Trace.Space

Exciting announcement! 🚨 We have raised a $4M seed round from Cherry Ventures to continue building the future of AI-enhanced requirements management. Headlines around Western manufacturing focus on layoffs, factory closures, and products that fail to meet customer expectations. It is painful to see engineers at great companies struggle with outdated processes and legacy practices. Our mission is to give engineering organizations the tools to win back their market share.

We are hiring a Senior React Developer to lead our Front-end efforts! Remote anywhere in the EU. Great talent density in the team – that's a promise now and in the future! Plus, if you recommend someone and we end up hiring them you get any tech product up to EUR 1,500.

Ai Agents are impossible to build - EP #24 Ai Ranch Mikus Krams - requirements for hardware using AI #AIRanch #AI #aiagents #impossible #podcast

New AI Ranch episode is out! This time we talk to Mikus Krams who is the co-founder and COO of Trace.Space, a company that is building the next generation of requirements management software for hardware products. Go listen to it! https://lnkd.in/dQNp2sXY #AIRanch #AI #aihardware #entrepreneurship #podcast

🚨 New Year, New Speakers at TechChill 2025! 🚨 Start the year off right by getting inspired by incredible leaders in tech and business. And don’t forget—ticket prices go up on January 9, so grab yours now before they do! 🎟️ We’re excited to announce three amazing speakers: 🎤 David Hooker – Director of Brand at Printify Once a writer, David's journey took him through leading design teams for rockstars, scientists, and more. After transforming the brand at Prezi and TravelPerk, he's now on a mission to help people unlock their freedom at Printify. 🌍 Mikus Krams – Co-founder & COO at Trace.Space Born in Latvia, Mikus has lived across the globe and built his career in finance and operations at Lokalise and Chili Piper. Now at Trace.Space, he’s developing AI-powered software to save manufacturing companies in the US and EU. 🚀 Bret Waters – Entrepreneur & Investor Founder & CEO of three Silicon Valley software companies, Bret now teaches entrepreneurship at Stanford and invests in the next generation of global startups. 🎟️ Grab your ticket today before prices increase - https://lnkd.in/dJ6KsHCJ

Exciting to announce Trace.Space is coming to REConf! It was the first conference we went to after starting our company. Incredible concentration of engineers from the best companies in Europe 🇪🇺 Looking forward to catch up with friends in May. 🍻

Trace.Space product update (week 47) 🚀 New features: – Parameters! Add Parameter attribute to Items, to manage numerical values in Requirements, Tests, Designs etc. – AI autocomplete for Requirements authoring – More filtering options in global Filters ⚙️ Improvements: – Enhanced performanced - reduced loading time for right sidebar Tree and Doc view – Enhanced platform security – Numerous UI/UX improvements, fixes and stability improvements – Jira integration is GA!

Happening tonight, an interactive conversation with Mikus Krams of Trace.Space and Cyril Golub of Latvian Business Angels Network regarding deal terms and cap tables. We will go through the various terms and argue about what is fair and not fair. Hopefully with a bunch of disagreements so that it is not boring!

𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 𝐢𝐬 𝐋𝐢𝐤𝐞 𝐚 𝐑𝐚𝐫𝐞 𝐃𝐢𝐬𝐞𝐚𝐬𝐞 / 𝐖𝐡𝐲 𝐀𝐈 𝐒𝐭𝐫𝐮𝐠𝐠𝐥𝐞𝐬 𝐰𝐢𝐭𝐡 𝐒𝐜𝐚𝐫𝐜𝐞 𝐈𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧. Artificial Intelligence thrives on data—the more it has, the better it gets. In medical diagnostics, AI excels at detecting common diseases like melanoma because it can learn from a vast pool of information. In Australia alone, about one-third of the population will experience melanoma at some point. That's over 10 million cases, providing ample data for AI to analyze and recognize patterns. This wealth of information helps AI improve diagnostic accuracy and assist doctors in catching the disease early. But when it comes to rare diseases, AI hits a stumbling block. With so few cases, there's not enough data for the algorithms to learn from, making it tough for AI to identify these conditions accurately. The situation is similar in the world of engineering. While AI can easily access and learn from legal texts or literature—since they're widely available—engineering data is a different story. It's scarce and highly protected, much like data on rare diseases. Companies guard their engineering designs and specifications closely because they're core intellectual property that gives them a competitive edge. Without access to this critical information, AI can't learn or operate effectively in complex hardware engineering tasks. This lack of available data means AI can't make the same strides in engineering as it does in other fields. However, as technology advances and if ways are found to share data without compromising proprietary information, there's hope that AI could overcome these challenges. While it's a tough nut to crack today, the future may see AI playing a bigger role in engineering, complementing human expertise and pushing the boundaries of innovation.

Stay tuned for the next episode at AI Ranch with Mikus Krams; we dove deep into operations and methods that helped Lokalise get to a 50mil USD round and how AI is changing operations nowadays. Meanwhile, check out AI-enabled Trace.Space. The documentation platform for hardware product companies. #AI #COO #FutureWork #Hardware