RelevanceAI · jordanc-relevanceai · Sep 7, 2026
diff --git a/build/agents/create-an-agent.mdx b/build/agents/create-an-agent.mdx
@@ -88,4 +88,4 @@ Once you've created an Agent, explore the rest of the build guides to refine it:
 - [Triggers](/build/agents/build-your-agent/triggers) — run your Agent automatically on a schedule, from a webhook, or from an integration
 - [Alerts](/build/agents/build-your-agent/alerts) — get notified when your Agent needs attention, and define when it should loop in a human
 - [Memory](/build/agents/build-your-agent/memory) — configure how your Agent retains context across conversations
-- [Version history](/build/agents/build-your-agent/version-history) — every save creates a snapshot you can restore, so you can experiment without losing working versions
+- [Version history](/build/operations/version-history) — every save creates a snapshot you can restore, so you can experiment without losing working versions
diff --git a/build/invent/invent.mdx b/build/invent/invent.mdx
@@ -27,7 +27,7 @@
    Invent defines the checks each Agent must pass before launch and samples live runs after deployment. When quality drops, it diagnoses the problem and proposes changes to prompts, Tools, examples, models, or orchestration. It can test those changes against the same requirements before you approve them.
  </Card>
  <Card title="Review performance and find opportunities" icon="chart-line">
    Invent reviews Agent activity, errors, Evals, and performance dashboards to diagnose problems and recommend improvements. Describe a recurring process, and it can help identify where Agents, Tools, or Workforces could automate it.
  </Card>
 </CardGroup>

@@ -89,7 +89,7 @@

 <AccordionGroup>
  <Accordion title="Project isolation">
    Invent's access to Relevance AI is scoped to the active project at the API-key and fine-grained authorization layers, not only in the interface. Each internal platform request uses the active project ID and the caller's API key, then passes through the standard authorization checks. Enabling Invent in a sandbox project does not grant it access to assets in a production project.
  </Accordion>

  <Accordion title="Integration reach">
@@ -220,7 +220,7 @@
   <Accordion title="Restore a version" icon="clock-rotate-left">
     Ask Invent to roll an asset back to an earlier version — for example, "Restore the previous version of this tool". Invent copies that version into the current draft, leaving the live published version unchanged until you publish. This restores an earlier version of an existing asset; it doesn't recover one that's been deleted.
 
-    Invent always asks you to confirm before restoring, and appends `(restored)` to the version name so the restored state is easy to identify later. For a full guide to version history — including how to restore and rename versions from the builder UI, and how retention works — see [Version history](/build/agents/build-your-agent/version-history).
+    Invent always asks you to confirm before restoring, and appends `(restored)` to the version name so the restored state is easy to identify later. For a full guide to version history — including how to restore and rename versions from the builder UI, and how retention works — see [Version history](/build/operations/version-history).
   </Accordion>
     </AccordionGroup>
   </Tab>
@@ -230,7 +230,7 @@
 
 Invent can build an initial Evals suite, review results, investigate failed Checks, and diagnose performance alarms for Agents and Workforces.
 
-<Card title="Learn more about Evals" icon="chart-line" href="/build/agents/evals/introduction">
+<Card title="Learn more about Evals" icon="chart-line" href="/build/operations/evals/introduction">
   Learn how to create scenarios and reusable Checks, run evaluations, and monitor live performance.
 </Card>
 

diff --git a/build/agents/evals/checks.mdx → build/operations/evals/checks.mdx b/build/agents/evals/checks.mdx → build/operations/evals/checks.mdx
@@ -10,7 +10,7 @@ A Check is one pass-or-fail criterion. Every Agent and Workforce has its own lib
 - **To a Monitor dashboard** — it runs on a sampled portion of live tasks.
 - **To a one-off evaluation** of already-completed tasks selected from the task list.
 
-This page is the reference for what each type scores. To attach one while building a Test, see [creating Tests](/build/agents/evals/test-sets).
+This page is the reference for what each type scores. To attach one while building a Test, see [creating Tests](/build/operations/evals/test-sets).
 
 ---
 
@@ -99,7 +99,7 @@ The Checks tab lists every Check on the Agent or Workforce, grouped by type. Fil
 
 ---
 
-Next: Learn how to [run Evals](/build/agents/evals/running-evaluations) against your Test sets.
+Next: Learn how to [run Evals](/build/operations/evals/running-evaluations) against your Test sets.
 
 ## Frequently asked questions (FAQs)
 

diff --git a/build/agents/evals/introduction.mdx → build/operations/evals/introduction.mdx b/build/agents/evals/introduction.mdx → build/operations/evals/introduction.mdx
@@ -1,10 +1,10 @@
 ---
 title: 'Introduction to Evals'
 sidebarTitle: 'Introduction to Evals'
 description: 'Test and evaluate Agents and Workforces with simulated conversations and reusable scoring criteria'
 ---

 Evals is where you test and measure performance. It works on both Agents and Workforces, and lives in the **Evaluate** tab of the Agent or Workforce builder, next to **Build** and **Run**. Use it to create Test sets, define reusable scoring criteria, run evaluations, and monitor quality on live conversations.

 <div
  className="video-embed"
@@ -30,11 +30,11 @@
  ></iframe>
 </div>

 ## Why use Evals?

 Any time you put an Agent to work, you want to be sure it's accomplishing your business outcomes. That might be increasing marketing qualified leads, or reducing the time it takes to respond to a lead. Evals gives you the confidence that your Agent is hitting the mark with its target audience — and that it still does after the next change.

 You write Tests that simulate the users and situations you care about, and Evals scores each one against success criteria you define. Agents and Workforces are non-deterministic — the same input can produce a different answer, and a change to a prompt, a Tool, or a model can shift behavior somewhere you weren't looking — so holding the Tests and the criteria steady is what makes one version's score comparable to the next.

 <CardGroup cols={3}>
  <Card title="Run Tests" icon="flask-vial">
@@ -50,11 +50,11 @@

 ---

 ## Overview of Evals

 Evals has five core features, each with its own section in the left sidebar of the Evaluate tab:

 - **Test** — Create and manage Test sets. Each Test set holds Tests that simulate users; running a Test produces a conversation with the Agent or Workforce that gets scored by the criteria you attach.
 - **Runs** — Past evaluation run results. Browse average scores, tasks evaluated, progress status, cost (Credits and Actions), and creation date for every run.
 - **Checks** — Your library of scoring criteria; each one is called a Check. Create a Check once, then attach it to Tests, to Monitor dashboards, or to one-off evaluations of completed tasks.
 - **Publish** — Choose which Test sets must pass before your Agent or Workforce can be published. Set a minimum pass rate and optionally block publishing on failure.
@@ -89,13 +89,13 @@
 
 ---
 
-Next: Learn how to [create Tests](/build/agents/evals/test-sets) — the simulated conversations your Agent gets evaluated against.
+Next: Learn how to [create Tests](/build/operations/evals/test-sets) — the simulated conversations your Agent gets evaluated against.
 
 ## Frequently asked questions (FAQs)
 
 <AccordionGroup>
  <Accordion title="I don't see the Evaluate tab. How do I get access?">
    Evals is available on every plan. The **Evaluate** tab sits next to **Build** and **Run** in the Agent or Workforce builder — if it isn't there, [contact support](/get-started/support).
  </Accordion>

  <Accordion title="How are evaluations billed?">

diff --git a/build/agents/evals/monitor.mdx → build/operations/evals/monitor.mdx b/build/agents/evals/monitor.mdx → build/operations/evals/monitor.mdx
@@ -1,10 +1,10 @@
 ---
 title: 'Monitoring Evals'
 sidebarTitle: 'Monitoring Evals'
 description: 'Score the real conversations your Agent or Workforce is having against Checks, on dashboards you configure per sample rate'
 ---
 
-The **Monitor** section continuously scores live tasks against [Checks](/build/agents/evals/checks). Unlike the **Test** section, which runs simulated conversations, Monitor evaluates the real conversations your Agent or Workforce is having.
+The **Monitor** section continuously scores live tasks against [Checks](/build/operations/evals/checks). Unlike the **Test** section, which runs simulated conversations, Monitor evaluates the real conversations your Agent or Workforce is having.
 
 Monitor is organized into **dashboards** — you can create more than one (for example, one focused on tone, another on tool-use accuracy) and configure each independently.
 
@@ -44,7 +44,7 @@

 You also get:

 - **Overall score timeseries** to spot regressions or improvements over time.
 - **Per-Check charts** so you can see which criteria are slipping.
 - **Version markers** that line up score changes with each publish.
 - **A list of evaluation runs** with score, name, and a drill-in to the full conversation.

diff --git a/build/agents/evals/running-evaluations.mdx → .../operations/evals/running-evaluations.mdx b/build/agents/evals/running-evaluations.mdx → .../operations/evals/running-evaluations.mdx
@@ -1,10 +1,10 @@
 ---
 title: 'Running Evals'
 sidebarTitle: 'Running Evals'
 description: 'Run Test sets and individual Tests, read the scores that come back, and require evals to pass before publishing'
 ---
 
-Once you've created [Tests](/build/agents/evals/test-sets) and defined [Checks](/build/agents/evals/checks), you're ready to run evaluations and see how your Agent or Workforce performs. You can run them by hand, or have a publish run them for you.
+Once you've created [Tests](/build/operations/evals/test-sets) and defined [Checks](/build/operations/evals/checks), you're ready to run evaluations and see how your Agent or Workforce performs. You can run them by hand, or have a publish run them for you.
 
 ---
 
@@ -94,7 +94,7 @@
 
 ---
 
-Next: Learn about [monitoring Evals](/build/agents/evals/monitor) — scoring the real conversations your Agent or Workforce is having.
+Next: Learn about [monitoring Evals](/build/operations/evals/monitor) — scoring the real conversations your Agent or Workforce is having.
 
 ## Frequently asked questions (FAQs)
 

diff --git a/build/agents/evals/test-sets.mdx → build/operations/evals/test-sets.mdx b/build/agents/evals/test-sets.mdx → build/operations/evals/test-sets.mdx
@@ -4,7 +4,7 @@ sidebarTitle: 'Creating Tests'
 description: 'Create Tests that simulate real user conversations with your Agent or Workforce, and group them into Test sets'
 ---
 
-A **Test** simulates one conversation with your Agent or Workforce. You describe a user in the **Scenario** field — *"You are a long-time customer who was charged twice for the same order"* — and Relevance plays that user, generates their messages, and hands back the transcript. The [Checks](/build/agents/evals/checks) you attach score it.
+A **Test** simulates one conversation with your Agent or Workforce. You describe a user in the **Scenario** field — *"You are a long-time customer who was charged twice for the same order"* — and Relevance plays that user, generates their messages, and hands back the transcript. The [Checks](/build/operations/evals/checks) you attach score it.
 
 Tests live in a **Test set**, which is what a run points at — run the whole set, or a single Test inside it.
 
@@ -47,7 +47,7 @@ Tests live in a **Test set**, which is what a run points at — run the whole se
      </Tab>
    </Tabs>
 
-   See [Check types](/build/agents/evals/checks) for what each type scores and the fields it takes.
+   See [Check types](/build/operations/evals/checks) for what each type scores and the fields it takes.
 
 8. Set **When the test hits an approval** to control how the Test resolves Tool approvals and escalations mid-conversation:
 
@@ -112,7 +112,7 @@ Tests can be reorganized across Test sets as your testing strategy evolves. Each
 
 ---
 
-Next: Read the [Check types](/build/agents/evals/checks) reference — what each type scores and how the Checks tab works.
+Next: Read the [Check types](/build/operations/evals/checks) reference — what each type scores and how the Checks tab works.
 
 ## Frequently asked questions (FAQs)
 

diff --git a/...ents/build-your-agent/version-history.mdx → build/operations/version-history.mdx b/...ents/build-your-agent/version-history.mdx → build/operations/version-history.mdx
diff --git a/build/tools/create-a-tool.mdx b/build/tools/create-a-tool.mdx
@@ -99,4 +99,4 @@ Once you've created a Tool, explore the rest of the build guides to refine it:
 - [Inputs](/build/tools/customize-tool/inputs) — configure what data your Tool receives
 - [Steps](/build/tools/customize-tool/steps) — chain actions together into a workflow
 - [Outputs](/build/tools/customize-tool/outputs) — define what your Tool returns
-- [Version history](/build/agents/build-your-agent/version-history) — every save creates a snapshot you can restore, so you can experiment without losing working versions
+- [Version history](/build/operations/version-history) — every save creates a snapshot you can restore, so you can experiment without losing working versions
diff --git a/build/workforces/create-a-workforce.mdx b/build/workforces/create-a-workforce.mdx
@@ -42,4 +42,4 @@ Once you've created a Workforce, explore the rest of the build guides to refine
 - [Add Tools](/build/workforces/build-an-ai-workforce/add-tools) — connect Tools directly within your workflow
 - [Add conditions](/build/workforces/build-an-ai-workforce/add-conditions) — create routing rules for smarter workflows
 - [Edge settings](/build/workforces/build-an-ai-workforce/edge-settings) — configure how connections between nodes behave
-- [Version history](/build/agents/build-your-agent/version-history) — every save creates a snapshot you can restore, so you can experiment without losing working versions
+- [Version history](/build/operations/version-history) — every save creates a snapshot you can restore, so you can experiment without losing working versions
diff --git a/changelog.mdx b/changelog.mdx
@@ -12,7 +12,7 @@

 The newest version of Invent is now available.

 Invent can create and edit Agents, Tools, Workforces, Knowledge tables, Triggers, and Evals, run tasks, pull your analytics, and much, much more. It has context over everything in your project and acts as a specialist who can help you create almost anything inside of Relevance AI.

 Open Invent from the badge tucked into the right edge of the screen, from the button in the bottom-right corner of the Home page, or from Invent in the left navigation menu. Invent is enabled per project: an organization admin opens Settings → Projects, selects the project, clicks Manage settings, and turns on the Invent toggle. See [Build with Invent](/build/invent/invent) for more information on using and configuring Invent.

@@ -22,27 +22,27 @@

 ## Concurrency visibility for project and organization admins

 ![Concurrency panel showing a seven-day usage chart with queued runs stacked in red above the limit line, 20 of 20 slots in use with 6 tasks waiting, and a live capacity by project bar with other projects anonymized](/images/changelog/changelog-concurrency-visibility.png)

 Concurrency monitoring on the Analytics page now covers queued runs, live slot counts, and a per-project capacity breakdown.

 Queued runs now stack in red above the limit line on the usage chart, live counters show slots in use and tasks waiting, and a per-project bar attributes running slots to the projects holding them. Between them you can see whether you're at the limit, how much is queued behind it, and which project is consuming the capacity. Project admins see the same charts with other projects' names and task details anonymized.

 Project admins find the chart on the Analytics page; organization admins can also view it on the Plan & Billing page.

 </Update>

 <Update label="June 29, 2026" description="Eval cost breakdowns and Workforce evaluations">

 ## Eval cost breakdowns and Workforce evaluations

 ![Eval run cost breakdown panel showing total credits and actions, with per-component rows for Scenario Runner, Agent Execution, and Checks broken down by AI Judge model and Tool Usage](/images/changelog/changelog-eval-cost-breakdown.png)

 Eval runs now show exactly where their cost goes, itemized per check, and cover full Workforce runs including sub-agent and tool calls.
 
 Each completed Eval run renders a cost breakdown panel that itemizes credit and action consumption per component. Checks account for 1 action per run across every check type, including LLM as Judge and Tool Usage, so the panel's totals reconcile to the exact source of every credit and action. Workforce runs that fan out to sub-agents or call tools record and evaluate each of those interactions, the same as individual Agent runs.
 
-To see the breakdown, open any completed Eval run; the panel appears alongside the results. See the [Evals documentation](/build/agents/evals/introduction) for full details.
+To see the breakdown, open any completed Eval run; the panel appears alongside the results. See the [Evals documentation](/build/operations/evals/introduction) for full details.
 
 </Update>
 
@@ -80,7 +80,7 @@

 ![Microsoft Teams trigger settings showing the new Outreach replies only toggle enabled](/images/changelog/changelog-teams-outreach.png)

 Microsoft Teams triggers now support an **Outreach replies only** mode that limits responses to direct replies on the Agent's own outbound DMs.

 The trigger distinguishes between inbound replies (replies to messages your Agent sent) and channel mentions. In outreach-only mode, only inbound replies route to the Agent — channel chatter doesn't trigger a run.

@@ -134,7 +134,7 @@

 You can now manage public sharing settings for all agents, workforces, and tools from one central location!

 Project-Level Public Agent Controls give admins the power to disable public cloning and embeddability across their entire workspace with a single setting. When you disable these features at the project level, they’re automatically turned off for all agents, workforces, and tools—and individual users can’t re-enable them.

 ➡️ Centralized control – Manage security settings for all assets from one place

@@ -182,7 +182,7 @@

 ![Agent Performance Observability](/images/changelog/changelog-observability.webp)

 You can now track how your agents perform in real-world scenarios with comprehensive production monitoring!  Just like software development has build → test → monitor stages, agent development now has the same complete lifecycle. After building your agents and testing them with Evals, you need visibility into production performance at scale.

 ➡️ **Automatic evaluation** – Set up LLM judges to continuously assess your agents on custom criteria like summary quality, hallucination detection, and workflow execution

@@ -194,7 +194,7 @@

 With Agent Performance Observability, you can catch performance degradations immediately—like when a model update changes behavior or agents start hallucinating—instead of discovering issues weeks later.

 🔐 **Permissions required:** Available exclusively for select Enterprise customers. Evals delivers the advanced testing capabilities needed for mission-critical AI deployments. This feature is not available on non-Enterprise plans.

 To access Agent Performance Observability, enterprise users can go to their agent’s dashboard and select the “Monitor” tab, then navigate to the “Test Suites” section. If you’re on an Enterprise plan and don’t yet have access, contact your Relevance AI sales representative to register interest.

@@ -253,13 +253,13 @@

 </Update>

 <Update label="March 10, 2026" description="Monitor organization concurrency usage with detailed analytics and timeseries data">

 ![Monitor organization concurrency usage with detailed analytics and timeseries data](/images/changelog/changelog-concurrency.webp)

 **Org Concurrency Timeseries: Track Your Organization’s Performance Analytics**

 You can now monitor your organization’s concurrency usage and limits with detailed timeseries data!

 View comprehensive analytics directly from your organization settings page under the Plan & Billing section, giving you complete visibility into how your team uses Relevance AI’s resources.

@@ -269,9 +269,9 @@

 ➡️ Usage limit monitoring – Keep track of your current usage against your plan limits to avoid unexpected throttling

 ➡️ Visual timeseries charts – Easy-to-read graphs show your concurrency patterns, helping you identify optimization opportunities

 With Org Concurrency Timeseries, you can make data-driven decisions about your AI operations, ensuring optimal performance and resource allocation across your entire organization.

 🔐 Permissions required: Organization Admin access to view billing and usage analytics

@@ -507,11 +507,11 @@

 ![Claude Opus 4.6 model now available in Relevance AI](/images/changelog/68faec2d3ffbd34e9c9295b9-changelog-claude.webp)

 **Claude Opus 4.6: Anthropic's Most Advanced AI Model Now Available**

 You can now access Anthropic's flagship Claude Opus 4.6 model directly in the platform, with an optional 1M context window variant for handling massive documents!

 Claude Opus 4.6 delivers exceptional performance on complex reasoning, coding, and advanced agentic tasks. This latest version brings Anthropic's most powerful AI capabilities to your workflows, with both standard and extended context options to match your specific needs.

 ➡️ Standard 200K token context window – Process lengthy documents and conversations with ease

@@ -519,7 +519,7 @@

 ➡️ Adaptive thinking support – Tackle complex reasoning and multi-step problem solving

 ➡️ Advanced image processing – Work with jpg, jpeg, gif, webp, and png files

 ➡️ Exceptional output quality – Benefit from improved reasoning and response generation

@@ -563,15 +563,15 @@

 </Update>

 <Update label="February 9, 2026" description="Test and validate AI agents with Evals: Enterprise-grade agent testing">

 ![Test and validate AI agents with Evals](/images/changelog/698a6f9d99180607d34d642c-changelog-evals.webp)

 **Evals: Test and Validate Your AI Agents with Confidence**

 You can now thoroughly test your AI agents with our powerful Evals feature, ensuring they perform exactly as expected in real-world scenarios!

 Evals provides a structured testing framework for your AI agents, allowing you to create test suites with multiple scenarios to validate functionality. Create golden test examples, simulate user interactions, and evaluate agent performance without triggering actual tool executions or external actions.

 ➡️ Create organized test suites – Group related tests together for better organization and management

@@ -583,9 +583,9 @@

 ➡️ Coming soon: Tool simulations – Test workflows with sensitive or expensive tools without triggering actual executions

 With Evals, you can confidently deploy agents knowing they've been thoroughly tested against a variety of scenarios, ensuring reliability and consistent performance for your users.

 **Available exclusively for select Enterprise customers**, Evals delivers the advanced testing capabilities needed for mission-critical AI deployments. To access Evals, enterprise users can go to their agent's dashboard and select the "Monitor" tab, then navigate to the "Test Suites" section. If you’re on an Enterprise plan and don’t yet have access, contact your Relevance AI sales representative to register interest. This feature is not available on non-Enterprise plans.

 Start building more reliable AI agents with comprehensive enterprise-grade testing today!

@@ -665,11 +665,11 @@

 Workforce Trigger Controls give you granular management over your automation workflows. Quickly pause specific triggers when issues arise, cancel problematic workflows, or pause an entire workforce at once—then resume operations when you're ready.

 ➡️ Pause individual triggers – Temporarily stop specific automations without affecting others

 ➡️ Cancel active workflows – Immediately terminate problematic processes

 ➡️ Resume paused triggers – Restart automations when issues are resolved

 ➡️ Pause entire workforces – One-click solution to halt all triggers during maintenance

@@ -783,11 +783,11 @@

 ![Control your meeting agent in real time with chat commands](/images/changelog/695a95a2a931a05c425b7b72-changelog-meeting-bot-real-time-commands.webp)

 **Meeting Agent Realtime Commands: Control Your AI Agent During Live Meetings**

 You can now trigger your AI meeting agent with custom commands during live meetings without interrupting the flow of conversation!

 Meeting Agent Realtime Commands lets you interact with your meeting bot during meetings by simply typing trigger words in the chat. Your agent springs into action when it detects these keywords, performing tasks like searching information, controlling recordings, or creating meeting artifacts—all while your meeting continues uninterrupted.

 ➡️ Use custom trigger words – Define specific phrases that activate your agent during meetings

@@ -799,7 +799,7 @@

 ➡️ Extend with any Relevance AI capability – Connect to Notion, Slack, or other tools for seamless workflows

 With Meeting Agent Realtime Commands, you can enhance your meeting productivity by leveraging AI assistance exactly when you need it, without disrupting the conversation flow.

 To set up your own meeting agent with custom commands, create a new agent from scratch, add the "Relevance AI Meeting Bot" under Triggers, add and configure your desired meeting bot tools (such as 'Pause Recording' and 'Resume Recording') and more general tools (such as 'Google Search' and 'Slide Builder') and trigger words.


diff --git a/docs.json b/docs.json
@@ -110,6 +110,22 @@
                   "build/invent/invent"
                 ]
               },
+              {
+                "group": "Operations",
+                "pages": [
+                  {
+                    "group": "Evaluate Performance (Evals)",
+                    "pages": [
+                      "build/operations/evals/introduction",
+                      "build/operations/evals/test-sets",
+                      "build/operations/evals/checks",
+                      "build/operations/evals/running-evaluations",
+                      "build/operations/evals/monitor"
+                    ]
+                  },
+                  "build/operations/version-history"
+                ]
+              },
               {
                 "group": "Agents",
                 "pages": [
@@ -123,7 +139,6 @@
                       "build/agents/build-your-agent/alerts",
                       "build/agents/build-your-agent/memory",
                       "build/agents/build-your-agent/variables",
-                      "build/agents/build-your-agent/version-history",
                       {
                         "group": "Trigger Types",
                         "pages": [
@@ -167,16 +182,6 @@
                       }
                     ]
                   },
-                  {
-                    "group": "Evaluating Performance",
-                    "pages": [
-                      "build/agents/evals/introduction",
-                      "build/agents/evals/test-sets",
-                      "build/agents/evals/checks",
-                      "build/agents/evals/running-evaluations",
-                      "build/agents/evals/monitor"
-                    ]
-                  },
                   {
                     "group": "Running Tasks",
                     "pages": [
@@ -783,6 +788,30 @@
     }
   },
   "redirects": [
+    {
+      "source": "/build/agents/evals/introduction",
+      "destination": "/build/operations/evals/introduction"
+    },
+    {
+      "source": "/build/agents/evals/test-sets",
+      "destination": "/build/operations/evals/test-sets"
+    },
+    {
+      "source": "/build/agents/evals/checks",
+      "destination": "/build/operations/evals/checks"
+    },
+    {
+      "source": "/build/agents/evals/running-evaluations",
+      "destination": "/build/operations/evals/running-evaluations"
+    },
+    {
+      "source": "/build/agents/evals/monitor",
+      "destination": "/build/operations/evals/monitor"
+    },
+    {
+      "source": "/build/agents/build-your-agent/version-history",
+      "destination": "/build/operations/version-history"
+    },
     {
       "source": "/enterprise/org-project-controls-governance",
       "destination": "/enterprise/manage-projects-and-users-api"
@@ -1145,15 +1174,15 @@
     },
     {
       "source": "/evals",
-      "destination": "/build/agents/evals/introduction"
+      "destination": "/build/operations/evals/introduction"
     },
     {
       "source": "/build/agents/evals",
-      "destination": "/build/agents/evals/introduction"
+      "destination": "/build/operations/evals/introduction"
     },
     {
       "source": "/build/agents/build-your-agent/evals",
-      "destination": "/build/agents/evals/introduction"
+      "destination": "/build/operations/evals/introduction"
     }
   ]
 }
diff --git a/get-started/pricing.mdx b/get-started/pricing.mdx
@@ -151,17 +151,17 @@
 | **[1,000+ App Triggers](/build/agents/build-your-agent/agent-triggers/integrations)**                                        | ✓    | ✓   | ✓    | ✓          |
 | **[Premium Triggers](/build/agents/build-your-agent/agent-triggers/integrations)** (WhatsApp, LinkedIn, Telegram)            | ✗    | ✓   | ✓    | ✓          |
 | **[Build your own Triggers](/build/agents/build-your-agent/triggers)**                                                       | ✗    | ✓   | ✓    | ✓          |
 | **[Enterprise Triggers](/build/agents/build-your-agent/agent-triggers/integrations)** (Salesforce, Snowflake, Zendesk)       | ✗    | ✗   | ✗    | ✓          |

 ### AI management

 | Feature                                                          | Free | Pro | Team | Enterprise |
 | ---------------------------------------------------------------- | ---- | --- | ---- | ---------- |
 | **Use any LLMs with credits**                                    | ✓    | ✓   | ✓    | ✓          |
 | **Bring your own LLM**                                           | ✗    | ✓   | ✓    | ✓          |
 | **A/B Testing**                                                  | ✗    | ✓   | ✓    | ✓          |
 | **[Analytics Dashboard](/enterprise/analytics)**                 | ✗    | ✗   | ✓    | ✓          |
-| **[Agent Evaluations](/build/agents/evals/introduction)**    | ✗    | ✗   | ✗    | ✓          |
+| **[Agent Evaluations](/build/operations/evals/introduction)**    | ✗    | ✗   | ✗    | ✓          |
 | **Work Hour Controls**                                           | ✗    | ✗   | ✗    | ✓          |
 
 ### Security & compliance

diff --git a/guides/customer-success/account-health.mdx b/guides/customer-success/account-health.mdx
@@ -1,10 +1,10 @@
 ---
 title: "Account health and churn signals"
 sidebarTitle: "Account health"
 description: "Score every account on health with reasoning, not just a number. Surface risk before renewal so CSMs can act in time."
 ---

 Health scores that are just numbers don't get used. A health Agent rates accounts across the signals that actually predict churn — usage drops, support spikes, exec turnover, deal-stage stalls — and surfaces the *why* so CSMs can do something about it.

 ## When this pays off

@@ -13,7 +13,7 @@
    Churn risks are caught at renewal, not 90 days out when there's still time to fix them.
  </Card>
  <Card title="Health score is ignored" icon="eye-slash">
    The existing red/yellow/green field doesn't influence CSM action — nobody trusts the rollup.
  </Card>
  <Card title="Signals live in silos" icon="puzzle-piece">
    Usage data, support tickets, deal notes, exec changes — all in different tools, nobody synthesizes them.
@@ -55,11 +55,11 @@
  </Card>
 </CardGroup>

 Either way, these are prompts your CSMs can use on day one:

 - *"How is Acme Corp doing right now? Usage, tickets, last contact, anything I should worry about?"*
 - *"Which 5 accounts in my book look highest-risk for Q1 renewal?"*
 - *"Compare Globex's engagement this quarter vs. last — what changed?"*

 ## Where to take it

@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Pipe churn outcomes back into the Agent's [evals](/build/agents/evals/introduction) so scoring tracks what predicted cancellation.
+    Pipe churn outcomes back into the Agent's [evals](/build/operations/evals/introduction) so scoring tracks what predicted cancellation.
   </Card>
 </CardGroup>
 
@@ -81,7 +81,7 @@

 <AccordionGroup>
  <Accordion title="Score without reasoning" icon="magnifying-glass">
    A number alone is unactionable. CSMs need to see *which* signals moved and *why* the Agent flagged the account — otherwise they ignore it.
  </Accordion>
  <Accordion title="Stale signal definitions" icon="clock-rotate-left">
    Your churn drivers shift over time. Review the prompt's scoring criteria each quarter against actual churned accounts.
@@ -90,6 +90,6 @@
    Some segments use the product weekly and never churn; others log in monthly and stay loyal. Weight signals by segment, not globally.
  </Accordion>
  <Accordion title="No feedback loop from churned accounts" icon="arrows-rotate">
    Without piping churn outcomes back to the Agent's evals, the scoring can't learn. Connect closed-lost / churned status to evaluation runs.
  </Accordion>
 </AccordionGroup>
diff --git a/guides/customer-success/getting-started.mdx b/guides/customer-success/getting-started.mdx
@@ -1,10 +1,10 @@
 ---
 title: "Customer Success"
 sidebarTitle: "Getting started"
 description: "Put AI Agents to work across the post-sale journey — health, renewals, expansion — so CSMs spend time on the accounts that need them."
 ---

 CSMs are stretched across too many accounts. AI Agents take the watchful work — tracking signals, prepping QBRs, surfacing renewal risks — so CSMs focus on the conversations that actually move retention and expansion.

 ## Start with a Marketplace template

@@ -12,13 +12,13 @@

 <CardGroup cols={3}>
  <Card title="Atlas, the Account Analyst" icon="magnifying-glass-chart" href="https://marketplace.relevanceai.com/listing/678c9cf9-9b64-467a-8c51-e2d3db409fb1">
    In-depth research on an account, producing a structured report — useful before QBRs and renewal conversations.
  </Card>
  <Card title="Apla, the Account Planning Agent" icon="clipboard-list" href="https://marketplace.relevanceai.com/listing/fd712abc-66e4-4507-8f16-c4404cf5f5e5">
    Researches an account and writes the plan back to your CRM — handy for expansion across the book.
  </Card>
  <Card title="Browse the Marketplace" icon="store" href="/get-started/marketplace/introduction">
    The full catalog of Agents — health scoring, renewals, QBR prep, customer comms.
  </Card>
 </CardGroup>

@@ -55,7 +55,7 @@
 </Tab>

 <Tab title="Build visually" id="build-visually">
  You're comfortable in product UIs. You don't want to wire up an Agent from scratch, but you do want it to follow your CS playbook account by account. Open the cloned Agent in the builder and shape every piece.

  ## Connect the tools it needs

@@ -64,7 +64,7 @@
  - **CRM** — [HubSpot](/integrations/popular-integrations/hubspot) or [Salesforce](/integrations/popular-integrations/salesforce) for account data, deal stage, and renewal timing
  - **Support** — [Zendesk](/integrations/popular-integrations/zendesk) or Intercom for ticket activity and CSAT
  - **Product analytics** — your usage data source for engagement signals
  - **Comms** — [Gmail](/integrations/popular-integrations/gmail), [Slack](/integrations/popular-integrations/slack) for outreach and internal alerts

  See more about [Integrations](/integrations/introduction).

@@ -103,9 +103,9 @@

  ## Test before you trust
 
   Set up evals so health scoring or QBR-prep regressions get caught before they reach the CSM.
 
-  <Card title="Evals" icon="vial" href="/build/agents/evals/introduction">
+  <Card title="Evals" icon="vial" href="/build/operations/evals/introduction">
     Define test cases in the UI. Run them on every change.
   </Card>
 
@@ -119,7 +119,7 @@

  ## MCP & Plugins

  Connect your AI coding environment to Relevance AI over MCP. Describe what you want in natural language; your AI assistant reads and writes your Relevance workspace — system prompts, Tools, knowledge, triggers, workforces, evals.

  <CardGroup cols={2}>
    <Card title="Claude Code plugin" icon="terminal" href="/integrations/mcp/claude-code">
@@ -154,7 +154,7 @@
    Product usage drops on a key account → health score updates → the CSM is alerted with a draft outreach plan, all without anyone touching a dashboard.
  </Card>
  <Card title="L4 — Self-driving" icon="infinity">
    You set the objective — "reduce gross churn" — and the Workforce scores health, drafts outreach, and logs to the CRM, with its risk-signal criteria tuned through evals as churn outcomes flow back.
  </Card>
 </CardGroup>


diff --git a/guides/customer-success/qbr-prep.mdx b/guides/customer-success/qbr-prep.mdx
@@ -12,11 +12,11 @@
  <Card title="QBRs slip or shrink" icon="calendar-xmark">
    Reviews get canceled or shortened because nobody had time to prep — the customer notices.
  </Card>
  <Card title="Inconsistent across CSMs" icon="scale-unbalanced">
    Senior CSMs ship excellent QBRs; newer ones ship rough ones — the customer experience varies wildly.
  </Card>
  <Card title="Manual data pulling" icon="hammer">
    CSMs are exporting from HubSpot, screenshotting Looker, copying from Zendesk — the same way every time.
  </Card>
  <Card title="Strategic content is rushed" icon="hourglass">
    The "next quarter recommendation" slide always gets written last, briefly, because data prep ate the time.
@@ -58,8 +58,8 @@
 Either way, these are prompts your CSMs can use on day one:

 - *"Draft a QBR for Acme Corp covering last quarter — usage, support summary, business wins, recommended next steps."*
 - *"What did Globex achieve this year vs. their stated goals? Pull from CRM notes and product usage."*
 - *"Give me the operational summary slide for Initech's QBR — usage trends and support trend only."*

 ## Where to take it

@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Feed back which QBR sections landed into the Agent's [evals](/build/agents/evals/introduction) so the format tracks what's used.
+    Feed back which QBR sections landed into the Agent's [evals](/build/operations/evals/introduction) so the format tracks what's used.
   </Card>
 </CardGroup>
 
@@ -84,7 +84,7 @@
    A QBR that lists metrics without telling a story is just a report. Force the prompt to summarize what changed and why it matters.
  </Accordion>
  <Accordion title="Same QBR for every segment" icon="clone">
    Enterprise QBRs and mid-market QBRs should look different. Branch the prompt on segment so the depth and audience tone shift accordingly.
  </Accordion>
  <Accordion title="Auto-sending without CSM review" icon="paper-plane">
    Tempting to skip the CSM read. Don't — a misread on a strategic account is a relationship cost. The Agent drafts, the CSM ships.

diff --git a/guides/customer-success/renewal-expansion.mdx b/guides/customer-success/renewal-expansion.mdx
@@ -32,13 +32,13 @@
    Account, renewal date, health score, segmentation, last touch, prior QBR commitments.
  </Card>
  <Card title="Sources" icon="globe">
    CRM, prior QBRs, support history, usage data, your renewal playbook, expansion criteria.
  </Card>
  <Card title="Output" icon="file-lines">
    A renewal plan — recommended action sequence, drafted outreach for each step, expansion talking points where they apply.
  </Card>
  <Card title="Delivery" icon="paper-plane">
    Plan saved to the CRM, outreach drafts queued in [Gmail](/integrations/popular-integrations/gmail), expansion intel posted to the AE in [Slack](/integrations/popular-integrations/slack).
  </Card>
 </CardGroup>

@@ -55,11 +55,11 @@
  </Card>
 </CardGroup>

 Either way, these are prompts your CSMs can use on day one:

 - *"Acme Corp renews in 90 days — give me a 3-touch renewal plan with drafted emails, plus any expansion angle worth raising."*
 - *"What did we promise Globex at the last QBR? Draft a follow-up confirming we delivered before their renewal."*
 - *"Is Initech worth a price increase conversation this renewal? Pull usage and engagement signals to make the case."*

 ## Where to take it

@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Feed renewal outcomes back into the Agent's [evals](/build/agents/evals/introduction) so it leans on the plays that saved accounts.
+    Feed renewal outcomes back into the Agent's [evals](/build/operations/evals/introduction) so it leans on the plays that saved accounts.
   </Card>
 </CardGroup>
 

diff --git a/guides/customer-support/getting-started.mdx b/guides/customer-support/getting-started.mdx
@@ -4,7 +4,7 @@
 description: "Put AI Agents to work across the support queue — triage, drafting, knowledge — so agents handle the cases that need a human."
 ---

 Support teams are buried in repetitive volume that's faster to answer than to escalate. AI Agents take the routine — triaging tickets, drafting first replies, generating knowledge base articles from resolved cases — so human agents handle the cases that need judgment.

 ## Start with a Marketplace template

@@ -22,7 +22,7 @@
  </Card>
 </CardGroup>

 Click **Clone Agent** on any listing, connect your support tools (Zendesk / Intercom / Salesforce Service Cloud), and run on a real ticket.

 ## Pick your path

@@ -55,7 +55,7 @@
 </Tab>

 <Tab title="Build visually" id="build-visually">
  You're comfortable in product UIs. You don't want to wire up an Agent from scratch, but you do want it to follow your support playbook ticket by ticket. Open the cloned Agent in the builder and shape every piece.

  ## Connect the tools it needs

@@ -64,7 +64,7 @@
  - **Ticketing** — [Zendesk](/integrations/popular-integrations/zendesk), Intercom, or Salesforce Service Cloud for tickets and case history
  - **Knowledge base** — your KB system for citation-grounded responses
  - **CRM** — [HubSpot](/integrations/popular-integrations/hubspot) or [Salesforce](/integrations/popular-integrations/salesforce) for customer context
  - **Comms** — [Gmail](/integrations/popular-integrations/gmail), [Slack](/integrations/popular-integrations/slack) for follow-up and internal escalation

  See more about [Integrations](/integrations/introduction).

@@ -103,9 +103,9 @@

  ## Test before you trust
 
   Set up evals so regressions in tone or accuracy get caught before the Agent replies to a customer.
 
-  <Card title="Evals" icon="vial" href="/build/agents/evals/introduction">
+  <Card title="Evals" icon="vial" href="/build/operations/evals/introduction">
     Define test cases in the UI. Run them on every change.
   </Card>
 
@@ -119,7 +119,7 @@

  ## MCP & Plugins

  Connect your AI coding environment to Relevance AI over MCP. Describe what you want in natural language; your AI assistant reads and writes your Relevance workspace — system prompts, Tools, knowledge, triggers, workforces, evals.

  <CardGroup cols={2}>
    <Card title="Claude Code plugin" icon="terminal" href="/integrations/mcp/claude-code">
@@ -151,10 +151,10 @@
    An agent reviews a batch of new tickets — the Agent has already drafted replies and triage suggestions, the agent approves and sends.
  </Card>
  <Card title="L3 — Autopilot" icon="bolt">
    A new ticket lands → triaged, tagged, routed, first-reply drafted and auto-sent on simple cases, all without an agent touching the queue.
  </Card>
  <Card title="L4 — Self-driving" icon="infinity">
    You set the objective — "cut time-to-first-response" — and the Workforce triages, drafts, and routes, with its triage and template criteria tuned through evals as CSAT outcomes flow back.
  </Card>
 </CardGroup>


diff --git a/guides/customer-support/kb-generation.mdx b/guides/customer-support/kb-generation.mdx
@@ -73,7 +73,7 @@ Once it's running, deepen it in three moves:
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Feed read and deflection data back into the Agent's [evals](/build/agents/evals/introduction) so it drafts the formats that help.
+    Feed read and deflection data back into the Agent's [evals](/build/operations/evals/introduction) so it drafts the formats that help.
   </Card>
 </CardGroup>
 

diff --git a/guides/customer-support/response-drafting.mdx b/guides/customer-support/response-drafting.mdx
@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Feed back which drafts shipped untouched, plus CSAT, into the Agent's [evals](/build/agents/evals/introduction) so it matches what your team sends.
+    Feed back which drafts shipped untouched, plus CSAT, into the Agent's [evals](/build/operations/evals/introduction) so it matches what your team sends.
   </Card>
 </CardGroup>
 
@@ -87,7 +87,7 @@
    The Agent cites articles that don't exist or fabricates policy. Force citations to KB IDs from your actual catalog and fail visibly when there's no match.
  </Accordion>
  <Accordion title="Tone gets robotic" icon="robot">
    Without a strong tone-of-voice doc, every draft sounds like the same chatbot. Upload your best past replies as examples in Knowledge.
  </Accordion>
  <Accordion title="Auto-send before you're ready" icon="paper-plane">
    Auto-sending replies before you've watched the Agent on real tickets for a month is how you ship a bad answer at scale. Start with drafts only.

diff --git a/guides/customer-support/ticket-triage.mdx b/guides/customer-support/ticket-triage.mdx
@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Feed resolved-ticket outcomes back into the Agent's [evals](/build/agents/evals/introduction) so its triage tracks what actually held up.
+    Feed resolved-ticket outcomes back into the Agent's [evals](/build/operations/evals/introduction) so its triage tracks what actually held up.
   </Card>
 </CardGroup>
 
@@ -90,6 +90,6 @@
    Tickets get routed by topic only and miss the account dimension — a P3 from a churning enterprise account isn't a P3. Pull CRM context into the triage prompt.
  </Accordion>
  <Accordion title="Auto-applying without review" icon="robot">
    A wrong tag at scale corrupts reporting and routing. Start with Agent-as-suggester (writes to a "suggested_priority" field) and graduate to direct application after a quarter of audit.
  </Accordion>
 </AccordionGroup>
diff --git a/guides/marketing/campaign-analytics.mdx b/guides/marketing/campaign-analytics.mdx
@@ -35,7 +35,7 @@
    Marketing automation ([HubSpot](/integrations/popular-integrations/hubspot), [Marketo](/integrations/popular-integrations/marketo)), ad platforms (Google, Meta, [LinkedIn](/integrations/popular-integrations/linkedin)), web analytics, CRM, your own benchmark docs.
  </Card>
  <Card title="Output" icon="file-lines">
    A digest — top performers, underperformers, key shifts vs. last period, suggested actions — with cited data and reasoning.
  </Card>
  <Card title="Delivery" icon="paper-plane">
    Posted to [Slack](/integrations/popular-integrations/slack), written to a [Notion](/integrations/popular-integrations/notion) page for the team review, emailed to the CMO Friday morning.
@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Weight the Agent's [evals](/build/agents/evals/introduction) toward the metrics that actually predicted pipeline.
+    Weight the Agent's [evals](/build/operations/evals/introduction) toward the metrics that actually predicted pipeline.
   </Card>
 </CardGroup>
 

diff --git a/guides/marketing/content-repurposing.mdx b/guides/marketing/content-repurposing.mdx
@@ -1,6 +1,6 @@
 ---
 title: "Content creation and repurposing"
 sidebarTitle: "Content & repurposing"
 description: "Turn one piece of content into many — blog posts, social snippets, ad copy, email teasers — without losing the source voice."
 ---

@@ -16,7 +16,7 @@
    Every channel needs its own voice — copying the headline into Twitter doesn't work. Manual rewrites take hours per asset.
  </Card>
  <Card title="Webinar / podcast assets sit idle" icon="microphone">
    Hours of recorded content with no repurposing — clips, summaries, follow-up emails are all theoretically going to happen.
  </Card>
  <Card title="Big launch coming up" icon="rocket">
    A product launch needs 30+ derivative pieces and the content team has time for 5.
@@ -29,7 +29,7 @@

 <CardGroup cols={2}>
  <Card title="Inputs" icon="arrow-right-to-bracket">
    Source asset (blog, webinar transcript, video, whitepaper), target channels and formats, campaign goal.
  </Card>
  <Card title="Sources" icon="globe">
    Brand voice docs, channel-specific style guides, past top-performing posts per channel.
@@ -38,7 +38,7 @@
    A bundle of derivatives — blog posts, LinkedIn carousels, X threads, email teasers, ad copy variations — each tuned to its channel.
  </Card>
  <Card title="Delivery" icon="paper-plane">
    Posted to [Notion](/integrations/popular-integrations/notion) or a content doc for review, drafted into your scheduler (Buffer / Hootsuite), pushed to ad platforms via integration.
  </Card>
 </CardGroup>

@@ -73,7 +73,7 @@
     Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
   </Card>
   <Card title="Let it improve" icon="arrows-rotate">
-    Feed channel engagement back into the Agent's [evals](/build/agents/evals/introduction) so it leans on what performed.
+    Feed channel engagement back into the Agent's [evals](/build/operations/evals/introduction) so it leans on what performed.
   </Card>
 </CardGroup>
 

diff --git a/guides/marketing/getting-started.mdx b/guides/marketing/getting-started.mdx
@@ -4,7 +4,7 @@
 description: "Put AI Agents to work across the marketing funnel — content, campaigns, analytics — without losing your brand voice."
 ---

 Marketing teams are stretched across channels. AI Agents take the high-volume execution work — drafting nurture sequences, repurposing content, pulling cross-channel reports — so marketers can spend their time on strategy and storytelling.

 ## Start with a Marketplace template

@@ -43,7 +43,7 @@

  ## Make it run on its own

  When you find yourself drafting the same campaign every month, set a trigger — every new MQL gets the onboarding sequence drafted, every product launch triggers a content repurposing pass. One toggle, no code, no builder.

  <Card title="Triggers" icon="bolt" href="/build/agents/build-your-agent/triggers">
    Schedule runs, fire on CRM events, listen to webhooks.
@@ -55,7 +55,7 @@
 </Tab>

 <Tab title="Build visually" id="build-visually">
  You're comfortable in product UIs. You don't want to wire up an Agent from scratch, but you do want it to sound like your brand and follow your campaign cadence. Open the cloned Agent in the builder and shape every piece.

  ## Connect the tools it needs

@@ -103,9 +103,9 @@

  ## Test before you trust
 
   Set up evals so brand-voice regressions get caught before they ship to your list.
 
-  <Card title="Evals" icon="vial" href="/build/agents/evals/introduction">
+  <Card title="Evals" icon="vial" href="/build/operations/evals/introduction">
     Define test cases in the UI. Run them on every change.
   </Card>
 
@@ -119,7 +119,7 @@

  ## MCP & Plugins

  Connect your AI coding environment to Relevance AI over MCP. Describe what you want in natural language; your AI assistant reads and writes your Relevance workspace — system prompts, Tools, knowledge, triggers, workforces, evals.

  <CardGroup cols={2}>
    <Card title="Claude Code plugin" icon="terminal" href="/integrations/mcp/claude-code">
@@ -154,7 +154,7 @@
    A new MQL lands in HubSpot — segmentation, nurture-sequence drafting, and Slack alerts to the AE all happen automatically.
  </Card>
  <Card title="L4 — Self-driving" icon="infinity">
    You set the objective — "increase trial-to-paid conversion" — and the Workforce runs onboarding sequences, with subject lines, send times, and CTAs tuned through evals as conversion data flows back.
  </Card>
 </CardGroup>