DoubleAI Unveils First Code‑Execution Model, Secures $220 Million Funding

How Eclipse Achieves Performance Gains

Tel Aviv startup DoubleAI announced today the launch of its inaugural code‑execution engine, designed to boost GPU and CPU efficiency for developers. The company also revealed a fresh $220 million financing round, led by major venture firms, and disclosed that it has acquired 1,000 Nvidia B300 chips to support the new platform.

The new model, dubbed „Eclipse,” is engineered to translate high‑level programming languages into optimized machine‑level instructions that can run faster on both graphics and central processing units. By leveraging advanced static analysis and just‑in‑time compilation techniques, Eclipse claims to reduce execution times by up to 30 percent on standard benchmarks, while lowering power consumption. DoubleAI’s CEO, Amir Katz, said the technology is ready for integration into existing development pipelines and can be accessed via a cloud‑based API.

Why the $220 Million Infusion Matters

Eclipse’s core innovation lies in its hybrid optimization engine, which combines static code analysis with runtime profiling. Developers submit source code in languages such as Python, C++, or Java, and the engine generates a low‑level representation that is then mapped onto the underlying hardware architecture. By tailoring instruction streams to the specific capabilities of GPUs and CPUs, the platform eliminates unnecessary data movement and instruction stalls.

During internal testing, DoubleAI reported that Eclipse achieved a 28 percent speed increase on machine‑learning workloads compared to conventional compilers. The company also highlighted a 12 percent reduction in energy usage, a key metric for data‑center operators. „Our goal is to make high‑performance computing accessible without requiring deep hardware knowledge,” Katz explained. „Eclipse lets teams focus on algorithm design while the engine handles the intricacies of hardware acceleration.”

What Does This Mean for Developers and Cloud Providers?

The recent capital raise brings DoubleAI’s total funding to over $300 million, positioning it among the most well‑capitalized AI infrastructure firms in the region. Investors cited the company’s strong technical foundation, growing customer base, and the strategic timing of its product launch as reasons for backing. The infusion will accelerate product development, expand the team of hardware engineers, and fund the acquisition of additional Nvidia B300 GPUs, which are essential for scaling Eclipse’s cloud service.

The B300 chips, known for their high throughput and low latency, enable DoubleAI to offer competitive performance to enterprises that rely on GPU‑accelerated workloads. By securing a sizable inventory of these processors, DoubleAI can avoid supply bottlenecks that have plagued the industry in recent years. „Having a dedicated supply of B300s gives us the flexibility to meet demand quickly and maintain consistent performance guarantees,” Katz noted.

Frequently Asked Questions

The launch of Eclipse could shift the balance of power in software development. By abstracting hardware complexities, the platform may lower the barrier to entry for small teams that lack specialized expertise in GPU programming. Cloud providers could integrate Eclipse into their managed services, offering customers a turnkey solution that delivers higher performance without additional configuration.

However, the success of Eclipse will depend on its ability to support a broad range of use cases and maintain compatibility with existing ecosystems. Critics point out that the technology’s effectiveness may vary across different workloads, and that the initial cost of adopting a new compiler could deter some organizations. DoubleAI’s roadmap includes expanding language support and providing detailed profiling tools to help developers fine‑tune performance.