Trace.Space, a SaaS Startup with headquarters in Latvia that develops AI-powered solutions for engineering product development, has raised $1.5 million in a pre-seed round of funding from investors led by Fiedler Capital.
Participants in the round included Nebular, Tiny VC, Foreword VC, Charlie Songhurst, a former general manager at Microsoft, and Change Ventures.
The most ideation stage funding has been raised by Baltic founders in the most recent capital round of SaaS Startup.
Budapest, Hungary is home to the venture capital company Fiedler Capital. The VC makes investments in pre-venture, early seed, and leading or co-leading pre-seed deals. Fiedler Capital issues checks in the range of €50 and €750K.
“We all take the world that has been constructed around us for granted,” says Robert Hegedues of Fiedler Capital. the aircraft you travel in, the automobiles you drive, and the smartphone you’re probably using to read this. A trace a space team is developing a tool for the unexplored realm of artificial intelligence, one of the most revolutionary new technologies that will revolutionize the planet.
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Contrary to contemporary productivity tools like Slack or Figma, according to Trace.Space, engineering projects in the real world are typically operated on outdated business software with a dated user interface, a monolithic architecture, and high annual subscription prices.
The technologies used by engineering teams for requirements management are old, awkward, and burdensome, according to Janis Vavere, co-founder and CEO of Trace.Space. Due to its invisibility and lack of glamour, a billion-dollar market has gone untapped while software for subsequent stages of product development has already advanced.
“Initially, Trace.Space wants to modernize the fundamentals of requirements management before moving on to other stages of product development, says Vavare.
Trace.Space, which was established in 2022 by Janis Vavere, Mikus Krams, and Karlis Broders, has created AI-powered API-first software for complicated engineering product creation.
The program provides AI-powered capabilities for controlling 80% of the product development lifecycle to producers of industrial and automotive products.
In Q2, 2023, Trace.Space intends to deploy its initial product iteration. For engineering teams, it will include requirements management, which is the procedure for gathering, preserving, and verifying requirements for the product being developed.
Engineering teams will be able to document and amend requirements 10x faster thanks to the incorporation of the GPT algorithm in Trace.Space’s requirements management solution.
Customers may anticipate higher-quality goods with a quicker time to market as a result, according to the business.
The business claims that its software architecture was developed for a non-linear process of product creation, allowing clients to produce an illimitable amount of product variations.
Image Credit: Trace.Space
