LIVE WEBINAR -
ZEPHYR
X
KAPA
Thursday, July 16
10:00 PT / 13:00 ET / 19:00 CET
45 minutes | Live demo, with Q&A
Speakers
Developer Advocate
The Zephyr Project
Emil Sorensen
CEO, Founder
Kapa
Save your seat
Free, live, and recorded. Reserve your spot below
WHY GENERIC AI SOLUTIONS FALL SHORT
A general model guesses
Generic AI tools are not built for this kind of complexity. They blend everything they have ever seen and produce a fluent, plausible answer, whether or not it is correct for your SDK, your board, or your version.
Why it matters herE
In embedded, a confident wrong answer is dangerous
Damaged hardware. Silent runtime bugs that only surface in the field. Safety and compliance failures. The cost of a hallucination is not a re-prompt, it is a recall.
What "grounded" actually means
Why generic LLMs fail on embedded, and what grounding looks like in practice: evals, refusal, and citations.
Trained only on real sources
How AI built on docs, source code, GitHub PRs, and forum answers handles device trees, Kconfig, and version migrations.
Knowledge inside the IDE
What it looks like to bring your docs and SDK knowledge into the IDE via MCP, ending in working code.
Make your documentation AI-ready
How to prepare your own hardware docs and SDKs, with analytics that show exactly where developers get stuck.
Deploying AI assistants on your technical documentation
Get answer in your IDE
Via MCP, the docs and SDK knowledge come to where developers already work, ending in working code.
See where devs get stuck
A quick look at the analytics: top questions and documentation coverage gaps.
Benjamin leads developer advocacy for Zephyr, the Linux Foundation RTOS that runs on 1,000+ boards and ships in over 10M devices. He is a long-time embedded and IoT engineer and maker.
Emil Sorensen, CEO and Founder
Emil co-founded kapa.ai to help technical teams turn their docs and source into accurate AI assistants. kapa now answers more than 30M developer questions for 200+ companies, including OpenAI, Silicon Labs, and Nordic Semi.
Save your seat
Free, live, and recorded. Reserve your spot below
How is this different from just using ChatGPT or Copilot?
Generic models guess from everything they have seen, which is how you get confident, wrong answers. kapa is grounded only in your real sources, docs, source code, GitHub PRs, and forum answers, and it cites them. When it is not sure, it says so instead of hallucinating.
How does it handle multiple versions of the same SDK?
It reasons across versions instead of pointing you at a single guide. We will demo a live "migrate from Zephyr 4.3 to 4.4" question so you can see it in action.
What happens when the docs are wrong or out of date?
Answers are tied to their sources, so fixing the source fixes the answer. The analytics also surface where documentation is missing or contradicts itself, so you know what to fix first.
Can it work inside our IDE, and how hard is it to set up?
Yes, via MCP. We will show the same question answered inside the IDE, ending in working code, and walk through what it takes to set up.
How does an open-source project or hardware company get started?
Whether you are an open-source project or a hardware company, we will show the first step to making your docs AI-ready and what it takes to get there.