Hiring Analytics In Chat
"How's the pipeline?" and "which sources are working?" answered in chat — open positions, hiring metrics, source effectiveness. Read-only; candidate work lives in Recruiting Agent.
Why Hiring Analytics Stay In Slide Decks
Talent Hub Agent attacks the specific failures that turn recruiting analytics into a Monday-morning slide that nobody references the rest of the week.
Pipeline Health Lives In A Weekly Slide, Not In Chat
VP of People asks "how's the pipeline?" — answering means opening the ATS, exporting to a dashboard, and screenshotting it into Slack. By the time it's reviewed, the snapshot is already stale. Pipeline health should be a chat query, not a Monday ritual.
Time-To-Fill Doesn't Get Looked At Until It's Bad
Senior engineering reqs are over target by 18 days, and nobody notices until the hiring manager complains. How long each req has been open should be visible alongside the open list, so stale reqs surface before they become a complaint.
"Which Source Should We Spend More On?" Stays A Vibe
The recruiting team feels like Indeed is wasteful and referrals are gold, but nobody has the side-by-side numbers handy. Candidates and hires per source live in a quarterly report that nobody refreshes — so budget decisions get made on instinct, not data.
Offer Acceptance Gets Checked Once A Quarter
A drop in offer acceptance is a leading indicator of comp issues, candidate experience issues, or competitor offers — but the rate lives in a quarterly deck. Ask for the rate for last week, last quarter or the trailing year in chat and compare.
Funnel Conversion Rates Stay Trapped In Per-Stage Reports
Applied-to-screen, screen-to-interview, interview-to-offer — three numbers, three reports, no comparative view. The bottleneck might be at screen or at interview, but without a single funnel summary the recruiting leader keeps adjusting top-of-funnel spend when the drop is actually mid-funnel.
Open Reqs Go Stale Behind The Loudest Manager
The roles that get filled are the ones with the loudest hiring manager — the rest stall quietly. The agent lists the open reqs (up to 50 at a time, by department if you ask) with candidate counts and days open, so the quiet ones surface.
Talent Hub Agent At A Glance
Talent Hub AI
Pipeline summary, open positions, hiring metrics, sources.
Inside Talent Hub Agent — The Actual Capabilities
Every block below maps to a real tool the agent uses against your hiring data. Four read tools — pipeline summary, open positions, hiring metrics, and source effectiveness — designed for recruiting leadership conversations. Candidate-level work happens in the Recruiting Agent.
Pipeline Summary — Live, Configurable Period
"How's the pipeline?" gets a real answer — candidates by stage, open job count, and conversion between stages across the configurable period. The Monday-morning slide becomes a chat query that anyone in leadership can run any day of the week.
get_pipeline_summary— total candidates by stage, open job count, conversion rates.- Configurable period — week, month, quarter, or year (default month).
- Funnel view — applied / screening / interview / offer / hired counts.
- Conversion rates between stages — surfaces where the funnel actually leaks.
Open Positions — With Days Open
"What's open and which reqs are stale?" The agent returns the list of open positions with candidate counts and how many days each has been open — so stale reqs surface before they become a hiring-manager complaint.
list_open_positions— open jobs with candidate counts, location and days open, optionally filtered by department.- Department filter — partial-match on department name.
- Configurable limit — default 20, max 50.
- Days open — the age of every open req, so the oldest stand out.
Hiring Metrics — The Real KPIs
Recruiting leaders ask "what's our application-to-interview rate this quarter?" and "what was offer acceptance last month?" The agent surfaces the headline hiring KPIs for the window you ask about — week, month, quarter, or year.
get_hiring_metrics— application-to-interview rate, interview-to-offer rate, offer acceptance rate, avg time-to-fill.- Configurable period — week, month, quarter, or year (default quarter).
- Compare windows — ask the same question for week, month, quarter or year; the agent reports each window's figure and does not compute a change or alert.
- Offer acceptance — the rate for the window you ask about.
Source Effectiveness — Volume And Hires By Source
The agent surfaces sourcing analytics — candidates, hires and hire rate for each recruiting source. "Should we spend more on referrals or LinkedIn?" becomes a question with numbers behind it, not a vibe. Cost per hire by source lives on Talent Hub's Source Analytics page.
get_source_effectiveness— candidates, hires, and hire rate by source.- Configurable period — week, month, quarter, or year (default quarter).
- Hires, not just volume — the hire rate per source is the sourcing decision.
- Budget signal — pairs with the cost figures on the Source Analytics page.
Outcomes Teams Can Measure
The agent's job is to put recruiting analytics in front of leadership every day — without adding work to the recruiting ops team. Measure against your pre-agent baseline.
- Average time-to-fill — the headline pipeline-velocity metric.
- Stale-req count — open positions that have been open longest.
- Offer acceptance rate by window — a leading indicator of comp or candidate-experience issues.
- Hire rate by source — and the share of hires coming from your best-converting sources.
- Analytics-query frequency — how often leadership pulls pipeline data via agent vs. ad-hoc dashboard pulls.
Intentionally Read-Only · Candidate Work Lives In Recruiting Agent
Talent Hub Agent has no write tools at all. The agent surfaces aggregated analytics — pipeline, positions, metrics, sources — for leadership conversations. Candidate-level work (screening, outreach, offers) is the Recruiting Agent's job, where writes are explicitly gated. The two agents compose; the responsibilities don't blur.
- Zero write tools — strictly read-only. No req edits, no candidate moves, no analytics overrides through chat.
- Composes with Recruiting Agent — Talent Hub answers "how's it going?"; Recruiting Agent does the candidate-level work.
- Permission-aware — only people who can already open Talent Hub get answers.
- Audit trail on every retrieval — every read call is logged with the requesting user and the tool used; the AI request log keeps detail for 30 days.
WHAT TEAMS TRY INSTEAD
The four alternatives — and none of them know your pipeline, your sources, or your hiring SLAs
Hiring analytics usually means an ATS dashboard the recruiting leader exports into a slide deck weekly. None of the alternatives keep the answer fresh, inside your tenant's permissions, and one prompt away — and none compose cleanly with a candidate-level recruiting agent.
ChatGPT, Claude, or Copilot on pasted ATS exports
Generic AI on stale pipeline CSVs
- Talent Hub Agent reads live pipeline, open reqs, source effectiveness — generic AI sees Monday-morning export
- Pasting candidate-pipeline data into a personal ChatGPT account leaks PII; the agent works under your tenant's permissions, with every tool call logged
- Answers only people who can already open Talent Hub — generic AI returns whatever was pasted to whoever asks
Greenhouse AI, Workday Recruiting AI, Eightfold AI
Vendor ATS AI — separate license, separate audit, separate roster
- Lives on the same platform as your HRIS, performance, and headcount apps — vendor ATS AI sits in a separate system
- Managers without an ATS seat ask about the pipeline in the same MangoApps app
- Every tool call logged in MangoApps; ATS AI forces parallel SSO and roster sync that drifts the day a hiring manager moves teams
Custom recruiting dashboard in Tableau / Looker
A people-analytics build, then maintenance for every new pipeline question
- Already shipped — pipeline summary, position counts, hiring metrics, source effectiveness, and a log of every tool call in place
- Period lenses (week / month / quarter / year) work without writing new SQL each time leadership asks
- Composes with Recruiting Agent — analytics here, candidate-level work there, both inherit the same permission model
"Ask recruiting ops for the weekly pipeline deck"
The status quo — recruiting leaders building reports
- "How's the pipeline?" / "which sources are working?" answered in seconds — not a weekly slide build
- Leaders see the open reqs without an ops ticket — recruiting team gets time back
- Source effectiveness visible per period without re-running an ATS report
PLATFORM ADVANTAGE
Talent Hub Agent inherits everything the platform already runs
A standalone recruiting analytics tool has to plumb each of these. The agent gets them for free.
Composes with Recruiting Agent
Talent Hub answers "how's it going" — Recruiting Agent does the candidate-level work. Same identity, same permission model.
Period lenses without new SQL
Week / month / quarter / year scoping built in — same prompt, different lens, no recruiting ops report rewrite.
Source effectiveness as a primitive
Candidates, hires, and hire rate ranked per source — surfaces what's actually working before next quarter's spend.
Permission-aware visibility
The agent answers only people who can already open Talent Hub, and only from your own tenant's data. The agent enforces it.
Every tool call logged
Every read call is logged with the requesting user and the tool; the AI request log keeps detail for 30 days.
Automatic model tiering
The platform assigns each agent one model tier suited to its work — set for the agent, not picked per question.
INDUSTRY FIT
Industries where pipeline visibility moves the most weight
Talent Hub Agent shines where hiring velocity gates revenue, ops, or compliance.
Retail
Store-manager and seasonal pipelines visible per district — VP-Ops sees gaps before holiday peak, not after stores under-staff.
Healthcare
RN and tech pipelines tracked by unit and shift — CNO sees coverage risk before agency-spend balloons.
Manufacturing
Production-operator and EHS pipelines per plant — plant manager sees the funnel before line uptime suffers.
Hospitality
Seasonal and post-event hiring visible per property — GMs see funnel and source health without an HR-ops report.
Financial Services
Licensed-advisor and compliance-officer pipelines with regulatory-clock visibility — leadership sees hiring runway against board commitments.
Public Sector
Civil-service and seasonal hiring is tracked per bureau, with no separate ATS analytics seat.
WHY MANGOAPPS WINS
An embedded hiring-analytics agent beats a dashboard, an ATS module, or a custom report on every axis
The argument recruiting, finance, IT, and the executive team all share — and the one a horizontal AI or a single-vendor ATS AI structurally cannot answer.
Cheaper than the alternatives
No Greenhouse AI add-on, no Eightfold seat fee, no Tableau-build cost — and recruiting ops stops building weekly pipeline decks.
More secure
Read-only by design — zero write tools, every retrieval audit-logged, every Recruiting visibility rule honored. AI requests go to the platform's configured model providers, like every MangoApps agent.
Easier to deploy
Already deployed once Talent Hub is enabled — the agent is on by default, and pipeline / source / metrics questions work the same day.
Easier to use
"How's the engineering pipeline this quarter" / "which sources convert" — one prompt, no dashboard hunt.
Easier to manage
The agent's on/off switch, the source taxonomy, and who can open Talent Hub sit in the same admin console as every other app's settings.
Easier to extend
New analytics surfaces (DEI lens, location lens, regretted-attrition cross-ref) ship as tools — picked up the same release.
AI is actually better
A vendor or generic AI can chart open reqs. Talent Hub Agent also sees what's pending, what's interviewing, what's offered, and which sources actually convert — across week, month, quarter, and year, for the people allowed to ask.
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.
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Frequently Asked Questions About Talent Hub Agent
4 tools across pipeline analytics — get a pipeline summary (candidates by stage, open job count, conversion rates), list currently open positions with candidate counts, days open and a department filter, get hiring metrics (application-to-interview, interview-to-offer, offer acceptance, avg time-to-fill), and get source effectiveness (candidates, hires, and hire rate by source).
Talent Hub Agent is the analytics lens — read-only, leadership-facing, aggregate metrics for "how's hiring going?" conversations. Recruiting Agent is the candidate-level operator — pipeline visibility, AI screening, interview scheduling, outreach, and offer generation with three explicitly-gated write actions. They compose: leaders use Talent Hub; recruiters and hiring managers use Recruiting.
No. The agent has no write tools. Talent Hub Agent retrieves and surfaces analytics; it cannot edit a requisition, move a candidate, or override a metric. Any changes happen in the Recruiting app or through the Recruiting Agent's gated write actions.
All three period-taking tools accept the same four windows — week, month, quarter or year. get_pipeline_summary defaults to month; get_hiring_metrics and get_source_effectiveness default to quarter. The period filter on every tool lets leadership flex from "last week" to "trailing year" without leaving chat.
Average time-to-fill, stale-req count (positions open longest), offer acceptance rate by window, hire rate by source, and analytics-query frequency (how often leadership pulls pipeline data via agent vs. ad-hoc). Compare against your pre-agent baseline.
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