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Investing.com -- Loop Capital downgraded MongoDB (NASDAQ:MDB) to Hold from Buy and slashed its price target to $190 from $350 in a note Tuesday. 

The firm highlighted concerns over slowing adoption of the company’s Atlas platform and delayed benefits from artificial intelligence (AI) workloads.

“Our most recent industry checks indicate that its highly strategic Atlas platform continues to show lackluster market adoption,” Loop Capital analysts wrote. “This decelerating trend could continue, which we believe could result in slower ramp of AI-related workloads on the Atlas platform.”

Loop warned that while AI hype continues to grow, MongoDB may not see a proportional benefit in the near term. 

The firm noted that MongoDB’s target market for cloud database platforms remains “highly fragmented,” with organizations unlikely to standardize on a single vendor like MDB for all AI deployments. 

“This scenario will likely result in a slower ramp of AI-related workloads running on the MDB platform vs. the pace of overall AI deployments,” the analysts said.

Additionally, industry contacts are said to have told Loop that large enterprises may be less inclined to consolidate their database platforms due to GenAI reducing development complexity. 

“This could lead to organizations opting for low-cost alternatives, including open source platforms such as PostgreSQL,” explained the firm.

Despite heavy investment in targeting large enterprises, Loop sees limited progress. 

“The need to consolidate and standardize on one platform within a large organization to generate more efficiency and lower maintenance cost is becoming less relevant,” the note said.

Loop did acknowledge MongoDB’s long-term strengths, including “a large, loyal community consisting of 7M+ developers,” but flagged short-term risks, including transition-related uncertainty as new CFO Mike Berry joins the company later this month.

While first-quarter estimates remain unchanged, Loop lowered its Atlas growth trajectory going forward due to persistent weakness in new workloads and a slower AI ramp.

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