MarketBeat analyst Thomas Hughes argues that the recent selloff in cloud software is overdone and that three cloud-native names—MongoDB, GitLab, and Snowflake—look attractive on the dip because their earnings and AI relevance are stronger than their stock prices imply.
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Thomas Hughes’s core thesis is that the current tech/software drawdown has pushed down a group of cloud-native software names too far, and that the disconnect between fundamentals and price action is creating a buying opportunity. He argues that these businesses are not being displaced by AI; instead, they are part of the infrastructure that AI needs to function, especially around data management, developer collaboration, and cloud data platforms. He starts with MongoDB, framing it as a database company whose document-oriented structure is better suited to flexibility, scalability, and AI use cases than traditional table-based storage. He says the latest results were strong on both top and bottom lines, with revenue growing nearly 27%, margins solid, and full-year guidance still strong despite a somewhat soft Q1 guide. …
Near term, these names are tradable only if the support retests hold and the rebound attracts follow-through; otherwise the current bounce could fail inside a still-weak software tape.
Over the next few months, the base case is a gradual repricing higher if earnings stay strong and AI-related demand continues to show up in client growth, retention, and guidance.
Longer term, the transcript argues that cloud-native software is part of the AI infrastructure layer, so selective platforms with real enterprise stickiness could benefit from the AI cycle rather than be disrupted by it.
The sell-off in these cloud-native software stocks is overblown because AI cannot function without them.
The speaker argues these cloud-native software companies are critical to AI infrastructure, so AI's growth will drive their growth, making the recent downturn excessive.
AI models will not disrupt established niche software players — AI is enhancing these businesses, not replacing them.
Speaker cites NVIDIA CEO Jensen Huang's view and argues AI models are being used by these software companies internally and for customers, enhancing rather than disrupting their businesses.
MongoDB had a blowout quarter with revenue growth of nearly 27%, accelerating both sequentially and year-over-year.
Speaker cites the specific revenue growth rate and that it accelerated on both a sequential and YoY basis, with margins also strong.
What do the three cloud software companies have in common?
Thomas says they are cloud-native software companies that are critical to AI infrastructure. He argues the recent sell-off is overblown, recent reports were solid, and institutions and analysts still support the names.
Which cloud company is the first one on the list?
He identifies MongoDB and explains that its flexible document database model is useful for AI and scalability. He says earnings were strong, guidance had a small near-term hiccup, but the stock has already begun rebounding and upside remains in the double digits.
How does MongoDB support AI growth instead of getting displaced by it?
Thomas says MongoDB's data structure is useful for training models and inference, and that its scalable approach makes it important for data management in AI-era data centers.
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