Hiring Analytics In Chat
Talent Hub Agent makes "how's the pipeline?" and "which sources are working?" chat queries instead of dashboard hunts. Four tools across pipeline summary, open positions, hiring metrics, and source effectiveness. Read-only by design — candidate-level work lives in Recruiting Agent.
Why Hiring Analytics Stay In Slide Decks
Talent Hub Agent attacks the four 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. Time-to-fill should be visible alongside the open list — colored by target — 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. Cost per hire and quality per source live in a quarterly report that nobody refreshes — so budget decisions get made on instinct, not data.
Offer Acceptance Drops Quietly, Trend Goes Unnoticed
Offer acceptance was 88% last quarter; this quarter it's 82%. A 6-point drop is a leading indicator of comp issues, candidate experience issues, or competitor offers — but it goes unnoticed until the next slide deck because nothing alerts on the trend.
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 Outpace Recruiter Capacity Before Anyone Calls It Out
One recruiter is sitting on 28 open reqs across three departments. The dashboard shows the reqs; nobody shows the per-recruiter load. The roles that get filled are the ones with the loudest hiring manager — the rest stall, and nobody asks "do we need a fourth recruiter?" until headcount targets are blown.
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, conversion between stages, and time-to-fill 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, conversion rates, time-to-fill metrics.
- Configurable period — week, month, or quarter (default month).
- Funnel view — applied / screening / interview / offer / hired counts.
- Conversion rates between stages — surfaces where the funnel actually leaks.
Open Positions — Status Colored By Target
"What's open and which reqs are stale?" The agent returns the list of open positions with candidate counts and time-to-fill against target — so stale reqs surface before they become a hiring-manager complaint.
- list_open_positions — open jobs with candidate counts and status, optionally filtered by department.
- Department filter — partial-match on department name.
- Configurable limit — default 20, max 50.
- Status visible — distinguishes on-track, at-target, and stale reqs.
Hiring Metrics — The Real KPIs
Recruiting leaders ask "what's our application-to-interview rate this quarter?" and "is offer acceptance trending down?" The agent surfaces the headline hiring KPIs with the configurable period lens — month, quarter, or year.
- get_hiring_metrics — application-to-interview rate, interview-to-offer rate, offer acceptance rate, avg time-to-fill.
- Configurable period — month, quarter, or year (default quarter).
- Trend surfacing — designed for quarter-over-quarter conversations.
- Offer acceptance as leading indicator — early warning for comp or candidate-experience issues.
Source Effectiveness — Cost And Quality By Source
The agent surfaces sourcing analytics — applications by source, quality of hires by source, and cost per hire. "Should we spend more on referrals or LinkedIn?" becomes a question with numbers behind it, not a vibe.
- get_source_effectiveness — applications by source, quality of hires by source, cost per hire.
- Configurable period — month, quarter, or year (default quarter).
- Quality + cost together — the actual sourcing decision, not just volume.
- Budget signal — pairs naturally with the budget allocation conversation.
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 rate — share of open positions past their time-to-fill target.
- Offer acceptance rate — trend over time as a leading indicator of comp or candidate-experience issues.
- Cost per hire by source — and the share of hires coming from the lowest-cost / highest-quality 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's RISKY_TOOLS list is empty. 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 — RISKY_TOOLS list is empty. 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 — analytics are scoped to what the user can already see in the Recruiting app.
- Audit trail on every retrieval — every read call logs the requesting user, the tool used, and the parameters.
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, scoped per hiring manager, 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 ChatGPT leaks PII; the agent keeps everything inside the tenant boundary
- Scoped to what each hiring manager can already see in Recruiting — generic AI returns whatever was pasted
Greenhouse AI, Workday Recruiting AI, Eightfold AI
Vendor ATS AI — separate license, separate audit, separate roster
- Reads pipeline alongside HRIS, performance, and headcount plan — vendor ATS AI sees only ATS data
- Hiring managers without an ATS seat still see their own pipeline in the same MangoApps app
- One audit trail; 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 audit log 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
- Hiring managers see their own 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
Cost per hire and source-to-hire conversion ranked per source — surfaces what's actually working before next quarter's spend.
Permission-aware visibility
Hiring managers see their own reqs; recruiting leaders see the function; CHRO sees the company. The agent enforces it.
One audit trail
Every read call logs through AiApiLog with the same retention as the rest of the platform.
RubyLLM model tiering
Pipeline lookups run on small tier; period summaries on standard. Cost stays bounded even at company-wide hiring volumes.
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 tracked per bureau — within the FedRAMP-eligible boundary, 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, no extra recruiting-ops headcount running weekly pipeline decks.
More secure
Read-only by design — zero write tools, every retrieval logged through AiApiLog, every Recruiting visibility rule honored. Nothing leaves the tenant.
Easier to deploy
Already deployed if Recruiting is enabled. Turn the agent on and pipeline / source / metrics 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
Per-business period defaults, source taxonomies, and visibility rules 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. Only Talent Hub Agent can also see what's pending, what's interviewing, what's offered, and which sources actually convert — across week, month, and quarter, scoped to who's asking.
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
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Frequently Asked Questions About Talent Hub Agent
4 tools across pipeline analytics — get a pipeline summary (candidates by stage, conversion rates, time-to-fill), list currently open positions with candidate counts and department filter, get hiring metrics (application-to-interview, interview-to-offer, offer acceptance, avg time-to-fill), and get source effectiveness (applications by source, quality of hires by source, cost per hire).
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. RISKY_TOOLS is empty. 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.
get_pipeline_summary supports week, month, or quarter (default month). get_hiring_metrics and get_source_effectiveness support month, quarter, or year (default 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 rate (share of positions over target), offer acceptance trend, cost per hire 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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