Launch HN: Opusense (YC X25) – AI assistant for construction inspectors on site
Here’s a video: https://www.youtube.com/watch?v=u3Pi1iih1_Y.
Before this, I (Roya) worked in human-machine interaction at Huawei, and before that as a construction site inspector for civil engineering firms. I have a PhD in Civil Engineering, and in my experience reporting was by far the most tedious and mind-numbing part of the job.
You’d walk around a site all day taking short notes (maybe, often you'd rely on memory) and snapping photos, then go to three more sites before finally making it back to the office and try to remember everything you wanted to write. Sometimes you’d fill in gaps from memory or you’d keep it purposefully vague. Reports had to be consistent, branded, and checked by senior engineers. It was a huge time sink across the team.
Writing reports was the worst part of the job, so we built Opusense to get rid of it. On-site, users type or dictate short notes (e.g. “rebar exposed east end of slab”), and the tool turns them into full sentences, paragraphs, tables, or photo captions in a report template that matches the firm’s format. You can work offline, and it syncs automatically when back online.
Most inspection and reporting tools are built for checklist-style workflows (which is great for home inspections or punch lists), but civil, structural, environmental, or geotechnical engineers usually need freeform notes, not radio buttons.
This is a particularly good fit for LLMs because engineering field reports live in a constrained, conventional domain: similar language, repeated structures, and highly standardized content across firms and projects. There’s a lot of redundancy and grunt work, summarizing the same site conditions, formatting repetitive data, translating field notes into polished paragraphs, all of which LLMs handle well with the right prompting and guardrails. We’re not generating arbitrary prose; we’re transforming structured inputs (notes, images, forms) into structured outputs, with firm-defined templates and required fields that minimize the risk of hallucination. When facts matter (e.g. test results or measurements), we keep them grounded in the user’s input, the model doesn’t invent data because there’s nothing for it to invent. This makes it one of those cases where LLMs aren’t just a novelty, they're genuinely the best tool for the job.
Under the hood, we use a combination of prompt-engineered LLMs and firm-specific formatting rules to get outputs that don’t just sound good, but also look right. We’ve recently added translation features, and we’re iterating quickly based on field feedback. We charge per seat and are deployed at mid size firms, and trialing with some multinational engineering firms who have thousands of reports to file each week. We're also starting to see interest from construction managers and developers who do their own internal QA reporting.
We don't have a self-serve way to try out the product yet, because the way our business works requires templates to be customized by company. But there’s a demo at https://www.youtube.com/watch?v=u3Pi1iih1_Y, and if you want to poke around the UI yourself, here’s a sample account to log in with:
login: hndemo@opusense.com
password: OpusenseHacker2025
We’d love to hear how others are thinking about tools for field work, reporting, or similar workflows (engineering, architectural, etc.). If you’ve built in this space, or have thoughts on how to improve it, we’re all ears!
What happens if your product is involved in a fatal or very expensive construction incident or situation?
What happens if your product is involved in a PE going to jail?
One conventional startup possibility is that the startup shuts down, and its people move on to new startups and other employment. But I'm wondering whether that's different for startups that involve regulated safety-critical work.
What we’re really doing is shifting the process from spending an hour (or several, depending on the department) writing a report, to just a few minutes reviewing a completed draft.
In some domains, people will just rubber-stamp, but I would guess that some roles within civil engineering, aerospace engineering, etc., would remain very serious about their signoff responsibility, for at least a generation.
How are the gaps getting filled in by AI?
I worked on safety reporting in another domain, and in that domain, I can't immediately think of how AI could fill in the gaps from notes safely. Every detail of observation, interpretation, and suggestion mattered.
Maybe what you're doing with the construction domain reports is different, or you have found the right line for what you do and don't do?
For example, are you only generating boilerplate parts that fabricate zero observation information? Say, if the note is "rebar exposed, south wall", then that becomes a sentence without anything added, and the rest of the paragraph is copied verbatim from professional standards about what this means?
Or maybe there is potential for the AI to do harm (e.g., an LLM component hallucinates a typical description of exposed rebar, that adds or subtracts some important fact), but you trust the engineer to read closely and catch that every time before they stamp (rather than "rubber-stamp").
My unsolicited advice is I would expect Owner-side administrators (IT people) to direct sales decisions, and they don’t care about users or working products. I have only ever met one CTO in the AEC space who even considered end user benefit. Unfortunately, this means your product quality and utility is not actually important as evidenced by the whole Bentley product line, but integration with existing products is. Nobody seems to make big money in tech for white-collar AEC unless Bentley or Autodesk buy your IP. Then they will crudely bolt it onto their garbage software and their missionaries embedded in large companies disguised as technologists and CAD managers will sell it.
My opinion is con-tech is totally broken for very complicated reasons with the private market (commercial architecture) being the only small voice of sanity since they compete on price sometimes.
In our experience, owners do care because inspection practices directly affect the quality, consistency, and timeliness of the final reports delivered to their clients. These reports significantly influence client satisfaction and future business decisions.
We’ve spoken with end clients who receive these inspection reports, and they consistently tell us that the quality of the documentation plays a major role in their choice of consulting partner. So while integration with existing systems is critical, we also believe strongly that the usability and quality of the product matter, because they shape the company’s external image.