cap technology names, the debate underscores a key theme for 2026: execution risk tied to real-world deployment.

Government contracts can provide validation and revenue visibility. But they also introduce political exposure, regulatory scrutiny, and headline volatility. Private AI leaders like Anthropic and OpenAI may dominate public discourse, but publicly traded players — from Palantir (PLTR), which has longstanding defense ties, to Apple (AAPL), whose app ecosystem reflects consumer sentiment in real time — are often the ones absorbing market swings.

The situation also revives questions about what some critics have called the industry’s “hype cycle.” Years of bold claims around AI autonomy and decision-making capabilities helped accelerate defense adoption. Now, as policymakers confront the technology’s limitations, that enthusiasm is meeting institutional caution.

For small-cap investors, this dynamic matters.

Emerging AI infrastructure providers, cybersecurity firms, data analytics companies, and niche software developers frequently market defense or government pathways as long-term growth drivers. Yet this episode illustrates that capital access and contract durability can hinge on shifting ethical standards and public perception — not just technological performance.

It also reinforces a broader capital markets takeaway: reputational capital is financial capital.

Anthropic’s consumer download surge suggests ethical positioning can resonate with users. But legal challenges and lost government business could weigh on enterprise relationships. Conversely, OpenAI’s Pentagon alignment may strengthen federal revenue prospects while pressuring brand perception.

As AI migrates from consumer chatbots into mission-critical systems, readiness — technical, regulatory, and ethical — will increasingly define winners and laggards.

For small-cap investors, the lesson is clear: in emerging technologies, policy risk is no longer a side variable. It’s central to valuation.

OpenAI Lands $840 Billion Valuation as Amazon, Nvidia, SoftBank Double Down on AI Arms Race

OpenAI has secured one of the largest private capital raises in history, reaching an $840 billion valuation as Amazon, Nvidia, and SoftBank anchor a massive $110 billion funding round.

The blockbuster raise underscores that, despite 2026’s volatility in technology stocks and growing talk of an AI valuation bubble, capital formation in artificial intelligence remains robust. For investors, the message is clear: the AI infrastructure race is accelerating, not slowing.

According to Reuters, SoftBank committed $30 billion in the round, Nvidia invested $30 billion, and Amazon pledged $50 billion. Additional investors are expected to participate as the financing progresses. The funding comes ahead of OpenAI’s anticipated mega-IPO later this year, with Wall Street expecting further capital raises before a public debut.

Compute Is the New Oil

The capital injection is designed primarily to secure advanced chips and computing infrastructure.

OpenAI said it will deploy Nvidia’s latest Rubin systems, representing five gigawatts of computing capacity — enough energy to power millions of U.S. households. That scale highlights a defining theme of the AI cycle: frontier models now require industrial-level energy and hardware commitments.

For Nvidia (NVDA), the $30 billion investment deepens its financial ties to one of its largest customers. However, shareholders have recently pressured the chipmaker over its decision to reinvest heavily into the AI ecosystem rather than prioritize capital returns.

The interdependence has also revived concerns about “circular financing,” in which companies invest in key customers while simultaneously securing supply agreements. Critics argue such structures can blur the line between organic demand and strategically supported revenue.

Amazon Expands Strategic AI Footprint

Amazon (AMZN) is pairing capital with infrastructure.

Alongside its $50 billion commitment — beginning with an initial $15 billion investment — OpenAI will utilize two gigawatts of computing capacity powered by Amazon’s proprietary Trainium AI chips. The companies are also expanding a previously signed $38 billion cloud agreement, with OpenAI planning to spend an additional $100 billion on Amazon Web Services over eight years.

AWS will become the exclusive third-party cloud provider for OpenAI Frontier, the company’s enterprise AI platform for building and running agents. Importantly, OpenAI’s relationship with Microsoft remains intact, with Azure continuing as the exclusive cloud provider for its APIs.

The multi-cloud, multi-chip strategy reflects how hyperscalers are competing not just for AI workloads, but for long-term ecosystem control.

Competition Is Intensifying

The raise comes as Alphabet’s Google strengthens its AI position following the launch of Gemini 3, and as Anthropic continues to gain traction in enterprise AI applications. OpenAI, which has yet to turn a profit, is reportedly targeting approximately $600 billion in total compute spending through 2030.

At the same time, technology stocks have faced sharp declines in 2026 as investors question whether AI investments will generate returns sufficient to justify soaring valuations.

Still, OpenAI’s scale is formidable. The company reports more than 900 million weekly active users for ChatGPT and over 50 million consumer subscribers, with early 2026 pacing as its strongest period for new subscriber growth.

Why It Matters for Investors

This deal reinforces several market themes:

  • AI capital intensity is rising dramatically.
  • Infrastructure partnerships are becoming equity-linked.
  • Hyperscalers are competing for exclusive compute relationships.
  • Pre-IPO valuations are stretching toward trillion-dollar territory.

Whether these commitments ultimately deliver sustainable returns remains a key question for public markets. But for now, the AI capital formation cycle remains firmly in expansion mode.

Nvidia Stock Drops Despite Strong Earnings as AI Spending Questions Grow

Nvidia delivered another quarter of eye-catching growth. Investors still found reasons to sell. Shares of the AI chip leader fell as much as 5.6% Thursday after its fiscal first-quarter revenue forecast, while ahead of average Wall Street estimates, failed to ease mounting concerns about how long the artificial intelligence spending boom can last. The decline marked the stock’s sharpest intraday drop in three months.

On paper, the results were hard to fault. Nvidia projected fiscal first-quarter revenue of about $78 billion, topping the average analyst estimate of $72.8 billion, though some forecasts had climbed closer to $80 billion in recent weeks. For the fiscal fourth quarter, revenue surged 73% to $68.1 billion, beating expectations. Adjusted earnings of $1.62 per share and gross margins of 75.2% also edged past consensus estimates.

The company’s data center division — which includes its AI accelerators and networking products — generated $62.3 billion in quarterly revenue, above projections. That business has become the centerpiece of Nvidia’s growth story as hyperscale cloud providers and enterprises race to build AI infrastructure.

Other segments were softer. Gaming revenue of $3.73 billion and automotive revenue of $604 million both trailed analyst expectations. Ongoing memory supply constraints have weighed on certain product lines, highlighting that even Nvidia is not immune to broader semiconductor supply dynamics.

The market reaction underscores a key shift: Expectations are now extraordinarily high. After explosive gains over the past two years tied to generative AI demand, investors are increasingly focused on sustainability rather than acceleration.

CEO Jensen Huang pushed back against fears of an AI bubble during the earnings call, arguing that customers are already generating returns from their AI investments. According to Huang, expanding compute capacity directly supports revenue growth for Nvidia’s clients, reinforcing the case for continued infrastructure buildouts.

Still, questions remain. Nvidia disclosed $95.2 billion in purchase obligations, up sharply from $16.1 billion a year earlier. While those commitments reflect efforts to secure supply and meet anticipated demand — with shipments extending into calendar 2027 — they also raise the stakes if capital spending slows.

Geopolitical uncertainty adds another layer. The company has received limited U.S. government licenses to ship certain processors to China, but data center revenue from the country remains excluded from guidance. Tariffs and inspection requirements create additional friction in an already complex global supply chain.

At the same time, Nvidia and its competitors are announcing large, long-term agreements with major customers to lock in computing capacity. Nvidia recently disclosed that Meta Platforms plans to deploy “millions” of its processors in the coming years, while Advanced Micro Devices announced its own multibillion-dollar AI infrastructure deal. These agreements are designed to demonstrate durable demand, though some observers caution that increasingly intertwined supplier-customer relationships can complicate traditional demand signals.

For investors, Nvidia’s quarter reflects a broader capital markets dynamic heading into 2026. Growth is still robust, but markets are scrutinizing visibility, balance sheet commitments, and the durability of capital expenditures more closely.

The AI buildout remains one of the most significant investment cycles in technology history. Nvidia’s latest results suggest momentum is intact. The stock’s reaction shows that confidence in how long it lasts is now the real debate.

Google Updates Viral AI Image Tool With Faster, Smarter Nano Banana 2

Google is doubling down on generative AI with the launch of Nano Banana 2, the latest version of its viral AI image generator. The update, announced Thursday, is designed to make the tool faster, more precise and better at rendering text — a key improvement for use cases such as marketing mockups, greeting cards and branded visuals. The rollout underscores how aggressively large technology platforms are iterating in the increasingly competitive AI image and video market.

Shares of Alphabet traded lower alongside the broader tech market, but the Nano Banana refresh highlights the company’s continued push to integrate generative AI deeper into its Gemini ecosystem.

Nano Banana first launched in August and quickly gained traction online as users shared AI-generated images across social platforms. Google followed with Nano Banana Pro in November, built on Gemini 3 Pro, targeting higher-fidelity and more accuracy-sensitive use cases.

Nano Banana 2 is now positioned as the speed-optimized successor.

According to Google, the new model incorporates “advanced world knowledge,” pulling real-time information from Gemini to produce more accurate visual renderings. The company emphasized three primary upgrades: faster generation, improved instruction-following and more precise text rendering inside images — an area where AI image models have historically struggled.

While Nano Banana Pro will remain available for high-fidelity tasks requiring maximum factual precision, Nano Banana 2 is being positioned for rapid creation and integrated image-search grounding. The new version will replace its predecessor across Gemini’s Fast, Thinking and Pro tiers.

The move comes as AI image and video tools are becoming mainstream consumer products. Users can now generate increasingly sophisticated visuals from simple text prompts, blurring the line between professional and consumer-grade creative tools.

Competition in the space is intensifying.

OpenAI launched its video-generation model Sora in 2024, drawing massive demand. Adobe has continued expanding Firefly, integrating generative AI across its creative software suite. ByteDance has also introduced its Seedance video-generation tool, though it has faced legal scrutiny from major studios over alleged intellectual property violations.

The rapid adoption of AI creative tools has also fueled debate around copyright, training data and the protection of original content. Media and entertainment companies have raised concerns that generative models may infringe on protected works, increasing regulatory and legal uncertainty across the sector.

For investors, Google’s Nano Banana 2 rollout highlights a broader capital allocation theme in 2026: speed of iteration is becoming a competitive advantage in AI.

Large platforms are not only investing heavily in infrastructure — such as GPUs and data centers — but are also racing to deliver user-facing AI products that drive engagement, subscription upgrades and enterprise adoption.

The generative AI market is still in its early innings. However, with major players rolling out new versions in rapid succession, product cycles are shortening, and differentiation is increasingly tied to performance, reliability and integration with broader ecosystems.

Nano Banana 2 may be an incremental upgrade. But in today’s AI arms race, incremental improvements — delivered quickly — can shape market leadership.

Perfect (PERF) – Revenue Growth Story Intact


Wednesday, February 25, 2026

Patrick McCann, CFA, Research Analyst, Noble Capital Markets, Inc.

Michael Kupinski, Director of Research, Equity Research Analyst, Digital, Media & Technology , Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Q4 results. Perfect reported Q4 revenue of $18.1 million, up 14.2% Y/Y and largely in line with our estimate of $18.2 million, while adj. EBITDA of $1.4 million exceeded our forecast of $1.0 million, representing 8% margins. Excluding a one-time goodwill write-off, the company would have generated operating income, underscoring improving cost discipline and operating leverage.

B2C momentum the primary growth driver. Management noted that strong demand for AI-powered content creation is driving engagement across the YouCam app portfolio. Generative AI photo and video tools remain key contributors, and we believe Perfect’s expertise with these technologies positions it well to benefit from sustained demand for personalized, AI-enabled digital experiences.


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Equity Research is available at no cost to Registered users of Channelchek. Not a Member? Click ‘Join’ to join the Channelchek Community. There is no cost to register, and we never collect credit card information.

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

Nvidia and Meta Deepen AI Alliance With Millions of Next-Gen Chips

AI infrastructure is getting another massive upgrade. Nvidia and Meta have announced an expanded multiyear, multigenerational partnership that will deliver millions of Nvidia’s latest GPUs, CPUs, and networking products into Meta’s data centers. The move underscores just how aggressively the world’s largest tech platforms are investing in artificial intelligence — even as investors question the sustainability of that spending.

Under the agreement, Meta will deploy Nvidia’s Blackwell and next-generation Rubin GPUs to train and run AI models across its family of apps, including Facebook, Instagram, and WhatsApp. The chips will power everything from recommendation systems to advanced generative AI tools designed for billions of users worldwide.

Nvidia CEO Jensen Huang described the partnership as a deep integration across computing layers, from GPUs and CPUs to networking and software. The goal is to bring Nvidia’s full-stack AI platform into Meta’s infrastructure, allowing the company’s researchers and engineers to push the boundaries of large-scale AI deployment.

Importantly, Meta will use the chips both in its own data centers and through Nvidia’s Cloud Partner ecosystem, which includes providers like CoreWeave. That hybrid strategy gives Meta additional flexibility to scale workloads quickly without waiting for new facilities to come online.

Beyond GPUs, Meta is also rolling out Nvidia’s Grace CPU-only servers, with plans to adopt the next-generation Vera CPU systems in 2027. These CPU deployments are notable because they signal Nvidia’s growing ambition to compete more directly in the traditional server market long dominated by Intel and AMD. If Nvidia can establish a foothold in CPU-heavy environments alongside its GPU dominance, it could reshape the balance of power in enterprise data centers.

Meta also plans to integrate Nvidia’s Confidential Computing technology into WhatsApp, enhancing privacy protections by enabling secure data processing on GPUs. As AI systems increasingly rely on sensitive personal data, secure processing capabilities are becoming a competitive differentiator.

The announcement comes at a time when AI-related stocks have faced renewed scrutiny. Shares of Nvidia and Meta have cooled in early 2026 amid concerns that hyperscalers may be overspending on AI hardware. Companies such as Microsoft, Amazon, and Google have introduced their own custom AI chips, raising questions about whether Nvidia’s GPUs will remain indispensable.

There are also broader concerns about whether all AI workloads truly require high-performance GPUs, or whether specialized processors could handle certain tasks more efficiently. Yet analysts argue that Nvidia’s advantage lies in versatility. GPUs can support a wide range of AI applications, from training large language models to running inference at scale, while custom chips tend to be optimized for narrower use cases.

For Meta, the decision is clear: scale matters. Running AI at the level required to serve billions of users demands proven hardware, deep software integration, and reliable supply chains. By doubling down on Nvidia, Meta is signaling that it views AI not as an experimental feature, but as core infrastructure for its future.

The partnership reinforces Nvidia’s central role in the AI ecosystem — and shows that, despite market jitters, the largest tech companies are still betting big on next-generation computing power.