Avoca, founded by MIT grads Tyson Chen and Apurva Shrivastava, announced on April 27 that it has raised more than $125 million across seed, Series A and Series B rounds at a $1 billion valuation. Meritech and General Catalyst led the Series B; Kleiner Perkins led the earlier A. The company sells AI agents that handle inbound calls, chat, email and SMS for HVAC, plumbing, roofing, automotive and moving-services operators — and books outbound campaigns and CSR coaching on top.
What's notable is the segment, not the funding number. The US services trades are a $1.5-trillion-plus economy whose primary technology bottleneck is missed calls — owners routinely say a plumber or HVAC dispatcher loses 20-30% of inbound demand simply because the phone rings while a technician is on a job. Avoca says it is on track to book $1 billion in jobs this year, which is a useful concrete number in a market where 'AI agent' demos rarely come with revenue attached.
The story is part of a broader rotation in 2026 venture funding away from horizontal foundation models and toward vertical agent platforms wrapped around specific workflow pain. Companies like Avoca, Crosby (legal), Harvey (law firms) and EvenUp (personal injury) sell less raw intelligence and more deterministic, integrated automation — the model is a component, not the product.
Takeaway for learners: if you want to ship AI to actual customers in 2026, the highest-leverage skill set is not training models. It is integrating LLMs into a vertical's existing systems — telephony, CRMs, dispatch software, billing — and proving that the agent reliably converts demand the human team would otherwise miss. The wedge is operational, not algorithmic.