Piper Sandler named five infrastructure software companies — Elastic, GitLab, MongoDB, Snowflake and Atlassian — as the main beneficiaries of corporate efforts to cut AI token costs, pointing to early deployments where token usage fell 50% to 75%. The firm’s argument is that the customer data these platforms already store cuts the number of tokens an AI agent needs to process. The five have not traded as a group, and none breaks out context-layer revenue in its filings.
Piper Sandler told clients on Wednesday that five infrastructure software names are positioned to solve the problem chief information officers complain about most: running AI agents at scale costs far more than anyone budgeted.
The note, led by analyst Rob Owens, named Elastic, GitLab, MongoDB, Snowflake and Atlassian as the primary beneficiaries. Its argument is that the customer data these companies already store can cut the number of tokens an AI agent needs to process, which lowers the cost of running it.
Clean data shrinks the token count
Owens wrote that the proprietary data already sitting inside these platforms can make models “significantly more accurate and efficient while dramatically reducing token usage costs.” That will let companies expand AI adoption without costs rising too much.
Early deployments showed token usage falling by 50% to 75% when clean organizational context was fed directly to the agent. Models use fewer tokens and answer faster when handed organized data instead of messy data.
Cheaper tokens, larger bills
Token prices fell this year, yet AI bills went up anyway. Owens noted that output tokens on newer frontier models run about 50% cheaper than the prior generation, yet improved reasoning capabilities caused consumption to increase.
Reasoning models think in tokens, so a single query that once cost a few hundred tokens can now cost tens of thousands. Vendors price context layers on consumption rather than per seat, and the per-seat model is what the market fears AI will destroy as headcounts shrink.
The five stocks have not moved together
MongoDB has been the standout, with a market capitalization near $27.7 billion in mid-July, up more than 62% from last year. The stock traded around $307 on July 21.
Elastic went the other direction, with shares near $50 in recent trading and Jefferies cutting its target to $75 from $95 while keeping a Buy rating. GitLab has been the weakest of the five, carrying an average Hold rating and a 12-month target of $34.50, roughly 4% above where shares trade.
Snowflake sits in between, with 33 analysts rating it Strong Buy at an average target of $302.26. Atlassian shares sat near $86, well below the average analyst target of $139.70.
Where the call fits against the software selloff
The S&P 500 software industry index has fallen more than 25% from its October highs. The iShares Expanded Tech-Software Sector ETF is down 13% this year, while the S&P 500 has gained close to 10% over the same stretch.
Snowflake, MongoDB and Elastic all report consumption metrics that investors can check against the call. But none of the five breaks out context-layer revenue as its own line item in filings, which means investors are betting on an analyst estimate rather than a disclosed number.
Source: TheStreet
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