Octocom Copilot

Octocom Copilot is an AI assistant built directly into the Octocom dashboard. Open it from the navbar and ask it to do things in plain language — inspect why the bot replied a certain way, rewrite a workflow, author knowledge base articles, analyze a spreadsheet of customer feedback, or run test conversations against your bot. It reads freely and explains changes before making them. Changes that clearly follow your request can run immediately; sensitive or ambiguous actions pause for an Approve / Deny decision.

There's nothing to install or connect — it's already there.

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What you can do with the Copilot

The best way to discover what's possible is to ask the Copilot itself: "What can you do?" It will introspect its available tools and give you an up-to-date overview.

Popular use cases include:

• Deeply debug bot responses. The Copilot can pull the exact system prompt the bot saw on any past response and the full sequence of tool calls it made — then trace which rule, workflow, article, or action drove the behavior, and fix it.
• Drive test conversations against your bot. The Copilot can literally chat with your Octocom bot, send messages, read replies, then iterate on the configuration in a tight loop — like an automated QA engineer.
• Operate on real customer conversations. List and read conversations, inspect transcripts, tag them, close them, or hand them off to humans.
• Analyze your support operation. The Copilot can query your conversation and agent analytics directly, crunch the numbers, and render charts inline in the chat — resolution rates by topic, handoff trends, busiest hours, whatever you ask for.
• Manage every part of the bot's configuration:
  • Bot rules — the policies that guide responses, with full version history and rollback
  • Workflows — multi-step playbooks for handling specific situations, with variants
  • Articles & documents — the knowledge base, with versioning, soft-delete and restore
  • Macros & folders — canned responses for human agents
  • Tags — for routing, reporting, and conversation triage
  • Data collection prompts — structured intake of customer info (email, order number, etc.)
  • Global bot config — model, tone, safety settings, and more
• Write custom code on your behalf, and test it before deploying:
  • Python actions — let the bot do anything Python can do
  • API actions — call any external API as a bot action
  • Condition providers — Python-based gates that decide when workflows/rules apply
  • Event handlers — Python listeners that react to bot/conversation events
  • Sidebar widgets — Python-rendered widgets for the agent UI
  • Every one of these can be validated with real inputs before you push it live.
• Configure social media response automation — comment workflows that handle Instagram/Facebook comments and DMs, including testing them against sample comments.
• Configure the review-response bot — Trustpilot, Okendo, and Google review workflows, including simulating an incoming review end-to-end.
• Build and run AI-generated product catalog parsers. Hand the Copilot any product feed (XML/JSON/CSV) and have it write a parser that maps it into Octocom's product catalog — sample the feed, write the parser, run it, inspect the execution, iterate.
• Search and inspect your product catalog conversationally.
• Ask it how Octocom works. The Copilot has Octocom's own documentation at its fingertips, so it can answer "how do I…" questions about the platform and then go do the thing for you — no Octocom expertise required on your end.

Beyond configuration: files, data, and documents

The Copilot isn't limited to managing your Octocom setup — it's also a capable analyst and writer:

• Upload files straight into the chat. Drop in CSVs, Excel spreadsheets, PDFs, Word documents, images, or plain text (up to 10 MB per file) and ask questions about them. Spreadsheets and documents are parsed automatically; images can be inspected visually.
• Run real computations. For data-heavy work, the Copilot writes and executes Python in a secure sandbox — so "average resolution time by weekday from this export" is an actual computation, not an estimate.
• Search the web. It can look up external documentation, competitor policies, courier tracking pages, API references — whatever the task needs.
• Produce charts, files, and PDF reports. Ask for a chart and it renders inline. Ask for a CSV and you get a download button. Ask for a polished PDF — a monthly support report, an audit summary, a proposal — and the Copilot designs and renders a print-ready document.
• Delegate research. For large investigations (say, sweeping hundreds of conversations for a pattern), the Copilot can spin up parallel read-only research tasks and synthesize their findings.

The real superpower: combining it all in one loop

The individual capabilities are useful, but the leverage shows up when you combine them. A few examples of what this looks like in practice:

• "Configure this, then stress-test it." Ask the Copilot to set up a workflow, action, or rule, then run 20 test conversations against it with varied scenarios, summarize where it broke, and iterate.
• "Here's a CSV of feedback — fix the bot." Drop a spreadsheet of conversation IDs and human comments. The Copilot reads each conversation, correlates the feedback, and explains targeted changes — rule by rule, article by article — with clarification and approval checks where needed.
• "Why did handoffs spike last week?" The Copilot queries the analytics, pulls representative conversations, reads the transcripts, identifies the driver, and proposes the configuration change that addresses it.
• "Build me an integration." Describe an external system. The Copilot looks up its API documentation on the web, writes a Python action, tests it with realistic inputs, wires it into a workflow, then runs end-to-end test conversations to confirm it all works.
• "Put it in a report." After any analysis, ask for a PDF and send it straight to your team.

In short: the same assistant does the analyzing, the coding, the configuring, the testing, and the reporting — in one conversation, inside the dashboard you already use.

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Clear explanations before changes

You do not need to be a developer to use Copilot. It should explain what the bot will do, when a rule applies, and what will change for your customers in everyday language. Even when you discuss technical features, the explanation should stay focused on the intended behavior. For example, when configuring a condition provider, it should ask which situations should make the condition true or false. It can provide code, SQL, or implementation details when you explicitly request them.

When investigating an incorrect response, Copilot should check the available information, workflow selection, conflicting instructions, and configuration before drawing conclusions. It should describe the behavior respectfully, avoid labels such as "stupid" or "hallucinated", and avoid guessing which model handled the conversation. Missing information or conflicting guidance should be identified only when supported by evidence. Recurring issues without a clear fix should be reviewed with your account manager or Octocom support.

Before making a change, Copilot should briefly explain the result it understood you want, which business and workflow/article/setting it will affect, and what will change. It should explain important effects on routing, policies, customers, or other settings before acting. For example, removing a time restriction from a workflow branch is different from deleting the branch itself.

For clear requests with an understood impact, Copilot can proceed after explaining its plan. If it would need to guess the target, scope, or effect, it should ask a focused question and wait for your confirmation. It should also clarify a plan that goes beyond what you requested. Your confirmation continues to apply while the agreed scope stays the same.

Configuration changes execute directly after Copilot understands your request and explains its plan. There is no separate automated approval review. Sending a message to a real customer or starting a customer conversation still shows an Approve / Deny prompt and requires manual approval.

If documentation or tools do not establish how something works, Copilot should say what it can and cannot verify rather than guess. Its available tools do not represent everything Octocom can do. If it remains blocked or encounters behavior it cannot explain, it should suggest checking with your account manager or Octocom support and provide this Copilot session's link for you to share. The team may know another way or a workaround. Copilot should also explain documented behavior if it differs from your understanding, and recommend support if the difference remains unresolved.

It can record concrete documentation, capability, tool, or SQL gaps for Octocom to improve, while continuing to help with the parts it can complete. It should say a note was recorded only after the reporting tool confirms it. Recording a note does not promise a fix or completion date, or mean support has taken ownership of your request.

Other safeguards include:

• Version history and soft-delete on most configuration entities (workflows, articles, bot rules, etc.), so it's almost always possible to revert a change.
• Organization scoping — the Copilot only ever sees and operates on the organization you have open.
• Rate limiting to prevent runaway loops.
• Audit logging of every action the Copilot takes.

Review the scope and impact it describes, especially for actions that touch real customers, like sending messages or closing conversations. Ask for clarification whenever the proposed outcome is unclear.

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Getting started

1. Open the Octocom dashboard and click the Copilot icon in the top navbar.
2. Type what you want in plain language — or start with something exploratory like "Give me an overview of how my bot is configured" or "What can you do?"
3. Your conversations are saved as sessions in the sidebar, so you can pick up long-running work where you left off.

Copilot is available to Organization Admins and Managers. If you don't see the icon, reach out to us.

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Copilot vs. Octocom MCP

Copilot and Octocom MCP share the underlying Octocom workspace tools. Copilot also has its own helpers, such as reporting improvement suggestions to Octocom; these are not exposed through MCP. The difference is where the agent lives:

Use the Copilot when you want zero-setup, supervised assistance inside the dashboard. Use MCP when you want Octocom available to an agent that also has access to your other systems.