Weekly Pre-IPO Stock Secondary Market Update | September 22, 2026

Unconventional AI is attempting something few infrastructure companies dare to try: replacing the compute architecture that has powered computers for the past 60 to 70 years. Founder Naveen Rao, whose MosaicML now accounts for roughly a quarter of Databricks revenue following its acquisition, raised a reported $475 million seed at a $4.5 billion valuation to build brain-inspired, dynamical-system chips designed alongside biologists. The thesis is simple. Energy is the binding constraint on AI, and every token and API call ultimately prices back to power. The human brain runs on roughly 20 watts, and the company's stated target is a 1,000x reduction in inference power. Its first model, Un-0, already matches state-of-the-art image diffusion while running on a software simulation of the chip. Demand is not the problem, with Google alone processing more than 3.2 quadrillion tokens per month and premium AI subscription tiers still selling out. We view energy efficiency as the defining infrastructure trade of the next decade, and the milestone that matters here is working silicon, not simulation.

TypeSafe AI attacks the same cost curve from the model side. Founder Diogo Almeida, a former OpenAI researcher behind the InstructGPT and RLHF (reinforcement learning from human feedback) work that became ChatGPT, emerged from two years in stealth with a $40 million DCVC-led seed. Its model, Jev, outputs structured decisions rather than English text, letting machines communicate in their own language instead of translating everything into prose. Pricing is $0.042 per million input tokens with 70 to 500 millisecond response times, and within days Vercel called it the fastest-adopted model in the history of its AI Gateway. The dynamic mirrors China, where GPU constraints pushed labs toward software efficiency and ultimately into open source leadership. Power and token scarcity will now force the same innovation in the US. Both TypeSafe and Unconventional remain early, and our preference is to underwrite companies once product, revenue, and a visible addressable market are in hand. Still, the arrival of two architectures this different is the clearest signal yet that AI remains in its first inning.

ElevenLabs Reception marks the voice leader's move from infrastructure into outcomes. The product is a 24/7 AI receptionist that answers calls, books appointments, and speaks more than 70 languages for roughly $29 per month. The economics are striking. One business owner pays $80,000 per year for a single offshore employee whose only job is to call new leads within five minutes, day or night, because speed to lead is his single biggest driver of new revenue. The broader point is that AI applications are converging on outcomes rather than categories. A CEO buying a booked meeting does not care whether it came from a voice company like ElevenLabs, a customer service platform like Sierra, or an enterprise search company like Glean. The winners will be those with the deepest access to company data, workflows, and context, and we expect six to nine months of learning before these agents perform at full capacity. Sales and marketing may prove to be the biggest near-term beneficiary of the AI cycle.

Shield AI is reportedly in talks to raise at a valuation of at least $20 billion, up from $12.7 billion in March. The company is guiding to 80% revenue growth and more than $540 million in 2026 revenue, up from $276 million in 2024. Hivemind, its autonomy software embedded across US military aircraft and drones, anchors the software narrative. V-BAT and the upcoming X-BAT, however, make this a hardware business priced at roughly 37x 2026 revenue, a multiple we find difficult to justify outside of a sector leader like Anduril, now at roughly $120 billion implied valuation. Defense budgets are finite, incumbent primes are entrenched, and no startup is likely to capture Google-like market share. The path to sustained growth likely runs through a Palantir-style expansion from government into commercial markets such as stadium and office security. Absent that, we frame defense tech as a durable value franchise with margin expansion and eventual dividend potential rather than a growth story. Castelion illustrates the entry-point discipline required, since a 3x return from a $13 billion valuation implies a $39 billion missile company within five years.