AI infrastructure products under Emisha Labs for hyperscalers, colocation, on-prem data rooms, and secure government environments.

Emisha Labs designs customized Sol-X, Sol-E, optical I/O, rack-scale, and secure data room solutions for customers facing AI data movement, power density, cooling, latency, and secure operations challenges.

Products offered

Customized product pathways, not one-size-fits-all hardware.

Emisha products are configured around the customer’s workload, facility constraints, security boundary, power profile, and deployment model.

Sol-E AI Electrical Compute Platform

Customized electrical compute, custom IC, and accelerator pathway for AI workloads requiring electronic logic, sub-15nm roadmap alignment, memory/interface integration, and a stick-in-package optical I/O concept that plugs into the server rather than operating as a separate external unit.

Rack-Scale AI Systems

Customized rack and pod designs for hyperscale, colocation, government, and enterprise on-prem data rooms. Designs can include compute, optical interconnect, power distribution, structured cabling, secure management, telemetry, airflow, and phased upgrade planning.

Optical I/O and Interconnect

In-package and board-level optical I/O concepts for high-bandwidth server interconnects, GPU/accelerator communication, rack-to-rack optical data movement, and reduced electrical bottlenecks.

On-Prem AI Data Rooms

Secure AI infrastructure modernization for enterprise and government data rooms, including customized rack layouts, network segmentation, SCIF-adjacent workflows, cloud backup, storage, NOC integration, and secure monitoring.

AI Pilot Systems

Proof-of-concept deployments for paid evaluations, pilot racks, photonic interconnect testbeds, customized reference designs, and workload-specific integration before scale-up.

Customer segments

Where Emisha fits in the AI infrastructure market.

Emisha focuses on customers that need higher throughput per watt, better data movement, secure infrastructure, custom rack integration, and long-term photonic compute adoption without replacing every existing system at once.

Hyperscalers: custom rack pods, optical interconnect pilots, AI cluster data-movement studies, secure storage, and transition pathways toward photonic compute.
Colocation and AI cloud providers: deployable rack designs, power/cooling optimization, GPU-cluster interconnect support, telemetry, and customer-specific secure infrastructure.
On-prem enterprise data rooms: AI-ready modernization, compact rack systems, secure storage, network segmentation, and integration with existing IT operations.
Government and defense: SCIF cloud storage, CMMC Level 3 project environments, secure rack/data-room architecture, mission AI pilots, and controlled technical data workflows.
Deployment path

From use case to rack-scale implementation.

1. Workload & facility assessmentAI workload, data movement, rack power, fiber paths, security boundary, cooling approach, and operator constraints.
2. Product designSol-X, Sol-E, optical I/O, rack layout, power/network, telemetry, software control, and storage architecture.
3. Prototype / pilotReference rack, testbed, photonic interconnect pilot, secure storage workflow, and acceptance metrics.
4. Manufacturing & scale-upPartner-enabled manufacturing, integration, validation, field support, and phased rollout.