Verda
Verda operates a full-stack AI cloud platform providing on-demand access to NVIDIA GPUs for the entire AI lifecycle, from rapid prototyping to foundation training and scalable inference. The platform offers self-service GPU instances, instant clusters with InfiniBand interconnect, serverless containers, and storage solutions, all managed through a console, API, or CLI. Verda's vertically integrated approach—owning data centers, hardware, and the cloud platform—delivers predictable cost, performance, and reliability, with confidential computing options for security-sensitive workloads.
- Artificial Intelligence
- AI Agents
- Clean Technology
- Developer Tools
- Energy
- Software Only
Funding
Raised to date
$450MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
$195.1M across 4 disclosed rounds
SV$117M · Series A
Announced Apr 2026
Disclosed cumulative: $195.1M
Reported total $450M
Incomplete round history. $254.9M of the $450M reported total isn’t matched to a known round.
Founders
Founder details are not available yet.
Product
Problem
AI teams face significant friction when trying to access the massive compute resources required for training and running large models. Traditional cloud providers offer limited GPU availability, complex procurement processes, and unpredictable pricing, forcing teams to wait weeks for capacity or over-provision to meet demand, which slows down innovation and increases costs.
Solution
Verda operates a full-stack AI cloud platform that provides fast, on-demand access to the latest NVIDIA GPUs, from single instances to multi-rack clusters with InfiniBand interconnect. The platform covers the entire AI lifecycle—enabling rapid prototyping, foundation model training, and scalable inference—all through a self-service console, API, or CLI. Verda manages everything from physical data centers and hardware to the cloud platform itself, offering predictable cost, performance, and reliability. The company also includes an in-house AI Lab that contributes to frontier research and open-source projects, and offers confidential computing solutions with hardware-attested inference and fine-tuning for enhanced security.
Target Audience
Primary customers are AI research teams, machine learning engineers, and enterprises that need scalable, on-demand GPU compute for training, fine-tuning, and inference workloads, as well as organizations with strict data sovereignty and security requirements based in Europe and globally.
Features
- GPU instances: Fast access to the latest NVIDIA hardware including GB300 NVL72, B300, B200, H200, H100, and A100 configurations with high-bandwidth memory
- Instant clusters: Self-service GPU clusters with InfiniBand interconnect, scalable from a single tray to 2+ racks with NVLink connectivity
- Serverless containers: Auto-scaling GPU containers for inference and batch jobs, eliminating manual capacity management
- Storage solutions: High-speed NVMe block storage, POSIX-compliant shared filesystem, and OCI-compliant container registry
- Confidential computing: Hardware-attested inference and fine-tuning for security-sensitive workloads, with industry-first support of 8× NVIDIA HGX™ B300 and B200
- Full programmatic control: API access to manage GPU resources via external code, alongside comprehensive documentation and community forum
- Secure and compliant: SOC 2 Type II and ISO 27001/27017/27018/27701 certified, GDPR compliant, powered by 100% renewable energy
- AI Lab: In-house research team that runs real workloads on the platform, working on GPU utilization improvement, inference optimization, and kernel engineering