The Platform
One system. Three layers. Every step of hiring.
Most hiring technology is point solutions: a careers site here, an ATS there, a screening tool bolted on. inploi is different. We built a unified system that connects the candidate experience, the data flowing through your workflow, and the agents doing the work — all governed by a single control plane.
Every layer is built to work together. That is what makes the flywheel possible: agents learn from data, data comes from experience, experience improves as agents improve. No other vendor owns all three.
Layer one
The surface. Where candidates meet your brand.
Think of the Experience layer as the Shopify for hiring. Just as Shopify gives retailers a fully brandable, performance-optimised storefront without rebuilding infrastructure, inploi gives enterprise hiring teams a fully configurable candidate-facing surface — careers sites, application forms, automation workflows — without touching the ATS.
The result is a candidate experience that genuinely reflects your employer brand: fast, accessible, multi-language, multi-location, and live in minutes via Studio. Not weeks of engineering time. Not a compromise between what your TA team wants and what your ATS can deliver.
Explore the Experience layer →Careers Sites
Enterprise-grade, fully brandable. 100% Lighthouse performance. Multi-brand, multi-language, multi-location.
Conversational Forms
Application forms that adapt to candidate answers, intent, and source. Consent and compliance baked in.
Workflows
Trigger-based automation between your experience layer and your ATS. Routing rules, notifications, handoffs.
Layer two
The fuel. Data that no other vendor can see.
inploi sits between the candidate market and your ATS. That position is unique. Your ATS sees what happens after the application. Job boards see what happens before it. inploi sees both — and the space in between.
The Data Nexus reconciles live job data from your ATS, candidate behaviour from the Experience layer, and resolution signals from your agents. That reconciled data is what powers Analytics, what feeds the Talent Agent Engine, and what creates the learning loop that makes agents better over time.
Native ATS connectors — Workday, Oracle Taleo, SAP SuccessFactors, iCIMS, Greenhouse, and eleven others — mean no custom integration work. Jobs sync. Applications submit. Disposition data flows back. All without ATS configuration changes.
Explore the Data layer →Analytics
Command centre for funnel, quality, and spend. Source-to-hire, drop-off, application quality — unified with agent performance.
ATS Connectors
14 native integrations. Jobs sync in. Applications go out. Structured data returns. No ATS changes required.
Data Nexus
The reconciliation layer. Candidate behaviour + ATS state + agent resolutions = signal that no other vendor has.
Layer three
The intelligence. Agents that own the work.
The Talent Agent Engine is the processing layer that turns data into action. Every agent interaction runs through a six-step loop — not a scripted chatbot, not a rule-based workflow. A genuine reasoning system purpose-built for hiring.
01
Intent classification
Understanding what the candidate actually wants — not just what they typed.
02
Context loading
Pulling live job data, knowledge base content, and candidate history into the reasoning context.
03
Orchestration
Determining which agent capability to invoke: answer, match, screen, schedule, escalate.
04
Generation under constraint
Producing responses within brand guidelines, compliance rules, and quality thresholds.
05
Validation
Checking outputs before delivery. No hallucinations about jobs that do not exist.
06
Learning loop
Resolution data feeds back into agent improvement. Agents get better the more they work.
The control plane
Studio. One interface for everything.
Studio is the control plane that sits across all three layers. It is where Talent Engineers configure agents, manage knowledge bases, run evaluation panels, inspect agent performance, manage user access, and deploy A/B tests — all without writing a line of code.
The ability to test and evaluate agents before they go live is what makes Studio different from every other AI hiring tool. You can see exactly what your agent will say to a candidate before a single real candidate sees it. That level of observability is what enterprise TA teams require.
See Studio in full →Agent configuration and knowledge base management
Evaluation and testing panel — preview before publish
Analytics dashboard — funnel, quality, agent performance
User access management and permissions
A/B testing for agent responses and careers site content
Publish to live instantly — no deployment pipeline
The flywheel
Each layer makes the others more effective.
This is not three separate products bundled together. It is one system with a reinforcing loop. Better candidate experience generates more data. More data makes agents smarter. Smarter agents improve the candidate experience. The loop compounds over time.
Interactive architecture diagram — Phase 5
Market position
AI-native on top of an existing engagement layer.
inploi does not replace your ATS. It sits above it — giving you a world-class candidate experience and an AI agent workforce without a re-platforming project. Challenger architecture. Incumbent distribution. You get the innovation without the disruption.
Above the ATS
Careers sites, application forms, agent conversations. Everything the candidate sees — inploi owns it.
Connected to the ATS
Live job sync, application submission, disposition writeback. 14 native integrations. No ATS config changes.
Invisible to the ATS
Candidate intent signals, agent conversation data, resolution analytics. Captured by inploi. Unavailable anywhere else.
Defensibility
The four things that compound over time.
01
Data capture
A decade of candidate behaviour data across 50+ enterprise hiring organisations. Every interaction makes the model more accurate. This dataset cannot be replicated by a new entrant.
02
Agentic orchestration
The Talent Agent Engine is purpose-built for hiring workflows, not adapted from a general-purpose AI framework. The intent classification, context loading, and validation layers are specific to recruiting.
03
Domain-specific tuning
Agents trained on hiring-specific context: job descriptions, compliance requirements, candidate communication patterns, ATS schemas. Not a general language model pointed at recruiting.
04
Observability
Studio's evaluation panel lets TA teams test, inspect, and iterate on agent behaviour before it goes live. No other AI hiring vendor offers this level of control and transparency.
Talk to us about what your hiring looks like in 18 months.
We will show you the platform on a hiring setup like yours. No generic demo. Takes 30 minutes.