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Ask AI

Ask AI

Ask AI is the primary conversational AI interface in TestRelic. It provides a full-page chat experience where you can ask questions about your test suite, request analysis, and generate structured artifacts — all using natural language.

Growth plan required

Ask AI requires the Growth plan. See Plans & Billing.

Accessing Ask AI

  • Click Ask AI in the left sidebar navigation.
  • The URL format is /ai for a new conversation or /ai/:conversationId to resume an existing conversation.

Starting a conversation

Type your question or request in the input box and press Enter. The AI responds with a streaming reply — text appears token-by-token as it is generated.

Example prompts

Analyze recent failures
What are the most common failure patterns in the last 7 days
across the @staging repository?
Generate a test plan
Create a test plan for the checkout flow covering happy path,
payment failure, and out-of-stock scenarios.
Ask about a specific run
Summarize the failures in @run-20240315 and suggest which ones
are likely infrastructure issues vs real bugs.

Attaching context with @ mentions

The @ context picker lets you attach specific entities to your message so the AI can answer with precision. Supported context types:

Context typeWhat it is
@repoA specific repository
@test_runA specific test run by ID
@test_caseA specific test case
@branchA Git branch
@suiteA test suite grouping
@tagA test tag label
@environmentA deployment environment
@integrationA connected integration

Type @ in the input box to open the context picker and search for the entity you want to attach.

Conversation history

All conversations are saved automatically. The Chat Sidebar on the left of the Ask AI page lists all your previous conversations. From there you can:

  • Resume any past conversation.
  • Rename a conversation for easier reference.
  • Delete conversations you no longer need.

Conversations are private to your user account within the organization.

Message feedback

You can rate any AI response using the thumbs up / thumbs down feedback controls on each message. This feedback helps improve the AI's responses over time.

AI artifacts

Some requests cause the AI to generate a structured artifact in addition to the text response. Artifacts appear in a dedicated panel to the right of the chat. The supported artifact types are:

Artifact typeDescription
dashboardA rendered analytics dashboard with charts and metrics
reportA formatted test quality or coverage report
test_planA structured test plan with scenarios and steps
presentationA slide-style summary for sharing with stakeholders
codeA code snippet (e.g. a new test, a reporter config)
data_tableA tabular breakdown of test data
chartAn inline data visualization
navigation_pathsA test navigation path map

See AI Insights & Artifacts for more detail on individual artifact types.

Any artifact can also be shared via a public or private link (Google-Drive-style): public links render a read-only view of the artifact — with its filters — to anyone who has the link, while private links require org sign-in. Shared artifacts are also collected in an artifact library. See sharing artifacts via links.

Streaming and tool use

Behind the scenes, the AI uses tool calling to fetch data from your repositories, runs, and test cases. While a tool call is running, the UI shows an indicator. The result of the tool call is incorporated into the final AI response — you do not need to take any action.

The streaming connection uses Server-Sent Events (SSE). If the connection is interrupted, the platform automatically retries and resumes streaming.

Memory

Ask AI can remember context from past sessions so that follow-up conversations feel continuous. Memory is controlled by a toggle in the composer bar — it is on by default.

Not the same as repo Memory

This section covers conversation memory — per-user recall of your recent chats and preferences. The team-shared, per-repository knowledge base of test decisions and constraints is a separate feature: see Memory.

How memory works

Memory operates in three layers. The layers are independent and stack on top of each other:

LayerWhat it containsAlways active?
Current threadThe last 20 messages of the open conversation, loaded from the databaseYes — unaffected by the toggle
Recent conversation historyShort excerpts pulled from your other recent conversations across all threadsOnly when Memory is on
Long-term memoryDurable facts about your preferences, recurring topics, and working patterns, extracted by the AI and stored across sessionsOnly when Memory is on and enabled on your instance

When Memory is on, all three layers are combined into the system context sent to the AI before each reply. When you turn Memory off, only the current thread history is used.

Enabling and disabling memory

The Memory toggle appears:

  • In the Ask AI composer bar at the bottom of the full-page chat.
  • In the AI Assistant panel (the floating assistant available on every page).

Toggle it off for any conversation where you want the AI to respond without prior-session context — for example, when troubleshooting an isolated issue or starting fresh on a new project.

note

Memory is scoped to your user account. Colleagues in the same organization cannot see or access your memory context.

Ask AI Apps

Ask AI Apps are third-party service integrations — such as Slack, Gmail, GitHub, and Jira — that you connect to Ask AI. Once connected, the AI can call actions in those services directly from the chat: look up Slack threads, draft emails, open Jira issues, and more.

Connecting an app

  1. Go to Settings → Integrations → Ask AI Apps.
  2. Browse the available app catalog and click the app you want to connect.
  3. Complete the OAuth authorization flow for that service.
  4. The app appears as Connected in the list and is now available in Ask AI.

You can manage connected apps (view status, disconnect) from the same page at any time.

Using an app in a conversation

Once an app is connected, you can bring it into any Ask AI conversation in two ways:

  • @ context picker — Type @ in the composer, search for the app by name, and select it from the list. The app is attached to your message as a composio_toolkit context item.
  • Apps control in the composer bar — Click the apps icon in the composer bar to open the apps picker, then select the connected app.

After attaching an app, the AI can call its tools when it determines an action is relevant to your request. You can attach multiple apps to a single message.

How app tool calls work

When an app is attached, the AI is given access to its tools through an MCP server backed by the Composio integration layer. If the MCP path is unavailable, the platform falls back to direct Anthropic tool definitions for the same app. In both cases, the tool call is transparent: the UI shows a tool-call indicator while the action runs, and the result is incorporated into the AI's reply.

tip

Connecting a Jira app alongside your test context lets Ask AI open tickets, query existing issues, and link failures directly — without leaving the chat.

Workspace vs personal connections

Some apps support a workspace scope (shared across your organization's Ask AI sessions) and a personal scope (visible only to you). The scope is shown when you initiate the connection and can be reviewed on the Ask AI Apps settings page.

TestRelic Slack App

The TestRelic Slack App is the inverse of Ask AI Apps: instead of the AI calling third-party services from the web chat, the Slack App lets your team trigger Ask AI from inside Slack. Both can be enabled at the same time — they're complementary, not exclusive.

FeatureAsk AI AppsTestRelic Slack App
Where you use itWeb app composerAny Slack channel or DM
DirectionAI → third-party toolSlack user → Ask AI
Typical use"Open a Jira ticket for this failure""/testrelic which tests broke after deploy?"
Memory continuityPer Ask AI conversationPer TestRelic user (Slack ↔ web is unified)

See the Slack Integration page for the full reference. The summary below covers what's specific to Ask AI behavior.

Slash commands

Type /testrelic <prompt> in any channel the app is a member of. The prompt runs through the same Ask AI runtime as the web composer — same tool calls, same context, same artifact types — and the response threads under your message:

Channel: #qa-leads
/testrelic which tests broke after yesterday's deploy?
Channel: #checkout-team
/testrelic generate a sprint review deck for @repo:web-app covering the last 14 days

Threaded follow-ups continue the same Ask AI conversation, so context like @repo or @test_run set on the first prompt carries through.

Scheduled QA digests

Any Ask AI prompt can be scheduled to post recurring summaries to a Slack channel — weekly flaky digests, Monday sprint reviews, nightly regression reports. Each digest is a Slack card with metric tiles, top offenders, and a deep link back to the live artifact in the web app.

Create a digest by running the prompt once in the web composer and clicking Share → Schedule to Slack, or from Slack with:

/testrelic schedule a weekly flaky digest to this channel every Monday 9am

Manage all scheduled digests at Settings → Integrations → Slack → Schedules.

Share-back from the web composer

Every artifact rendered in the Ask AI panel has a Share → Slack action. Pick a channel, add an optional message, and the artifact posts as a rich card with metric snapshots and a deep link. Presentations and reports upload as Slack files so they're searchable later.

Connecting Slack

Install from Settings → Integrations → Slack in the web app, or from the Slack App Directory. Full install steps, OAuth scopes, and troubleshooting live on the Slack integration page.

Pairing with Jira

Combine the Slack App with the Jira integration and an Ask AI Apps Jira connection to triage and file tickets entirely from Slack: /testrelic was this a flake or regression?/testrelic open a Jira ticket for this failure with the failure context attached.

TestRelic Microsoft Teams App

The TestRelic Microsoft Teams App brings Ask AI into Teams with full parity to the Slack App: run a prompt in a channel, schedule recurring QA digests, share artifacts back from the web composer, get quality-gate failure alerts, and continue the same conversation through threaded follow-ups. The same Ask AI runtime, artifacts, memory, and privacy posture apply. Teams-originated conversations appear in the Chat Sidebar with a Teams badge and are unified with your web and Slack conversations.

Installation is a two-step flow, and this is where Teams differs from Slack:

  1. Connect (OAuth) at Settings → Integrations → Microsoft Teams → Connect. This uses Microsoft Entra ID (Azure AD) and binds your Teams tenant to your TestRelic org.
  2. Add the Teams app package — sideload it yourself or have a Teams admin upload it to your org's app catalog (and enable the Azure Bot Teams channel).
Connect alone does not add the bot

Unlike Slack, OAuth Connect only links the tenant. The TestRelic bot appears in Teams only after the app package is added in step 2. If the bot is missing after Connect, the package has not been installed yet.

See the Microsoft Teams Integration page for the full install steps, command usage, digests, failure alerts, and troubleshooting.

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