
Lovable confirms new $13.3B valuation, raises another $400M
THE SO WHAT
Hitting $500 million ARR and a $13.3 billion valuation with another $400 million raised shows AI-native apps can still command late-stage multiples. For incumbents, this is a warning that “it’s just a feature” thinking is risky — category-defining UX around AI can still carve out standalone giants.
READ THE SOURCE
MORE FROM THE WIRE
Startups & VentureIndex in talks to lead $500m round for DeepMind researcher’s new AI lab
A $500M first check into a new lab from a DeepMind alum says frontier-scale capital is now comfortable backing talent plus thesis, not just incumbents. If you’re building infra, evals, or tooling, assume another well-funded foundation model competitor is entering your pipeline and adjust your partnership and hiring roadmap accordingly.
Startups & VentureHow a $250 million acquisition collapsed into allegations of fraud and forged signatures
A $250M deal unraveling into fraud and forged-signature claims is a governance warning shot—late-stage AI and software M&A is moving faster than many control environments. If you’re buying or selling, tighten diligence on cap tables, signatures, and board approvals this week; don’t assume standard processes kept up with the last two years of growth.
Startups & VentureSilicon Data, which offers real-time compute pricing data to financial institutions and exchanges, raised a $30.5M Series A led by the Valor Atreides AI Fund
A $30.5M Series A for real-time compute pricing is a tell that GPU capacity is being financialized like a commodity. If your business depends on large-scale training or inference, expect more transparent—and more volatile—pricing; start instrumenting your workloads so you can arbitrage clouds, regions, and vendors instead of taking list price.
Startups & VenturePartnering with Preview: Lights, Inference, Action
Sequoia backing Preview is another data point that inference-time orchestration — not just bigger base models — is where venture dollars see defensible value. If you’re building in applied AI, expect investor diligence to center on how you manage context, tools, and latency at inference, not just your fine-tune story.