iPronics presents the first plug & play general-purpose photonic processor

Boost applications with photonic processors for fiber transport, RF Photonics, and computing

Programmable Photonics for processing

iPronics is developing the innovative concept of general-purpose integrated programmable photonic systems, which are based on a common optical hardware configurable through software to perform multiple functions.

iPronics Smartlight Processor

  • Silicon Photonics chip (C-band), 72 tuning units in a hexagonal mesh configuration and 64 input/output ports.
  • User-friendly software with automatized functions, 1 year of free software updates included.
  • High performance building blocks included for 50, 100 and 200 GHz bandwidth filtering functions (programmable central wavelength and extinction ratio) and demultiplexing.
  • Laser 2nm range, central wavelength 1550 nm included.
  • Monitoring Unit with photodetectors at each optical output port.
  • Integrated Driving Unit with full operational control.

Our Benefits

Reconfigurable by software

iPronics SmartLight includes a friendly software interface that can be used even without prior experience on integrated photonics. By using proprietary optimization algorithms, the system is tolerant to faults and manufacturing defects, presenting self-healing and cooperative multi-tasking inherent behavior.

Boost your business

Products for application in a wide range of fields such as 5G & Beyond communication, data centers, artificial intelligence, sensing, autonomous driving, quantum computing and IoT.

90% Cost Reduction
95% Development Time Reduction

Avoid coming back to costly and time-consuming Multi-Project Wafer runs for any small modification in your photonic integrated circuit design. Eliminate 90% of non-recurring engineering costs and 95% in development times.

Photonic processing is the next big step for optical communications:

  • It eliminates electro-optical connections and moves data processing to the optical domain, drastically reducing power consumption
  • It scales down infrastructures in base stations, data centers and enterprise by parallelizing tasks using the same device

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