Schaman

Schaman is an AI Resolution Intelligence SaaS platform built for the agentic AI era: while conversational and CX-agent layers manage the dialogue, Schaman owns the resolution. It combines customer signals (Outside-In) with network and OSS data (Inside-Out) to identify the root cause of each issue, often before the customer has articulated it, and executes the fix on whichever channel initiated the contact: chatbot, voice, agent console, or field technician app.

The platform layers on top of the existing stack (CCaaS, CRM, BSS/OSS) with no platform replacement and no 12-month programme: it reaches production in 8-15 weeks. Its integration architecture separates the technical layer (data, connectors) from the business layer (resolution logic), so that when a system changes or migrates, only the technical connector is updated, the care logic remains untouched. Through its no-code graphical configuration interface (CX Designer), business teams, not developers, and not the vendor, configure and govern any aspect of customer care: new scenarios, rules, resolution policies, escalation paths, publishing across all channels in one click.

Schaman deploys three types of specialized AI Smart Agents: TBR Agents (Troubleshooting-Based Resolution) that autonomously diagnose and resolve technical issues, Execution Agents that carry out governed actions on live infrastructure, and Open Target Agents for open-ended queries. The AI Adaptive Agents Controller orchestrates them across use cases and channels, and exposes them natively via MCP and A2A, so Schaman can be delegated to as a peer agent by any orchestrating platform, without exposing its internal logic.

Every unresolved interaction feeds the NFF (No Fault Found) Learning Loop: Schaman turns cases without a conclusive diagnosis into the starting point for discovering new root causes, so the autonomous resolution rate keeps rising on its own, under operator governance, not as an opaque model that improves itself unchecked.

Real-world deployments confirm the results: at Vodafone Spain, a -40% reduction in contact center calls, 76% of interactions resolved in self-care, a 4x improvement in IVR resolution (+380%), and a +20 point improvement in T-NPS. At MasOrange, a -44% reduction in fault ticket ratio per customer and agent onboarding reduced to 5 days across all services.

With Schaman, operators get true resolution autonomy inside their agentic AI ecosystem, with full policy control and no ongoing vendor involvement, reducing costs and accelerating innovation from months to weeks.