Eliyan hits $1B valuation and Simile raises $200M as AI infrastructure funding surges in late July 2026

Four funding rounds closed in the last week of July 2026 that collectively sketch the shape of enterprise AI investment right now: one at the chip level, one at the model-behavior layer, one inside industrial supply chain, and one in employer health. The deals are unconnected by syndicate but share a common thesis, that foundational infrastructure and workflow-specific AI are both attracting large checks simultaneously.

Eliyan reaches unicorn status on chip interconnect bet

Santa Clara-based Eliyan closed a $145 million Series C that was oversubscribed, valuing the company at $1 billion, according to Tech Funding News. Cisco is among the company's backers, a detail that matters for enterprise network operators evaluating where AI infrastructure spend is heading.

Eliyan builds interconnect technology for AI chips, the pathways that move data between processors inside large training and inference clusters. As model sizes grow, the bandwidth between chips, not just the compute on any single chip, becomes a primary constraint on cluster performance. That is the gap Eliyan is positioned to fill.

An oversubscribed round at a clean $1 billion valuation indicates that investors with hardware expertise, including strategic backers like Cisco, see the interconnect layer as non-optional infrastructure rather than a nice-to-have optimization. For procurement teams buying or specifying AI server infrastructure, the competitive landscape at the interconnect level is now a serious evaluation criterion.

Simile doubles its valuation in five months on behavioral AI

New York-based Simile raised $200 million in a Series B that valued the company at $2 billion, Tech Funding News reported on July 31. The timing is striking: its Series A of $100 million closed just five months earlier. That pace of re-rating is unusual even by 2026 AI funding standards.

Simile's product is not a general-purpose AI assistant or code generator. The company focuses specifically on predicting human behavior before an AI system acts, a capability aimed at reducing the category of errors that occur when automated systems make decisions that surprise or contradict what the human operator actually wanted. For enterprise teams deploying AI in customer-facing or operations-critical workflows, that error-reduction layer has a direct cost analog.

The speed of Simile's Series B suggests that enterprise buyers, or at least the investors betting on them, are treating behavioral prediction as a distinct and valuable capability rather than a feature that foundation model providers will absorb. CIOs evaluating AI governance and reliability tooling should treat Simile's trajectory as a signal that a dedicated market is forming in this space.

Intropy targets spare-parts procurement with Oxford-founded AI

Intropy, a UK-based startup founded by Oxford physicist Franziska Kirschner, closed an $11 million seed round backed by Felix Capital, according to Tech Funding News. The company is applying AI automation to spare-parts sourcing, one of the more stubbornly analog corners of industrial supply chain.

Spare-parts procurement presents a specific set of challenges that have resisted standard digitization: fragmented supplier catalogs, irregular demand patterns, and parts that are often described inconsistently across systems. Kirschner's background in physics and published research at Oxford gives the technical approach a different origin than most supply-chain software, which tends to emerge from logistics or ERP consulting.

At $11 million, the Intropy round is small relative to the others in this week's cluster, but seed-stage AI funding in industrial supply chain is notable precisely because the sector has been slow to attract deep-tech founders. Operations and procurement leaders in manufacturing, energy, and transportation should watch whether Felix Capital's backing accelerates Intropy's commercial traction over the next 12 to 18 months.

Function Health's $450M round reframes employer health purchasing

Function Health secured $450 million from General Catalyst, with the company's argument resting on a structural gap in the US healthcare system: more than 100 million Americans lack a primary care doctor, and for those who do have one, average appointment times leave little room for preventive screening, according to Tech Funding News.

The company's model centers on comprehensive lab testing and data-driven health monitoring as a substitute for reactive care. For employers and benefits teams, the operational relevance is direct: if preventive diagnostics can reduce downstream claims costs, the math on offering Function Health as a benefit starts to work. General Catalyst, which has a track record of health system investments, is the lead backer.

The $450 million figure puts Function Health among the larger single-round healthtech raises of 2026. Benefits directors and HR technology buyers evaluating next-cycle vendor additions should put Function Health's enterprise offering on their evaluation list, especially as employer-sponsored preventive care continues to attract scrutiny as a cost-management lever.

Read together, the four rounds reflect a market that is no longer betting exclusively on frontier model builders. Capital is moving toward the hardware layer beneath models, the behavioral guardrail layer above them, the workflow-specific automation layer within industrial operations, and the health infrastructure layer that touches employer benefits. The next signal to watch: whether Eliyan's interconnect technology surfaces as a named component in hyperscaler procurement disclosures, which would confirm that the unicorn valuation is grounded in contracted demand rather than forward speculation.