Workforce Management Redesigned for AI
Learns from every forecast, every schedule, every operational cycle.
Cisne is an AI-native workforce management platform for BPOs and enterprise contact centers. Intelligence is not bolted on. It is built into how the platform forecasts, schedules, and adapts in real time.
THE PROBLEM WITH LEGACY WFM PLATFORMS
Forecasting models that don't inform scheduling
Scheduling tools that can't adapt when conditions change
Intraday monitoring that reacts after problems appear
Most workforce management platforms were built for a simpler era. AI was layered on later, added to individual features instead of embedded in the architecture. The result is a platform that forecasts in one place, schedules in another, and reacts in a third, with no shared intelligence connecting them.
AI features added on top of rules-based engines
AI is the architecture. Not the add-on.
Cisne is built with AI embedded at the core of how it forecasts, schedules, and adapts in real time. Every decision is informed by models that learn continuously from your operation, not static rules configured at implementation.
Adaptive Forecasting
Models that learn from historical patterns, seasonal trends, and operational context. Improve with every planning cycle, not fixed at implementation.
Dynamic Scheduling
Balances operational requirements, workforce constraints, and compliance rules. Optimized continuously, not configured once.
Intraday Orchestration
Detects emerging deviations and surfaces actions before service levels are impacted, not after.
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BPO organizations managing multiple clients, programs, and contractual SLAs simultaneously
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Enterprise contact centers with large, distributed, and cross-skilled workforce teams
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Operations leaders who need real-time visibility across channels, queues, and locations
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WFM teams accountable for forecast accuracy, schedule adherence, and intraday performance
Built for Contact Centers That Demand More
Designed for environments where standard tools fall short
THE WORKFORCE PLANNING LIFECYCLE
One continuous workflow from forecast to performance
Each stage informs the next. The platform learns from every cycle.
AI-NATIVE ARCHITECTURE
Eight coordinated AI agents. One shared intelligence layer. Operating continuously across every stage of workforce management.
Legacy WFM tools treat AI as a feature. Cisne treats it as infrastructure. Forecasting, scheduling, intraday management, and reporting are powered by coordinated AI agents that share the same operational context, so a change in one area informs decisions across the system.
Shared operational context
All agents operate on the same live data layer. No disconnected models or isolated modules.
Cross-lifecycle coordination
Insights from forecasting flow into scheduling. Intraday deviations inform future forecasts. Learns continuously.
Continuous operation
Agents run continuously, not on demand. Surface insights and coordinate across every stage.
CORE CAPABILITIES
Every capability you need. AI embedded across all of them.
AI is not a feature layer in Cisne. It is the architecture beneath every capability. Forecasting, scheduling, and intraday management are AI-native. Analytics, integrations, and automation share the same intelligence layer.
Forecasting
Models learn continuously from your data. Improve with every planning cycle.
Scheduling
Build staffing plans that balance service requirements, workforce constraints, and cost.
Intraday Command Center
Detect emerging gaps and surface actions before service levels are at risk.
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Autonomous Operations
Seven coordinated AI agents handle routine monitoring, report generation, and data validation continuously across the platform.
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Analytics and Reporting
Unified visibility across forecast accuracy, adherence, service levels, and workforce efficiency.
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Integrations
MCP-based connectivity with contact center platforms, ACD systems, CRM tools, and HR systems — standardized, not one-off.
Built for where contact centers are going. Not where they’ve been.
The workforce management category has been shaped by platforms built over a decade ago. Designed for simpler, single-channel environments with AI layered on later. That architecture limits forecasting flexibility, scheduling optimization, and real-time responsiveness.
LEGACY WFM PLATFORMS
AI added on top of rules-based engines
Forecasting and scheduling built on static rule sets, with AI layered in later. Creates gaps between what AI recommends and what the system can execute.
CISNE
AI as the core planning and decision engine
Forecasting, scheduling, and real-time operations built on AI from the ground up. No rules-based engines underneath. Intelligence is the architecture, improving continuously as it learns from your data.