ZingHR
Also known as: Cnergyis
Enterprise HCM for India, the Middle East and Southeast Asia, running eight named AI agents over one unified employee database: payroll that reconciles itself, a policy-grounded assistant on WhatsApp and Teams, and a no-code approval engine that timestamps every transaction it touches.
ZingHR is a Mumbai-based enterprise HCM platform used by more than 1,200 organizations and 2.8 million employees across India, the Middle East and Southeast Asia, backed by the Tata Capital Growth Fund. Its argument is architectural: 35+ modules built in-house by one team on a single codebase and a single database, covering the employee lifecycle from first candidate click to alumni re-hire, rather than a suite assembled from acquisitions.
Eight named agents run on top of it. ZingZeroTAP closes attendance and payroll on a self-reconciling cycle across every pay structure, location and currency an organization operates in. A recruitment agent runs cognitive assessment, personality profiling and ranked shortlists. Others cover engagement and grievance handling, continuous performance tracking against OKRs, microlearning in 32 languages, the confirmation-to-separation lifecycle, multi-country travel and expense, and round-the-clock monitoring of every payroll jurisdiction with real-time alerts.
The Zing Intelligence Hub is the layer they share. ZingBot answers employee questions on WhatsApp, Teams or the ZingHR app, grounded through retrieval-augmented generation in the organization's own policies and the asking employee's own record rather than in generic HR guidance; Zingo turns the answer into the transaction, raising leave applications, submitting claims and regularizing attendance in conversation.
Where a request needs a decision, a no-code Workflow Engine routes it for approval, pushes it to the manager and escalates to a human ticket when the agent cannot close it. Every transaction it handles is time-stamped, attributed and written to a permanent audit trail. Nineteen live Power BI dashboards and over a hundred auto-generating reports sit above it, with row-level security deciding at login what each viewer can see.
ZingHR sells twelve vertical configurations, each built around the compliance requirements of its sector, and integrates outward to SAP, Oracle and Dynamics 365 alongside host-to-host banking connections that disburse payroll directly. Customers can push data in and pull it out through documented APIs. It runs as cloud software on Microsoft Azure, priced through a sales conversation rather than a published rate card.
Vendor details
Canonical URL
https://www.zinghr.com
Category
Enterprise operations agent
Subcategory
Enterprise HCM — agentic HR and payroll operations
Funding status
Private. Mumbai headquartered enterprise HCM company backed by Tata Capital, Microsoft Accelerator, Mumbai Angels, and Erasmic Venture Fund. Serves enterprises across India, the Middle East, Southeast Asia, and Australia. No round figures are disclosed.
Company status
independent
Use cases & customers
Primary use cases
Target customers
Deployment options
Integrations
ZingHR states 100+ enterprise integrations, and the categories beneath the count are named: ERP through SAP, Oracle and Dynamics 365; communication through Zoom, Microsoft Teams and WhatsApp; plus assessment platforms. The connector that matters most is host-to-host banking across HDFC, HSBC, JPMorgan and ICICI with automated payroll disbursement, which is the platform moving money in a third-party system rather than syncing records. ZingHR's support portal records the API route in production against real systems: Xero globally in both directions, SAP SuccessFactors read through ZingHR's own pull APIs against SAP's exposed endpoints for recruitment, and Oracle PeopleSoft attendance fed by push. The no-code Workflow Engine adds external API orchestration, so a customer-built approval flow can reach a system with no prebuilt connector. Inbound, ZingHR documents customer push and pull APIs with a published reference, five shipped pull endpoints covering employee, master, leave, attendance and exit data, and a separate UAT environment. Naukri and LinkedIn integration is described as roadmap and is not counted.
In practice
A field employee asks on WhatsApp how much leave is left, ZingBot answers from the company's own policy and the employee's record, and Zingo raises the leave application, which reaches the manager as a push notification for approval.
A payroll team closes one cycle across every pay structure, location and currency while ZingZeroTAP reconciles attendance on its own, and salaries go out through host to host banking with HDFC, HSBC, JPMorgan or ICICI.
Asked by an auditor who approved a claim, an HR team pulls the Workflow Engine's audit trail for the transaction Zingo raised instead of searching through email.
Sources & related URLs
Related / legacy domains
Research sources
Agentic Index coverage score
9.0 / 14 capabilities · 64%
| Integrations & Tool Calling | Full |
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ZingHR lists 100+ enterprise integrations, with SAP, Oracle and Dynamics 365 alongside Zoom, Teams and WhatsApp, and prebuilt coverage across ERP, banking, assessment and communication platforms. In production, Xero connects globally through both API routes, SAP SuccessFactors is reached through ZingHR Pull APIs against SAP's own exposed APIs for recruitment, and Oracle PeopleSoft attendance is fed by ZingHR Push APIs. Host to host banking covers HDFC, HSBC, JPMorgan and ICICI with automated payroll disbursement, so the platform moves money in a third party system on the customer's behalf. External API orchestration in the Workflow Engine connects workflows to data in external systems, so a flow the customer configures can reach a system with no prebuilt connector. In the other direction, customer Push and Pull APIs let outside systems call ZingHR, and requests arrive through WhatsApp, Teams and the ZingHR app. Naukri and LinkedIn are not connected yet and are on the product roadmap. Sourcezinghr.com/solutions/zing-intelligence-hub with support.zinghr.com integrations articleread 2026-09-12 |
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| Workflow Orchestration | Full |
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The signature ZingBot workflow runs twelve numbered steps: employee initiates query, WhatsApp based access, live database lookup, RAG powered retrieval, employee specific context, policy validation, instant AI response, resolution in under five seconds, transaction requirement detected, Zingo raises request, smart escalation triggered, auto routed support ticket. It branches, since step 09 decides whether the run ends at an answer or continues into a transaction, and step 11 diverts to a person. The Workflow Engine is the part customers configure, a no code builder with a drag-and-drop form builder with conditional fields and approval routing, separate flows for operational and strategic approvals, and external API orchestration that connects steps to systems outside ZingHR, so a flow can be set up for any non-standard process without code or an IT ticket. ZingZeroTAP holds state across a long cycle, with real time, self reconciling attendance and payroll across every pay structure, location and currency and no manual intervention. Self reconciling means the process finds and resolves its own discrepancies between runs, and a payroll cycle spans weeks of attendance events across jurisdictions before it closes. The Employee Life Cycle Agent works the same way over a longer horizon, from confirmation to separation, with every milestone structured, documented and executed. The participants are the employee raising a request, the manager approving it, the HR administrator configuring the flow, the person receiving an escalated ticket, and the external systems each step reads and writes. Sourcezinghr.com/solutions/zing-intelligence-hub signature workflow and Workflow Engine, with the homepage agent setread 2026-09-12 |
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| Knowledge Grounding & RAG | Full |
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ZingBot answers HR queries through WhatsApp, Teams or the ZingHR app, grounded in the customer's actual policies through retrieval-augmented generation, not generic large language model output. ZingHR contrasts generic assistants that answer with generic HR policy with ZingBot answering from the customer's actual policy, the employee's actual data and the organization's actual rules. Every transaction across every ZingHR module writes to a single unified database with no ETL, no overnight batch and no sync delay, and dashboards load live data the moment they open, so the corpus is kept current, not assembled for each run. Retrieval is its own step. Steps 03 to 06 of the ZingBot workflow are live database lookup, RAG powered retrieval, employee specific context and policy validation, so the answer is checked against policy, not just generated near it. Unstructured content has a way in, since ZingLens OCR extracts GSTIN, amount, date and claim type from photographed bills and pre-fills the form. Row level security applies at login, so each persona reaches only its authorized data, which bounds what retrieval can reach. ZingHR does not describe citations back to the policy behind an answer, how the policy corpus is loaded or refreshed, or any freshness or confidence signal on a response. Sourcezinghr.com/solutions/zing-intelligence-hubread 2026-09-12 |
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| Human Oversight & Guardrails | Full |
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The Workflow Engine is ZingHR's own approval mechanism, and the customer shapes it. It is no code workflow automation with separate flows for operational and strategic approvals, a drag-and-drop form builder with conditional fields and approval routing, and custom approval flows for any non-standard process without code or an IT ticket. Zingo, the conversational automation layer, raises leave applications, submits claims and regularizes attendance through conversation. Those transactions enter the approval flow instead of completing themselves, and approvals arrive as push notifications to be actioned in 30 seconds, so an action the agent raises waits on a named person before it takes effect. Escalation is the second mechanism. The last steps of the ZingBot workflow are transaction requirement detected, smart escalation triggered and auto-routed support ticket, so the agent hands off to a person when a case exceeds it. ZingHR argues against approvals that live in email and get lost in someone's inbox with no tracking, no audit trail and no accountability, and the same Workflow Engine carries the audit trail and the multistep conditional sequencing. There is no confidence threshold, autonomy dial, override log or reviewer queue object. Sourcezinghr.com/solutions/zing-intelligence-hubread 2026-09-12 |
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| Security, Identity & Governance | Full |
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ZingHR's operational center is certified to ISO 27001:2013, and elsewhere ZingHR says only that it meets standards like ISO 27001. ZingHR runs periodic network and application penetration tests of the cloud service infrastructure, and a named security team runs risk assessment and treatment across strategic, financial, regulatory, compliance, management, operational and technical domains. Row level security applies at login and scopes data by persona, so the CHRO sees the full organization, the HRBP their business unit, the CFO costs and the manager their team, and each persona sees only its authorized data with no manual configuration. For an agent answering from one employee database, that row boundary decides what the assistant can reach. Microsoft Azure holds ISO 27001, HIPAA, FedRAMP, SOC 1, SOC 2, IRAP, G-Cloud and MTCS for the underlying infrastructure, and ZingHR's own attestation is the ISO 27001 certificate. That certificate names ISO 27001:2013, a version since superseded by ISO 27001:2022 with the transition window closed, and there is no trust center, certificate registry or renewal date. There is no single sign on, SCIM, MFA or role model beyond row level security, customer audit is restricted in the multitenant environment, and security controls and audit reports can be reviewed on request. Sourcesupport.zinghr.com audit-and-compliance article, with Row-Level Security from zinghr.com/solutions/zing-intelligence-hubread 2026-09-12 |
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| Observability & Auditability | Full |
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Every workflow transaction, ZingHR says, is time-stamped and attributed with a permanent, immutable audit trail, which records when it happened and who or what acted, and cannot be edited after the fact. Zingo raises leave applications, submits claims and regularizes attendance through the Workflow Engine, so actions the agent starts land in the trail with attribution, not as anonymous system events. A customer can reconstruct what the agent did, when and on whose behalf in the transactional layer, which is where these agents operate. ZingHR says email approvals have no tracking, no audit trail and no accountability, and claims an 80% reduction in audit prep time. ZingHelp SLA compliance is tracked as a KPI, and the nineteen ZingIntel dashboards report headcount, attrition, payroll, performance, recruitment and succession, which measure the workforce, not the agent. The trail covers workflow transactions only. There is no trace of ZingBot's retrieval or reasoning for each run, no record of which policy documents a RAG answer drew on, no confidence or citation trail on the conversational side, and no export or retention policy for agent activity or the trail itself. Sourcezinghr.com/solutions/zing-intelligence-hubread 2026-09-12 |
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| Memory & State Persistence | Not documented |
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ZingHR describes a system of record, not agent memory. Its central claim is one employee record, one source of truth, one database and real time data flow, with every transaction across every module writing to the single unified database. That persistent store of employee records is a data model, and the agent queries it for retrieval. The homepage says the platform learns from itself and that intelligence compounds at every stage, but neither phrase describes state the agent keeps, scopes and can retrieve, or anything a customer could inspect. The closest thing is step 05 of the ZingBot sequence, employee specific context, which assembles the requesting employee's record to answer the question in front of it and carries nothing from a previous conversation. Nothing says a second query knows what the first one asked, that a correction is reapplied or that a preference survives the session, and the sequence runs from query to resolution in under five seconds and ends. There is no named memory component, ZingBot conversation history or thread persistence, retained user preference, decision trace reused between runs, scope or lifetime for agent state, or way to inspect, edit, export or purge it apart from employee records. Row level security governs what the assistant may read. Sourcezinghr.com/solutions/zing-intelligence-hub with the homepage architecture claimsread 2026-09-12 |
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| Deployment & Data Residency | Not documented |
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ZingHR names its hosting, and it leaves the customer no control. The application runs on Microsoft Azure, and in what ZingHR calls the united hosting environment it is multi-tenant, with customer access for audit restricted. No other environment is named. ZingHR runs three regional site variants (IND, MEA and SEA), serves 30+ countries and localizes payroll compliance for each jurisdiction, but those are markets and statutory rules, not places a customer chooses to keep its data. A customer with an Indian, UAE or Singaporean data localization obligation cannot choose where its tenant is hosted or run ZingHR in its own environment. There is no region list, region picker, single tenant tier, private cloud, on premises option or self hosting. Sourcesupport.zinghr.com audit-and-compliance article, with zinghr.com regional navigationread 2026-09-12 |
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| Prebuilt Agents / Templates / Packs | Full |
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Three catalogs can be browsed. The homepage lists eight named agents under their own heading, each with its own description and job. The AI Recruitment Agent runs cognitive assessments, personality profiling and AI ranked shortlists. The ZingZeroTAP Agent handles real time, self reconciling payroll. The Engagement Agent covers pulse surveys, grievance resolution and sentiment tracking. Compliance 24/7 monitors every jurisdiction with real time alerts. The Performance Management Agent does continuous OKR aligned tracking, the Learning AI Agent delivers microlearning in 32 languages, the Employee Life Cycle AI Agent covers confirmation to separation, and the Travel and Expense AI Agent standardizes multi country travel policy. Each works on its own, not as a stage of one pipeline. Twelve vertical solutions are the second catalog, "twelve purpose-built vertical solutions, each engineered around the workflows, compliance requirements and outcomes your domain actually runs on." They cover BFSI and microfinance, staffing, logistics, manufacturing, pharma, energy, retail, hospitals, conglomerates, IT services, education and NGOs, each with its own page in the primary navigation and its own rule set per market. The third is content. Nineteen ZingIntel Power BI dashboards live across the modules, and "over 100 standard reports auto-generate from live module data with zero manual compilation." ZingESG adds packaged governance, risk, compliance and ESG reporting frameworks. The 35+ modules on their own are a product line. The eight agents are homepage cards, not pages of their own, so each gets a paragraph, and no page states which agents are licensed separately from the modules they sit on. Sourcezinghr.com homepage agent set, industries navigation and zinghr.com/solutions/zing-intelligence-hubread 2026-09-12 |
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| Triggers & Channel Coverage | Full |
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Work starts from channels, conditions and schedules, all generally available. ZingBot answers HR queries via WhatsApp, Teams or the ZingHR app, as the Intelligence Hub page states twice. WhatsApp matters here because ZingHR sells into Indian, Middle Eastern and Southeast Asian enterprises with large deskless and field workforces, where WhatsApp is the channel a frontline employee actually has. Going the other way, Workflow Engine approvals "arrive as push notifications and are actioned in 30 seconds," so the platform reaches the manager instead of waiting to be opened. Conditions start work too. Compliance 24/7 states that "every jurisdiction is monitored without pause," with real time alerts and continuous monitoring, a watcher raising something nobody asked for. In the published ZingBot sequence, step 09 detects a transaction requirement and step 11 triggers smart escalation, so a condition inside a conversation starts a different process. The Engagement Agent's sentiment tracking and the Performance Management Agent's continuous OKR tracking work the same way. Schedules and the employee lifecycle drive the rest. Payroll runs to a cycle across every pay structure, location and currency, with "every cycle closed on time." The Employee Life Cycle Agent hangs actions off dated milestones "from confirmation to separation," and Zing Learn auto assigns learning paths to every role and career path. Naukri and LinkedIn integration is on the product roadmap, per an FAQ on the support portal. No full trigger catalog is published, and whether a customer can define its own event conditions outside the Workflow Engine is not stated. Sourcezinghr.com/solutions/zing-intelligence-hub with the homepage agent setread 2026-09-12 |
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| Model Flexibility & Routing | Not documented |
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No one outside ZingHR chooses the model. There is no model picker, admin setting, model assignment per agent, routing policy per module or bring your own key path, including on the Zing Intelligence Hub page, ZingHR's own AI product page. ZingHR names no model provider at all, whether OpenAI, Anthropic, Azure OpenAI or an open weight model. The closest statement is a contrast about grounding, "Generic AI assistants answer HR questions with generic HR policy. ZingBot answers with your actual policy," which says nothing about which model generates the answer. So there is clearly no way to pick a model, and the stack underneath is undisclosed. ZingHR runs on Microsoft Azure per its compliance article, but a cloud host is not a model. No MCP server is documented either, and neither routing across more than one model on ZingHR's side nor a customer or admin control is described. Sourcezinghr.com/solutions/zing-intelligence-hubread 2026-09-12 |
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| APIs / SDKs / MCP Extensibility | Full |
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An API reference sits on ZingHR's support site. The SyncSwipeData documentation describes an "API for pushing swipe details from client to ZingHR system," with a production endpoint at portal.zinghr.com/2015/route/Integration/SyncSwipeData, a separate UAT endpoint at clientuat.zinghr.com on the same path, POST as the method, token based authentication where each request carries a token that identifies it, and a typed request schema with mandatory fields, data types and lengths. Data flows in and writes, since the client posts into ZingHR and attendance changes as a result. A second article covers the wider surface in both directions. The integrations FAQ defines customer Push APIs as "when a customer wants to push their data into the ZingHR platform" and Pull APIs as "when a customer wants to pull data from the ZingHR platform for use by their ERP systems," and states that "currently Employee-Basic, Master, Leaves, Attendance and Exit pull APIs are available." That is five named read APIs plus documented write. The same article records the APIs in production use, with Xero globally through both routes, SAP SuccessFactors through ZingHR Pull APIs against SAP's exposed APIs for recruitment, and Oracle PeopleSoft attendance through ZingHR Push APIs. No SDK, OpenAPI or Postman specification, developer portal or self serve key issuance is documented. The reference lives in a support knowledge base, not on a developer site. Coverage is five Pull APIs plus specific Push attributes, not the whole data model, and further Push APIs "can be made available based on customer needs." What is documented is complete enough for a customer's engineer to call. No MCP server is documented anywhere. WhatsApp and Teams are channels, and the prebuilt connectors are ZingHR calling out, not outside systems calling in. Sourcesupport.zinghr.com swipe-push-api and integrations articlesread 2026-09-12 |
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| Testing, Debugging & Optimization | Not documented |
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Nothing puts a change to the agent under test. There is no sandbox for agent behavior, dry run, holdout, A/B comparison, versioning of agent or workflow configuration, evaluator, scored verdict on what ZingBot answered, or regression surface. A customer can reconfigure a Workflow Engine flow or a rubric and it governs the next transaction, but nothing tries that change against known cases first, and no readable result compares before with after. The Swipe Push API reference has a UAT endpoint at clientuat.zinghr.com alongside production. That is a test venue for the customer's own integration payload. Nothing promotes, blocks or verifies anything between UAT and production, and it does not check whether ZingBot's answers were right. ZingHelp SLA compliance is tracked as a KPI. It is a live operational metric for the helpdesk's ticket performance, not for the quality of the agent's output, so a ticket a person closes inside SLA looks the same in that metric as one ZingBot resolves. ZingHR claims 60% fewer routine HR queries, an 80% reduction in audit prep time, resolution in under five seconds and a 70% reduction in hiring effort. Those are outcomes the vendor asserts, not tools a customer runs. Sourcezinghr.com/solutions/zing-intelligence-hub with support.zinghr.com swipe-push-apiread 2026-09-12 |
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| Browser / Computer-use | Not documented |
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Nothing in or out of ZingHR runs through a screen. Everything moves through protocols or conversation. Outbound work goes through prebuilt connectors to SAP, Oracle, Dynamics 365, Zoom, Teams and host to host banking, inbound work comes through documented Push and Pull APIs, and the Workflow Engine's "external API orchestration" reaches other systems by API instead of driving them. No hosted or local browser, desktop session, remote or local computer control, RPA, recorder, virtual machine or screen scraping fallback is described. ZingLens OCR "extracts GSTIN, amount, date, and claim type from photographed bills and pre-fills the form," which is document ingestion. Attendance capture runs on swipe data the customer's own hardware posts to ZingHR through the SyncSwipeData API, so even physical input arrives as a JSON payload, not through anything the agent operates. ZingHR sells a unified database and native connectors, positioning itself against suites that need middleware for integrations. Sourcezinghr.com/solutions/zing-intelligence-hub, the homepage and support.zinghr.com integration articlesread 2026-09-12 |
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The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Pricing
Contact only. ZingHR publishes no pricing page: there is no pricing entry in the primary navigation or the footer, and every conversion path on the current site is a demo request. A sales helpline and a general inquiry address are published instead. No figure, unit, tier or minimum appears anywhere on ZingHR's sites.
Carried from the July build and NOT confirmed first-party: per module and per employee across the HCM suite, on an enterprise contract. Nothing on the estate states the unit. What is confirmed is the shape around it — a subscription with recurring terms that renew automatically, cancellable on 15 days' notice before term end, with service level upgradeable or downgradeable during the term and no refund in either case.
Included quota
Not retrieved; scoped by contract.
Cost watchouts
Model usage for the AI agents and add on modules can increase cost beyond base licensing.
Variable cost rationale
Lowered from medium, because the July rationale asserted a cost that nothing publishes. It read that AI ASSISTANT USAGE ADDS MODEL COST ON TOP OF LICENSING; no page describes a usage, credit, query or token component anywhere, and ZingBot and Zingo are presented as capabilities inside the Zing Intelligence Hub rather than as metered services. Inventing a pass-through is the same defect as inventing a capability. What is actually documented points low: the cancellation policy describes a subscription that RENEWS AUTOMATICALLY AT THE END OF EACH TERM with the ability to UPGRADE OR DOWNGRADE LEVEL OF OUR SERVICES AT ANY TIME, which is term licensing with a deliberate scope dial and no runaway axis. THE CAVEAT IS REAL AND IS THE REASON THIS IS NOT AT THE FLOOR OF THE BAND. Headcount is the presumed axis, and ZingHR sells hard into staffing and facility management, gig and contractual labor, and field force — verticals where headcount is genuinely volatile rather than budgeted, and where a seasonal ramp is the business model. A per-employee license is low exposure for a manufacturer and something else for a staffing firm. Scored 0.3 rather than lower on that basis, and noting that the billing axis itself is unconfirmed, so this reads on the absence of metering rather than on a known unit.
Overage / add-ons
Scoped by contract; module and headcount expansions are negotiated.
Sales call required
Yes, required for paid access
Free / trial
No public free tier or self serve trial documented.
Lowest paid plan
Not retrieved.
Key ambiguities
The only published commercial terms sit on an older version of the website. zinghr.com/cancellation-policy is linked from the current site's footer but is served by the previous WordPress build, last modified 26 April 2024, with different product vocabulary: HR Ground Zero rather than HR Launchpad, six verticals rather than twelve industries, and Robotic Interview, ZingID Blockchain and Face Recognition in a Future Ready menu that no longer exists. A buyer clicking Cancellation Policy lands on terms written against products ZingHR no longer sells. The terms may still govern, but nothing confirms they were reviewed against the current offering. What those terms state: cancellation needs at least 15 days' notice before the end of the term; the subscription renews automatically each term; service level can be upgraded or downgraded at any time with no refund; and no refund is given for an unused remainder of a term, even where a plan is canceled mid month. Customer data is deleted from ZingHR servers within 90 days of cancellation. The mid month wording sits oddly against an enterprise sales motion and may mean the policy was written for an earlier product aimed at smaller customers. Billing does not run under the ZingHR brand. Cancellation notice goes to billing@cnergyis.com, naming Cnergyis as the billing entity behind the product.
Missing data
Every figure. No price, unit, tier, minimum seat count, currency or contract length is published anywhere on ZingHR's sites, and there is no pricing page to reach. Specifically unknown: whether licensing is per employee, per module, per employee per module, or a flat platform fee; whether the eight named AI agents and the Zing Intelligence Hub are licensed separately from the modules they sit on or bundled with them; whether any usage or credit component attaches to ZingBot queries or Zingo transactions; minimum contract term and minimum headcount; whether pricing differs across the India, MEA and SEA regional entities, which are sold as separate regional sites; and the price of the H2H banking and ERP connectors, which typically carry implementation cost in this category. The per module, per headcount basis on this card dates from July and is not confirmed.
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Alternatives to ZingHR
The closest documented capability profiles to ZingHR among enterprise operations agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Rillet9.0 / 14Matches ZingHR across all 14 documented capabilities
- Tabs8.5 / 14A lighter documented profile than ZingHR
- Workable8.5 / 14A lighter documented profile than ZingHR
- Zip9.5 / 14Adds documented Model Flexibility & Routing
- Alloy.ai8.0 / 14A lighter documented profile than ZingHR
- Celonis9.0 / 14Adds documented Testing, Debugging & Optimization
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded