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Otter is OpenLIT’s AI chat assistant for observability data. Ask questions in plain language about traces, costs, and tokens; create dashboards, rules, prompts, and Vault secrets through conversation; and run the same AI analysis you get from the telemetry detail views. Product copy describes it as: Ask questions about your observability data using natural language. Open Otter from the Otter mode toggle in the sidebar (/chat), or from the floating Otter button on other playground pages (hidden while you are already on /chat*). Configure a provider first under Chat Settings, then start chatting. Track spend on the Otter usage page. Trends for narrow phrases like “AI copilot for observability” are low-volume; broader interest sits around AI chat assistants and natural-language querying - Otter is the observability-native version of that workflow.

Chat with Otter

Conversations, SQL results, widgets, and resource actions

Chat Settings

Pick AI Provider, Model, and a Vault API key

Otter usage

Token and cost attribution by feature, provider, model, and date

AI Analysis

Trace and span analysis Otter can also run from chat

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What Otter can do

  • Natural language data questions - Otter turns questions into read-only SQL against your telemetry tables and shows results as tables or charts.
  • Save as Widget - turn a query result into a dashboard widget.
  • Resource management - create and manage rules, contexts, prompts, Vault secrets, and custom models through conversation.
  • Dashboard generation - describe a dashboard and import the generated layout.
  • Trace / span analysis and prompt improvement - same capabilities as the telemetry AI Analysis and Prompt Hub Otter flows, reachable from chat.

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Get started

1

Configure Chat Settings

Open /chat/settings (gear in the Otter sidebar). Choose AI Provider, Model, and API Key (from Vault), then Save Configuration (or Update Configuration if one already exists). Store the key in Vault first, or use Create new on the settings form.
2

Start a conversation

Open /chat, click New Chat, and try an empty-state example such as analyzing slow traces from the last 24 hours or breaking down token usage and cost by model.
3

Review usage

Open Otter usage (/chat/usage) to see tokens and cost by provider, model, and where Otter was used (chat, trace analysis, span analysis, prompt improvement).

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Frequently asked questions

Yes. Until a provider, model, and Vault API key are saved, Otter prompts you to configure Chat Settings.
Query tools run read-only against an allowlisted set of telemetry tables. Resource tools only change platform entities (prompts, rules, and so on) when you ask Otter to create or update them.