AI & RAG workflows

Watches a policy@ inbox, drafts a cited answer from your Confluence and Drive knowledge base, and either auto-sends it or routes low-confidence questions to a human for review.

On request, an agent assembles a personalized onboarding brief for a new hire's role by retrieving the relevant Confluence and Drive policies and writing a Notion page they can…

When a PagerDuty incident fires, an agent reads the alert, retrieves and reasons across multiple runbook pages, correlates recent GitHub changes.

Each week, reviews recently resolved PagerDuty incidents against the postmortem knowledge base and reports which incident types have no remediation precedent.

On every new PagerDuty incident, retrieves the closest matching past postmortems and posts a suggested remediation runbook with citations directly into the incident's Slack…

When a PagerDuty incident triggers, retrieves the relevant Dropbox specs and runbooks for the affected service and posts a grounded incident briefing into the incident's Slack…

Answers on-call and ops questions in Slack by grounding every reply in your Confluence + Drive runbook corpus, and refuses to answer when no supporting source exists.

Answers on-call and ops questions in Slack by grounding every reply in your Confluence + Drive runbook corpus, and refuses to answer when no supporting source exists.

On a Datadog alert, retrieves matching runbook guidance and decides whether the on-call can self-resolve in Slack or whether the spike warrants an immediate PagerDuty page…

When a Datadog monitor fires, this looks up the matching runbook knowledge base and posts a plain-English 'why this spiked' answer to Slack with linked Confluence citations.

When a new hire is added via webhook, retrieve the Loom walkthroughs relevant to their role from the indexed library, assemble an ordered playlist with timestamped links.

When an engineer requests a runbook for a service, retrieves all related postmortems, synthesizes a structured runbook.

When the answer bot can't ground a metric question in any existing Confluence runbook, it files a Linear ticket capturing the question, the Datadog evidence it found.

After a GitHub deployment, the bot checks the service's key Datadog metrics against pre-deploy baselines, consults the runbook for what 'healthy' looks like.

When the answer bot can't find a grounded answer in Coda, an agent researches the question against approved web sources, drafts a citation-backed new knowledge row.

When a PagerDuty alert fires, the bot automatically enriches it by comparing the alerting metric to its Datadog historical baseline and attaching the matching runbook steps.

An agent ingests a full uploaded questionnaire, retrieves grounded answers from the policy KB for every item, fills the response document.

Before each booked sales meeting, builds a one-page prep brief by combining the account's HubSpot context with grounded talking points and objection responses pulled from your…

Given an active incident, retrieves the matching runbook and returns a step-by-step remediation walkthrough with citations, then posts a status thread to Microsoft Teams.

Weekly job that uses the runbook agent to flag procedures contradicted by newer docs, missing owners, or unreferenced for months, and files the findings as Linear issues.

Weekly, samples answer-bot queries that returned low-confidence or no results, traces them to gaps or outdated pages in Confluence and GitLab wikis.

An agent investigates a remediation question by searching past postmortems and pulling live metrics from Datadog.

Before each external sales meeting on your calendar, this builds a one-page competitive brief grounded in win-loss notes for the relevant competitor and emails it to the rep.

Answers engineering questions posted in Slack by retrieving relevant Confluence RFCs and GitHub code, then replies with a grounded answer and clickable source citations.

On each new support ticket, drafts a cited reply from your runbook corpus and either auto-suggests it to the agent or escalates when documentation does not cover the issue.

Answers employee policy questions posted in Slack by retrieving the most relevant Confluence and Google Drive passages and generating a cited answer.

On a schedule, scans your Confluence and Drive policy library for statements that contradict each other (e.g. two different PTO rules) and posts a triage report to Slack so doc…

Lets staff ask support or product questions in a Slack channel and replies in-thread with an answer grounded in Confluence docs and historical Zendesk tickets, with citations.

Lets employees ask questions in Slack and replies in-thread with an answer grounded in the Coda corpus, including clickable citations to the exact source pages.

On a high-severity PagerDuty escalation, it assembles a grounded incident brief from the matching Confluence runbook and recent Datadog signals.

Scores each Front ticket against ReadMe and Coda docs, auto-drafts a cited reply for high-confidence questions.

Exposes an HTTP webhook that takes a question, retrieves the most relevant Coda blocks from the Supabase vector index, generates an answer strictly grounded in those blocks.

On a schedule, compare your process registry against the indexed Loom library to find procedures with no walkthrough and videos that are outdated or rarely retrieved.

After the RAG assistant answers a remediation question, an LLM judge grades the answer's grounding and citation quality, logs the score.

An agent reviews logged rep questions that the retrieval bot answered poorly, clusters the misses against the Dropbox collateral index.

Runs weekly to compare your published Notion battlecards against the latest win-loss notes, flagging cards that contradict or omit recent loss patterns and proposing edits.

A Slack bot that answers rep questions about a named competitor by retrieving relevant win-loss notes and approved battlecards, then drafting a grounded, cited response in-thread.

Monitors a shared RFP inbox, classifies whether an email contains answerable security questions, drafts cited answers for matched items.

Walks every entry in the Postgres answer bank, re-checks the Confluence page each answer cites, and flags or quarantines entries whose source doc changed, moved, or was deleted…

At shift change, summarizes the last shift's PagerDuty incidents and links each to relevant postmortems, delivering a grounded handoff brief to the incoming on-call engineer.

Listens for questions in a Slack sales channel, retrieves the most relevant collateral passages from Postgres.

Each night, re-checks recently logged answer-bot responses against the Coda source rows they cited and flags any claim not actually supported by its citation.

Answers 'how do I remediate X' questions posted in Slack by searching past incident postmortems and returning step-by-step fixes with linked source citations.

On a schedule, syncs Confluence runbook pages into a Postgres pgvector store and links them to Datadog monitor names so the spike-explainer flows always retrieve fresh.

Weekly, it reviews the spikes that the knowledge base answered poorly, identifies which Datadog monitors lack good runbook coverage.

On a schedule, pulls new and updated postmortems from Confluence, chunks and embeds them, and upserts the vectors into Postgres so the retrieval corpus stays current.

Each week, scans the questions asked across recent questionnaires, finds the ones with weak or missing policy KB coverage.

On a schedule, checks every previously answered questionnaire item against the current policy KB version and flags answers whose cited source has changed or been superseded.

Answers on-call questions posted in a Slack channel by retrieving the most relevant Dropbox engineering specs and replying with a grounded, source-cited answer in the thread.

Reps trigger a slash command in Slack with a deal objection; the flow retrieves matching battlecard and call-transcript passages from Postgres and replies in-thread…

Lets anyone ask a contract question with a Slack slash command or mention and replies in-thread with the answer and the exact clauses it came.

Watches GitLab merges to your API repo, detects changed OpenAPI specs and changelog files, re-chunks and re-embeds only what changed.

Each week, scans rep questions the answer bot couldn't ground in Coda, clusters the recurring gaps.

On a nightly schedule, pulls new and updated incident postmortems from Confluence, chunks and embeds them.

Answers engineers' on-call questions in Slack using only the versioned runbook wiki.

Answers engineers' runbook questions in Slack by retrieving the most relevant Confluence sections and replying with a grounded answer plus deep links to the exact source headings…

Triggered on a Slack thread, retrieves related prior ADRs for context, drafts a properly formatted Architecture Decision Record with an LLM.

Answers engineers' architecture questions in Slack by retrieving the relevant Architecture Decision Records from Confluence and the decision index in Postgres.

Runs weekly to compare benefits facts between Confluence and Notion plan sources, flags stale or conflicting figures with OpenAI.

Answers employee benefits questions in Slack by retrieving plan-document passages from Confluence and Notion, then replying with a grounded answer and source links.