RevOps case management system with AI assistant and Slack integration
Build an internal "RevOps Case Desk" workflow for a Commercial Ops team, backed by a CRM (I used Salesforce — swap for your team's CRM), with a lightweight AI helper on the front. Purpose: Give the RevOps team a single case-management workbench: a webpage where requesters can get instant AI-assisted answers or file a case, where managers can see cases from their reporting chain, and where RevOps admins can triage, own, and close the full case queue — plus lightweight AI-assist metrics. Trigger: Everything hangs off one space-authenticated webpage as the entry point. That page calls several backing API endpoints (also space-authenticated) for case operations, settings, and the AI helper. A separate externally-triggered webhook receives interactivity callbacks from a chat tool (I used Slack — swap for your team's chat tool) so users can reply to cases from a message thread. Main steps / structure: Case Desk webpage — the UI: an "Ask" tab for AI Q&A, "My cases" (requested + CC'd), "My team" (read-only for managers, based on the reporting hierarchy), and an admin "Desk" view (triage, status/priority/owner changes, close, converse, CC management) plus AI-assist metrics for admins. Ask agent endpoint — takes a question, grounds the answer in your team's knowledge base (I used Notion — swap for your wiki) and in similar prior cases from the CRM, uses an LLM (I used Claude/Anthropic — swap for your model provider) to answer and cite sources, logs the interaction, and routes unanswered questions into case filing. Case intake endpoint(s) — the canonical boundary that creates/updates cases in the CRM: checks for likely-duplicate open cases first, sets all case fields (subject, description, priority, owner, requester, related account/opportunity, etc.), handles file attachments, manages a CC list (tracked as case-comment events so the CRM stays the source of truth), classifies which other ops teams should be looped in via a lightweight AI classification pass, and notifies the relevant team's chat contact when a related team is tagged. Settings endpoint — admin-only store for the desk's admin allow-list, team memberships, and team-to-chat-contact routing. Chat interactivity webhook + processor — receives reply/action events from the chat tool's interactivity callbacks, opens reply modals, and writes authorized replies back to the CRM case. Connectors / external services: a CRM for case storage and identity/org-chart lookups, an LLM provider for the AI assist and team-classification, a wiki/knowledge base for grounding answers, and a team chat tool for notifications and interactive replies. Treat all of these as swappable — the workflow's shape doesn't depend on any one vendor. Side effects: creates/updates real CRM cases and comments, uploads attachments, sends chat notifications and opens chat modals, and persists settings — build it expecting real writes, not sandboxed test data. Tools used: Salesforce, Anthropic (Claude), Notion, Slack
What this prompt builds
An AI-enhanced case management system that lets employees submit requests to RevOps, get instant answers from a knowledge base and past cases, and tracks resolution through an app instead of scattered emails. The workflow routes cases intelligently across RevOps sub-teams, prevents duplicates, and allows requesters and RevOps staff to manage cases and reply via Slack or a dedicated web interface. It logs AI-assisted resolutions to measure deflection and improve future answers.
The problem
RevOps teams often answer the same questions repeatedly and lose resolution context when cases are handled through email threads scattered across inboxes. Requesters have no way to check documentation or past cases before filing, leading to duplicate requests and wasted time. Teams that handle requests across multiple specialties (GTM Systems, data ops, process ops) struggle to route cases to the right people, and managers lack visibility into their team's open requests. This workflow builds a case management app that solves all of that: an AI agent grounded in the team's Notion documentation and prior CRM cases answers questions before a case is ever filed, flags likely duplicates, intelligently routes cases to the right RevOps sub-team, and gives both requesters and RevOps staff a single interface to track, comment on, and resolve cases—with full Slack integration so replies flow back into the system instead of disappearing into email.
Solution and impact
The workflow deflects routine questions with an AI assistant that answers directly from documentation and past cases, logging those interactions so the team can measure how much time they save. When a case must be filed, it prevents duplicates, intelligently tags related teams, and keeps all resolution context in one place—visible to requesters, managers, and the RevOps team through a web app and Slack threads. Over time, the AI improves as it learns from newly resolved cases, and the team gains a historical record of how problems were solved instead of losing that knowledge to individual inboxes.