Company profile · 4 min read
Opusense AI: Field reports while the inspector is still on site
Opusense turns field photos, voice notes and observations into branded reports and a shared field-operations workflow.
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
Published · Updated
Opusense AI turns field notes, photos and voice into construction and inspection reports. It fits teams that lose hours writing up site work after the inspection is already over.
What it does
Opusense’s homepage describes an AI-native field-operations platform for constructors, engineers and property teams. Inspectors can capture photos, voice notes and typed observations on a mobile device, including offline, then generate branded reports and keep an audit trail.
The company’s public workflow spans three groups: field-review teams, constructors and owners or facilities teams. That is important. A report is not the final product if the next person still has to reformat it, issue tasks, answer questions and send progress updates.
The retained launch material says Opusense was built for engineering consultants and site inspectors, with exports to Word or PDF. It also says the company was live with multiple firms across North America. That is company-reported adoption, not an independent customer survey.
Pricing and fit
Opusense’s pricing page lists Base at $49/month per user, Pro at $79/month per user and Teams at $149/month per user. The plans differ in report volume, reviewer workflow, dashboard queries, multilingual support, summaries and team controls. Enterprise is custom and includes role-based permissions, region-specific hosting and onboarding.
That packaging maps cleanly to the buyer. A solo inspector needs capture and report generation. A working team needs review. A multi-department organization needs shared data, pre-filters, summaries and permissions.
The founder context is relevant: the YC profile describes Roya Cody as a civil-engineering researcher with construction and infrastructure inspection experience, and Michael Bacani as an engineer from construction technology startups. Those are source-backed professional facts, not proof of field performance.
What could make it the wrong choice
The system depends on the quality of site capture, templates and review. Offline support helps in the field, but buyers still need to verify sync, GPS/photo retention, report corrections and client access. The public sources do not provide an independent error rate or review-time comparison.
My editorial take
I would shortlist Opusense for an inspection or engineering team where report backlog is a measurable cost and the firm has templates worth preserving. The product is less compelling if the work is mostly unstructured consulting or if nobody owns the review step. The useful bet is not “AI writes reports.” It is that field evidence can become a shared operational record while the inspector is still on site.
Quick facts
| Field | Sourced detail |
|---|---|
| Product | Mobile field capture, AI report generation and operations workspace |
| Buyers | Inspectors, engineering consultants, constructors and property teams |
| Pricing | $49 Base; $79 Pro; $149 Teams per user/month; Enterprise custom |
| Key boundary | Offline capture plus reviewer workflow and audit trail |
| Public status | Company homepage says SOC 2 Type II certified; company claim |
Sources checked
| Source | Checked |
|---|---|
| YC profile | 2026-09-19 |
| Opusense homepage | 2026-09-19 |
| Pricing | 2026-09-19 |
| YC launch | 2026-09-19 |
Cohort context
Opusense AI is listed in Spring 2025. In our 2026-09-18 directory snapshot, 1 of 143 listed companies in that cohort have YC’s primary industry label Real Estate and Construction (0.7%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.
Public website snapshot
Observed 2026-09-19T16:15:47.438Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.
| Signal | Homepage observation |
|---|---|
| Product description metadata | Observed |
| Canonical link | Not observed in this response |
| H1 or H2 heading | Observed |
| Typed structured data | Not observed in this response |
| Docs/developer link | Not observed in this response |
| Pricing link | Observed |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |
Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.
About the author
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.
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