Internal Sites Generated, Audited, And Approved
Spin up a department page — or a whole batch — with real employees, policies, forms, and training pulled live. Risky writes wait for your confirmation, and publishing can require approval.
Why Internal Sites Become Stale Within A Quarter
Sites Agent attacks the specific failures that turn a launched intranet into a graveyard within 90 days — without forcing the comms team to manage 24 pages by hand.
"Create A Department Page" Is A 3-Hour Job, Repeated 12 Times
Hero, quick links, team members lookup, news feed embed, stats, resources. Per department. Twelve departments. The math doesn't work, so most companies launch a portal with three pages and call it done. The agent's batch_create_pages turns 36 hours into one confirmation.
"Pull The Engineering Team Into A team_members Section" Means Manual Copy/Paste
Every page needs real employees, real policies, real forms, real training. Without live lookups into the org chart, Policy Hub, Forms, and Training, pages either go up with placeholder data or with copy/paste lists that drift the moment someone joins or leaves.
Stale And Empty Pages Pile Up Invisibly
A page goes up in January, nobody updates it, by August half the content is wrong and the other half is empty placeholder sections. Without an audit_site tool surfacing the rot, governance is reactive — and by the time someone notices, trust in the intranet is already gone.
AI Pages Get Published Without A Human Approving Them
A model-generated page about "leadership philosophy" sounds plausible but reads like LinkedIn slop. Without an approval-before-publish workflow that an actual approver has to approve, AI-generated content lands in the company's voice without ever passing through a human filter.
Section Types Pile Up But Nobody Knows Which One To Pick
over 50 section types. The page author wants "list of upcoming training" — is that an event grid, a resource list, a training embed, or a custom callout? Without a guided picker that knows the org's data sources, authors default to free-text blocks and the page loses its live-data connection.
Page Edits Get Made But Nobody Sees The Diff Before Publish
A comms admin updates the "benefits enrollment" page on Monday. The change reverts a paragraph the legal team added last week — and nobody catches it because the publish flow doesn't show a side-by-side diff. The mistake gets discovered after the all-hands email goes out.
Sites Agent At A Glance
Sites AI
AI page generation · org-grounded lookups · approval workflow · governance audit.
Inside Sites Agent — The Actual Capabilities
Every block below maps to real tools the agent uses against your Sites data. 50+ tools total — page CRUD, section CRUD, asset library, org lookups, navigation, approval workflow, governance audit, versioning, translation. Every risky write (publish, delete, batch, find/replace, restore) sits behind explicit confirmation.
Page Generation Grounded In The Org Chart And App Data
Page starters pre-wire the right section types for each archetype — operational_hub, executive_overview, onboarding_journey, knowledge_article, department_showcase, culture_page, initiative_launch. Lookups inject real data: lookup_employees for team_members sections, lookup_policies for policy links, lookup_forms for embedded widgets, lookup_training for resource hubs.
create_page_from_starter/create_site_from_starter— generate pages and full sites from page starters and starter sites, with real content auto-populated.- 5 visual modes — utility, balanced, editorial, executive, campaign — controlling spacing and layout density.
- 7 page archetypes — operational_hub, executive_overview, onboarding_journey, knowledge_article, department_showcase, culture_page, initiative_launch.
- Live org lookups —
lookup_employees,lookup_policies,lookup_forms,lookup_traininginject current data, not snapshots.
Batch Create + Approval Before Publish
batch_create_pages generates department, team, or initiative pages in one call — every page lands as a DRAFT, never auto-published. The approval workflow (request_page_review → approve_page_review / request_page_changes / reject_page_review) sends drafts to a named approver before publish_page takes the page live.
batch_create_pages— multiple pages in one call from page starters. RISKY · confirmation-gated. All output is DRAFT.- Approval workflow —
request_page_review(send for approval),approve_page_review,request_page_changes,reject_page_review, andwithdraw_page_reviewfor whoever asked. The approver it was sent to, or an admin, decides — nobody approves their own request, and admins publish without one. publish_page/publish_site/schedule_page_publish— three publish paths, all RISKY, all confirmation-gated.- Versioning + restore —
list_page_versions,compare_page_versions(read),restore_page_version(RISKY, destructive).
Content Audit, Self-Maintaining Pages, And Find/Replace — Governance That Stays Current
audit_site checks every page for stale content, empty sections, missing heroes and governance findings. Beyond staleness, self-maintaining content watches the live records each page references — policies, forms, people, events. Linked sections always show the current record, and when one changes or is removed the page is flagged for its owner to check the words around it. suggest_improvements returns per-page recommendations. find_and_replace sweeps a string across the entire site (preview by default, apply on confirmation).
audit_site— comprehensive content audit (stale pages, empty sections, missing heroes, governance findings).- Self-maintaining content — linked sections always show the current record; a daily scan flags pages whose linked policy / form / person / event changed or was removed, so the owner checks the words around it, and links to removed records can be cleared from the draft in one click.
list_stale_pages,list_expiring_pages— governance reads; a page is stale when nobody has republished it or marked it Still accurate within the tenant's review interval, and expiring lists take a configurable lookahead.mark_page_reviewed/set_page_owner— say a page is still accurate without editing it, or hand it to a new owner; both ask for confirmation.suggest_improvements/find_and_replace/bulk_update_sections— per-page recommendations and sweep-style edits; sweeps are dry-run by default,apply: true+ confirmation to commit.
Outcomes Teams Can Measure
The agent's job is to compress page-creation cycle time, keep org-data lookups live (not copy/paste), surface stale and empty content before employees do, and make sure nothing AI-generated gets published without a person approving it. Measure against your pre-agent baseline.
- Page-creation cycle time — hours from "we need a department homepage" to a published page passing approval, vs the manual baseline.
- Org-data freshness — share of team_members / policy / form / training sections sourced from live lookups vs static copy.
- Stale-page burndown — pages past the review interval either marked Still accurate, refreshed or archived per month, via
audit_site+list_stale_pages. - Approval override rate — share of AI-generated pages rejected or sent back for changes in the approval workflow; treats too-high as a quality signal.
- Find/replace adoption — sweep-style edits (rebrands, role-title updates, link migrations) done in one confirmation instead of page-by-page.
- AI reach — how often Ask AI draws on each page, from the built-in AI reach analytics; the modern measure of whether a page earns its keep.
Every Risky Write, Always With A Human In The Loop
Sites Agent flags more of its tools as risky writes than any other agent in the fleet, because Sites is a write-heavy authoring surface. Every one requires explicit user confirmation; the destructive ones (delete_page, delete_site, restore_page_version, remove_sections, find_and_replace with apply=true) carry warnings the user has to acknowledge.
- Publish gates —
publish_page,publish_site,schedule_page_publish. All RISKY, all confirmation-required. - Destructive deletes —
delete_page,delete_site,remove_section,remove_sections,remove_site_member. The confirmation prompt states what each one takes away.delete_pageanddelete_sitemove content to Trash and are recoverable: a page comes back as a draft withrestore_page(or the site's Manage › Pages › Trash) for 90 days, and a site withrestore_site(or All sites › ⋮ › Trash on the web, the only place a site can be deleted permanently). A trashed page's comments, version history and translations are deleted with it. The rest cannot be undone. - Sweep-style writes —
find_and_replace,bulk_update_sections,batch_create_pages,clone_page. Dry-run preview by default;apply: true+ confirmation required to commit. - Restore is destructive —
restore_page_versionreplaces current sections with the snapshot; the confirmation prompt explicitly warns the current content will be overwritten.
WHAT TEAMS TRY INSTEAD
The four alternatives — and none of them know your org chart, your policies, or your section types
Most intranet owners try one of these four first. None stick because none can pull from Policy Hub, Forms, Training, and the org chart in a single call — and none gate publish through an approval workflow that an actual approver signs.
ChatGPT, Claude, or Copilot draft + paste into the CMS
Generic AI writing pages a human still has to wire up
- Sites Agent inserts real team_members from the org chart, real policies from Policy Hub, real forms — not Lorem-ipsum prose
- batch_create_pages produces 12 department pages in one confirmation; copy/paste tops out at one page at a time
- audit_site surfaces stale and empty sections post-launch; generic AI has zero visibility into what's already shipped
SharePoint Copilot, Notion AI, or Confluence AI
Vendor-trapped page AI inside a single document silo
- Reaches into shifts, training, recognition, and HRIS to embed live data — vendor AI can't see across silos
- Over 50 archetype-aware section types (events, KB embeds, team grids, training lists) — not just rich-text blocks
- Approval-before-publish workflow with a side-by-side diff; SharePoint AI publishes the moment you click apply
Custom CMS + RAG retrieval layer
A platform team building Sites and the AI on top of it
- Already shipped — section schema, permissions, approval workflow, and confirmation-gated writes are in the platform
- Inherits per-business confirmation thresholds, audit-log retention, and the existing permission model for free
- New section types and tools land via the agentic framework — no rewrite when "we need a training section" comes in
The comms team writes 24 pages by hand
The default when AI tools don't fit the section model
- Generates a department homepage with real employees, policies, and forms in one prompt — not a 3-hour Notion build
- Cuts content audit from a quarterly spreadsheet exercise to a single audit_site call that flags stale and empty pages
- find_and_replace + bulk_update_sections do platform-wide sweeps that would take comms ops a week of manual edits
PLATFORM ADVANTAGE
Sites Agent inherits everything the platform already runs
A standalone intranet builder has to plumb each of these. Sites Agent gets them for free because the platform already owns them.
Live org chart and HRIS
team_members sections render real reports-to relationships and titles from the org chart — no copy/paste, no drift when someone joins or leaves.
Policy Hub and Forms inline — and self-maintaining
Sections embed live policies and forms by reference. They always show the current record, and when a referenced source changes or is removed the page flags itself for its owner — no quarterly link audit.
Over 50 archetype-aware section types
Page banners, quick links, KB embeds, training grids, event lists, stats, resources — the agent picks the right section for the data, not free-text blocks.
Approval-before-publish workflow
Every AI-generated page lands as a draft. Turn approval on and a named approver compares it with the live version and signs off before it goes live.
Audit trail with version restore
Every section edit logs to the audit trail; restore_page_version is itself RISKY-gated so a rollback is a deliberate act.
Metered, governed AI
The agent runs on the platform's governed model policy, and every call is metered against the tenant's AI credits, so cost stays visible as the org scales to hundreds of pages.
INDUSTRY FIT
Industries where an intranet builder pays back in weeks
Sites Agent shines where intranet scope is wide, content owners are scarce, and stale pages erode trust fastest.
Retail
Batch-creates a store-team page per location with the real district manager, store associates, and the local SOP set — no district ops admin writing 200 pages.
Healthcare
Department homepages link the live on-call schedule, current clinical SOPs, and the training each role must hold — no broken policy links during a Joint Commission visit.
Manufacturing
Plant-floor sites embed live safety bulletins and the current shift roster; audit_site flags empty quality and EHS sections before the corporate review.
Financial Services
Compliance landing pages auto-embed the latest policy versions with audit-trail attribution; FINRA examiners see who reviewed what when.
Hospitality
Per-property pages with the GM, the day's events, and the housekeeping SOP set — generated once, refreshed automatically as the team rotates.
Public Sector
Department portals are built with full audit logging. AI requests go to the platform's configured model providers.
WHY MANGOAPPS WINS
An embedded builder beats a generic AI, a SharePoint add-on, or a custom CMS on every axis
The argument finance, security, IT, and comms all share — and the one a horizontal AI or single-vendor assistant structurally cannot answer.
Cheaper than the alternatives
No SharePoint Copilot add-on, no Notion AI seat, no custom CMS build — and no comms week lost authoring and auditing 24 department pages by hand.
More secure
Every section read and write lands in the platform's AI audit log; confirmation-gated writes (publish, delete, batch, sweep, restore) sit behind explicit confirmation prompts.
Easier to deploy
Already deployed if Sites is enabled. Turn the agent on, point it at the org chart, and batch-generate department pages the same afternoon.
Easier to use
Lives inside Ask AI and the page editor — no separate chatbot, no copy/paste between a generic AI and a CMS, no second permissions model.
Easier to manage
One switch turns the agent on, a second keeps it read-only, and who may create sites and approve pages are chosen in the same Sites settings as everything else.
Easier to extend
New section types ship as tools, not rewrites. A new "training grid" section reaches the agent the same week it reaches the section catalog.
AI is actually better
A generic or vendor AI can draft a page. Sites Agent also embeds the live team, current policies, due training, and an upcoming-event grid — and routes it for approval before publish.
At our head office within HR, marketing, and finance, we use ChatGPT quite a bit, and MangoApps AI Helper is a useful tool for us. As I go around to the stores, I’ve been showing them how the AI Intranet Helper can find things and answer plain language questions about our resources, and they’re quite excited about that.
Alison van Zijl
Head of Human Resources
Full House
Customer Success
MangoApps Customers
Organizations that trust MangoApps to run every workflow across their workforce.
Customer Case Studies
Customer Case Studies
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Customer Case Studies
Customer Case Studies
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Frequently Asked Questions About Sites Agent
50+ tools spanning site CRUD, page CRUD, section CRUD (over 50 section types), asset library (browse + semantic search + upload), org lookups (employees, policies, forms, training), navigation, approval workflow, versioning + restore, translation, content audit, suggestions, and sweep-style writes (find/replace, bulk_update_sections, batch_create_pages). The risky ones — publish, delete, batch, sweep, restore — all require explicit confirmation.
No. publish_page, publish_site, and schedule_page_publish are all flagged risky and require explicit user confirmation. Generated pages default to DRAFT status, and with approval required the approval workflow (request_page_review → approve_page_review) routes through a named human approver before publish.
lookup_employees pulls from the org chart, lookup_policies from Policy Hub, lookup_forms from Forms, lookup_training from Training. Sections render against the live records, so an employee joining or leaving a department shows up in the team_members section without anyone editing the page.
Yes — self-maintaining content. Each page tracks the live records it references (policies, forms, people, events), and a linked section always shows the current record. A daily scan detects when one of those sources changes or is removed and flags the page for its owner, who checks the words around it and marks it still accurate, or clears links to removed records out of the draft in one click.
Yes. Separate from the authoring agent, an "Ask AI about this page" reader assistant lets an employee ask a question and get an answer grounded only in the content they're permitted to see, with the source page cited. Admins can also see how often Ask AI draws on each page in the AI reach card of Sites analytics.
find_and_replace defaults to dry-run (preview only) — the agent returns the matches it would change without changing them. To commit, the admin passes apply: true, which triggers the RISKY confirmation prompt before any text is modified. It only changes the text readers see — never links, web addresses or page titles — and on a published page the change is saved as a draft, so nothing goes live until the page is published; every changed page also gets a restore point in its history. The same find & replace is in each site's Manage › Pages for editors who don't use the assistant. bulk_update_sections follows the same dry-run-by-default pattern.
Page-creation cycle time (hours from request to published, vs manual), org-data freshness (share of sections sourced from live lookups), stale-page burndown per month via audit_site, approval override rate on AI-generated pages, and find/replace adoption for sweep-style edits. Compare against your pre-agent baseline.
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Rolled out to every employee at AutoZone (125,000), PetSmart (50,000+), A.S. Watson and Raley's (20,000) — and at larger retailers we are not permitted to name.
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