For an electrical engineer, the first step in building a new device is often the most tedious: finding the right chip. It involves cross-referencing datasheets from dozens of manufacturers, comparing obscure parameters like slew rate and quiescent current, and navigating a fragmented landscape of distributor catalogs. It is a process that can consume days of an R&D team's time before a single line of circuit design is drawn. In Boise, Idaho, a pair of recent engineering graduates are betting that a conversational AI can cut that time to minutes.
QTex AI, founded in 2024 by Chris Dagher and Oliver MacDonald, is developing PartWise, a SaaS platform they describe as a ChatGPT for electronic components [BoiseDev, Oct 2025]. The premise is straightforward. An engineer can describe a needed function in natural language,"a low-noise operational amplifier for a sensor interface, 5V supply, in a small package",and the system returns a ranked list of suitable parts, complete with availability, pricing, and links to technical documentation [Trailhead]. The goal is to streamline the sourcing, optimization, and management of components, a foundational but often painful layer of the hardware development stack.
A wedge into engineering workflows
The bet is not on creating a new database; established players like Octopart and Findchips already aggregate component information. The differentiation QTex AI is attempting lies in the interface and the intelligence layer. By applying large language models to a structured corpus of component data, the platform aims to interpret ambiguous engineering intent and filter results based on a deep understanding of electrical parameters. This moves beyond keyword search into a form of technical recommendation. For a team of two founders who are themselves navigating the final stages of academic engineering projects,Dagher is a Ph.D. candidate in computing, while MacDonald recently completed a degree in engineering with a robotics focus,the pain point is intimately familiar [Boise State News, June 2025]. Their combined R&D experience, cited as over ten years, forms the initial dataset and design intuition for the tool [QTex AI website].
Validation through competition, not capital
In the absence of disclosed venture funding, QTex AI's early traction is measured in prize money and local accolades. This path is a deliberate feature of the Boise startup ecosystem, where programs like Venture College and competitions like Boise Entrepreneur Week provide non-dilutive capital and validation. The company's recent wins are notable:
- Boise Entrepreneur Week Championship. In October 2025, QTex AI won the event's top prize, netting $50,000 [BoiseDev, Oct 2025].
- Idaho Entrepreneur Challenge. The team secured first place in the 2024 statewide competition [Boise State News, Sep 2025].
- Startup World Cup Qualifiers. As Venture College alumni, they advanced to regional qualifiers for the global pitch event [Boise State News, July 2025].
This string of successes suggests a compelling narrative and product demo that resonates with judges, often local business leaders and investors. It has provided the runway to continue development without the immediate pressure of a priced equity round. The founders' backgrounds are summarized below.
| Founder | Role | Background |
|---|---|---|
| Chris Dagher | CEO | B.S. in Engineering (2023), Ph.D. candidate in Computing at Boise State, research in AI and robotics [Boise State School of Computing]. |
| Oliver MacDonald | CTO | B.S. in Engineering Plus Robotics (2024), Boise State University [Boise State News, Sep 2025]. |
The incumbent landscape and the integration challenge
The primary competitive pressure comes from the entrenched workflows built around established parts search engines. Engineers have used tools like Octopart for years, and they are often integrated directly into professional computer-aided design (CAD) software like SnapEDA. For QTex AI's PartWise to displace these habits, it must prove to be not just incrementally better, but fundamentally transformative,saving hours, not just minutes. The risk is that the product becomes a helpful auxiliary tool used occasionally, rather than the primary sourcing environment. Furthermore, the accuracy of its AI recommendations is paramount; a single erroneous part suggestion that leads to a design respin would destroy trust. Without published benchmarks or peer-reviewed validation of its model's precision, the platform relies on user testimonials and demonstrable speed in a controlled pitch environment.
The path forward likely hinges on a clear go-to-market motion. The company could target small and midsize electronics firms or academic research labs where procurement processes are less rigid and the pain of inefficient search is acutely felt. A deeper integration with CAD tools would be a logical, though technically demanding, next step to move from a standalone web app to an embedded part of the design workflow.
For the electrical engineer today, the standard of care is a manual, multi-tab process. It involves consulting distributor websites, manufacturer parametric search tools, and aggregated databases, often while simultaneously reading PDF datasheets to confirm compatibility. It is a context-switching heavy task that pulls focus from creative design. QTex AI is betting that a conversational interface can collapse that complexity, serving a population of engineers who simply need the right component, faster. The next twelve months will show if competition prize judges see the same potential as the engineering teams they are building for.
Sources
- [BoiseDev, Oct 2025] Boise tech startup wins Boise Entrepreneur Week championship | https://boisedev.com/news/2025/10/15/parts-sourcing-tech-startup-wins-boise-entrepreneur-week-championship/
- [Trailhead] QTex AI: Accelerating the Future of Electronics Design | https://trailheadboise.org/qtexai/
- [Boise State News, June 2025] Alums' startup transforming engineering efficiency with artificial intelligence | https://www.boisestate.edu/news/2025/06/06/alums-startup-transforming-engineering-efficiency-with-artificial-intelligence/
- [QTex AI website] About | QTex AI | https://qtex.ai/about
- [Boise State News, Sep 2025] Get that pitch ready: Bronco Entrepreneur Challenge launches | https://www.boisestate.edu/news/2025/09/25/get-that-pitch-ready-bronco-entrepreneur-challenge-launches/
- [Boise State News, July 2025] Venture College alumni advance to Startup World Cup Regional Qualifiers | https://www.boisestate.edu/news/2025/07/07/venture-college-alumni-advance-to-startup-world-cup-regional-qualifiers/
- [Boise State School of Computing] Chris Dagher - School of Computing | https://www.boisestate.edu/computing/about-us/computingdirectory/current-students-directory/chris-dagher/