Co-founders Ayan Barua and Lauren Long started Ampersand after six years of living the problem. The thesis was simple: a developer should declare an integration once and have it work in every customer ...

Today, we're announcing $5.75 billion in new capital to continue that work amidst this AI era: $1.75 billion for seed and early-stage investing and $4 billion for growth, raised in a single close.

Bessemer is proud to announce our investment in Cognition, the company behind Devin. For the last three years, the story of AI has primarily been a story about assistance. Autocomplete got better, ...

The true test of a pricing strategy comes at renewal cycles. Here’s how Strella, Recall.ai, Graph AI, and Ada each monetized proof of ROI. Ask four successful AI founders how they priced their ...

In less than two years, coding agents and workplace automation tools on the endpoint have gone from being an edge case to a regular process inside enterprises. While the existing security tools on the ...

Speed is the moat. Tokenmaxxing is high. Comprehension debt is the new tax. Here’s how engineering leaders are shipping faster, experimenting without chaos, and building the organizational ...

The fastest Centaur in enterprise software history: how they got there and how they doubled to $200M ARR in less than six months.

AI is the most power-intensive workload in computing history. As of early 2026, 190 GW of hyperscale data center capacity has been announced across 777 projects. This includes ~148 GW planned, ~21 GW ...

In our latest Bessemer Community research, one key point of tension captured where most high-growth teams find themselves right now: founders and leaders are convinced operationalizing AI matters, but ...

Before writing (or generating) a single line of code, the hardest question for any early-stage AI startup to answer is figuring out what they should actually build, for whom, and what customers will ...

No human actually wants to do highly repetitive physical tasks or endure unsafe working conditions in factories or hazardous sites. That observation sounds simple, but the implications are not.

As compute costs fall and models mature, sustaining a competitive edge in global drug development requires innovation across the entire data infrastructure stack. Biology-native data, agentic ...