Why we're building Jalapeño
Meetings should produce work, not notes. Jalapeño is built end-to-end around that single idea.
The problem we kept hitting
Meetings end. Action items get captured, maybe. Someone is supposed to do them. Some get done. Many quietly do not. Two weeks later, the question that comes up in the next meeting is the same one that was already answered in the last one.
We had been on the other side of this for years. Running teams, taking notes, circulating recaps that nobody read, copy-pasting tasks into Linear after the fact, forgetting half of them. The gap between what gets decided in a room and what actually ships is real and costly, and it gets worse as the team grows.
The tools that exist mostly help with the symptoms. They produce nicer transcripts. They generate prettier summaries. They put a search bar on top of past calls. None of them close the loop. The actual work (turning a commitment into a tracked ticket assigned to the right person with a due date) was still manual.
What we built
A platform that takes the work out of meeting follow-up. Jalapeño records your meetings, transcribes them with speaker labels, extracts action items as structured tickets, and flows them into the project tool your team already uses. Linear, Jira, Asana, Trello. Pick one or run several. Status changes round-trip in real time.
Carlton, the AI assistant built into every workspace, sits on top of all of it. Ask it what is overdue, who took on the most this week, what we promised the customer last Tuesday. With write access enabled, it can also create meetings, update tasks, and invite team members on your behalf.
The whole thing is built so the most-clicked button after a meeting is not needed. You walk out of the call and the work has already been kicked off in the right place.
What we believe
Meetings should produce work, not notes.
The deliverable of a meeting is the work that follows it. If the platform you use produces a beautiful summary doc and no tracked tickets, it has missed the point.
AI should do the chore, not just narrate it.
Summarizing a transcript is the easy half of the job. The hard half is turning commitments into structured records that flow into your team's real tooling. That is what we focus on.
Your data belongs to you.
Customer content is not used to train models. The infrastructure runs under Microsoft's enterprise agreement with zero retention defaults. Read the security page for the specifics.
Built on
Azure OpenAI handles transcription, speaker diarization, and the reasoning that produces action items. Cloudflare sits in front of every origin for delivery and edge protection. The web app is React 19 on Vite. The API is Node and Express. State lives in PostgreSQL. Recordings live in Azure Blob Storage with server-side encryption. Nothing exotic, everything proven.
We will keep this stack lean on purpose. Fewer moving parts mean fewer surprises for the teams who trust us with their meetings.
Get in touch
Questions about the product, the company, or where we're headed? We'd love to hear from you.