The SparkFun À La Carte (ALC) service offers a simple, point-and-click interface to design and manufacture custom boards. Its smart design, says the company, ensures that all connections have been made and that every board designed using the service is electrically sound.

Once designed, SparkFun builds and ships the boards within three to four weeks.

“Not everyone with an idea is a hardware engineer or has access to one to help bring their idea to life,” says Nathan Seidle, founder and engineer at SparkFun. “The beauty of ALC is that it does all the hard work for you. All you need to know is what parts you want to use, and our system will design all the traces and place the blocks for you, allowing anyone to create a custom-designed board.”

ALC includes a mix of “block” options:

  • Varied controller options encompassing ESP32 WROOM, ATmega328P, ATtiny84, SparkFun Artemis and SAMD51
  • Sensors from u-blox, Bosch, Microchip Technology, Sensirion, Texas Instruments and more
  • Joysticks, buttons, switches, trimpots, LEDs, buzzers and motors
  • Multiple connector options
  • RFID, Bluetooth, WiFi, LoRa and other transceiver options
  • Ability to integrate the Qwiic ecosystem of sensors, shields, LCDs, relays and accessories

Once a board has been built, users have the option to purchase fully routed design files. With these files unlocked, the design can be tweaked and customized as needed for traditional manufacturing through SparkFun or elsewhere.

“With SparkFun À La Carte, we’ve taken SparkFun’s years of board design and manufacturing knowledge and packaged them into an easy to use platform anyone can leverage to create custom boards,” says SparkFun CEO Glenn Samala. “With this offering, we hope to round out our service offerings and streamline our customer’s ability to reach proof of concept and bring products to market.”

SparkFun Electronics

Related articles:
SparkFun launches value-added services
Digi-Key PCB tool streamlines ordering, supports rapid prototyping
SparkFun Electronics expands open-source machine learning line


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