Salesforce
Salesforce · AI / ML · Filed Feb 11, 2026 · USPTO published Jun 25, 2026 · Jun 25 release
Salesforce Patents an AI That Turns Video Meetings Into Automatic Summaries
Every meeting ends with someone asking 'can you send a recap?' Salesforce has filed a patent for an AI that handles that automatically, pulling highlights, action items, and notes directly from the video call.
- Publication number
- US 2026/0178848 A1(US20260178848A1)
- Applicant
- Salesforce, Inc.
- Filed · Published
- Feb 11, 2026 · Jun 25, 2026
- Inventors
- Aaron Josephus Maurer, Katherine Jane Steigman, Olivia Diane Grace, Sohom Paul, McKenna Lowry, Michael Hahn, Jacquelyn Elizabeth Rocca, Kelly Holmes Moran, Zachary Alan Kaarvik, Leonard Jackson Shearer, David Barrett-Kahn, Wii Yatani, Omar Lee, Curtis Neil Allen JR.
- Status when we published
- Waiting for an examiner
- Document
- 20 claims
- US classification
- 715/254
- Parent application
- Continuation of 18/385,219 (filed Oct 30, 2023)(18385219)
What Salesforce's meeting-summary AI actually does
Imagine you just sat through a 45-minute team call. Normally, someone has to write up what was decided and who's doing what. Salesforce's patent describes a system that does that for you, automatically, the moment the meeting ends.
The system records the video call, transcribes everything that was said, and then runs that transcript through an AI model. The model doesn't just produce a wall of text. It breaks the output into highlights, action items, and AI-generated notes, then sends that summary to everyone who was in the meeting.
What makes this a little more than a basic transcription tool is that the AI also pays attention to how people reacted during the meeting. Things like emoji responses, chat messages typed while someone was talking, and even gestures can all feed into what the model decides to flag as important.
How the model reads reactions, chat, and speech together
The patent describes a pipeline that starts the moment a video meeting begins. Audio and video from the call are captured alongside what the patent calls user interaction data, a catch-all term for chat messages typed during the meeting, emoji reactions, message threads, and detected gestures.
Once the meeting ends, a natural language processing (NLP) model (software that reads and interprets human language) converts the spoken audio into a written transcript. That transcript is then passed into a second machine learning model trained to produce structured summaries.
The output is broken into three components:
- Highlights: the key moments or decisions from the call
- Action items: tasks assigned to specific people
- AI notes: additional context the model flags as worth remembering
The summary is then displayed on the devices of the meeting participants via what the patent describes as a group-based communication system, which maps closely to a channel-based platform like Slack. The inclusion of emoji and chat reactions as model inputs is the most distinctive technical detail. The idea is that a burst of reactions around a particular moment signals importance, giving the model a signal beyond just the words spoken.
What this means for Slack and Salesforce meeting tools
Salesforce owns Slack, which already competes with Microsoft Teams and Google Meet on meeting and messaging features. Both of those platforms have rolled out their own AI meeting-summary tools (Copilot and Gemini, respectively), so this patent is Salesforce staking out its own technical approach to the same problem.
For you as a user, the practical difference is the emoji and chat-reaction angle. If the model is genuinely trained to weight moments that got a lot of real-time reactions, the summaries could be more accurate about what the room actually cared about, not just what was said the loudest or the longest. That's a meaningful distinction if your meetings are anything like most people's meetings.
Source: US 2026/0178848 A1 at the USPTO (PDF). Full patent text and figures are in the official publication.
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