Long-form summarization

Universal Summarizer condenses articles, transcripts, and documents through large language models. A Beam agent sends a source when new content lands, reads the returned summary, and writes it onto the matching record with a link to the original. Summaries feed briefings, tickets, or research notes according to your rules. Content the service cannot summarize, or output that comes back empty or truncated, is flagged for a person with the source attached. Reviewers decide whether a summary is fit to share; the agent handles retrieval, submission, and filing around that check.

Multi-format ingestion

The summarizer accepts many formats and long inputs. A Beam agent detects the incoming type, submits it in the form the API accepts, and records which items summarized cleanly and which did not. Files that exceed practical limits or arrive in an unsupported shape are set aside and reported to a coordinator rather than dropped. This lets the agent work through a mixed queue of links, transcripts, and documents without a person sorting them first, while genuinely problematic inputs still reach someone who can decide how to handle them.

Digest assembly

Teams often want a single roundup rather than scattered summaries. A Beam agent gathers the day's summaries, orders them by your chosen rule, and assembles a digest posted to the channel or emailed to the list you name. Sources that failed to summarize are listed separately so nothing looks silently missing. When the digest would run unusually long or short, the agent notifies the owner before sending. People set the topics and cadence; the agent collects, arranges, and distributes the summarized material on that schedule.