Wipro’s ambition to lead in AI-powered consulting and digital transformation is constrained by data fragmentation across global operations, business units, and client delivery systems.
SCIKIQ enables Wipro to unify, contextualize, and activate its enterprise data—turning silos into AI-ready assets, powering business 360s, and operationalizing agentic AI at scale. The result: faster client impact, lower integration cost, and a step-change in data-driven service delivery.
Captured from 28 sources across strategy, leadership, lines of business, competition, geographies, capabilities and recent signals — and used to ground everything below.
The maturity curve runs from visibility, to explanation, to natural-language reasoning, to action — and each step depends on the one before it.
Wipro’s global delivery, client, and asset data are unified into a real-time business 360—making it possible to instantly detect service disruptions, SLA breaches, or asset failures across geographies and business units.
Unified visibilityA dynamic knowledge graph models relationships between clients, assets, vendors, and incidents—enabling root-cause analysis and impact tracing across the organization.
Root-cause clarityA GenAI-powered Copilot lets business and delivery leaders ask complex questions in plain English—grounded in real operational data, not just dashboards.
Conversational insightAutonomous agents trigger remediation workflows—such as re-routing delivery, escalating vendor tickets, or notifying clients—reducing response times and revenue at risk.
Autonomous actionBuilt bottom-up, because trust compounds upward: agents are only as safe as the copilot's grounding, the copilot only as reliable as the graph, the graph only as complete as the 360° model beneath it.
Unify client, delivery, asset, and operational data across Wipro’s global footprint for real-time visibility and anomaly detection.
Model relationships across clients, assets, vendors, and events—enabling root-cause analysis and impact assessment.
Conversational AI interface lets leaders and delivery teams ask questions and get answers, grounded in unified data.
Deploy autonomous agents to trigger remediation, escalation, or optimization actions directly from insights.
Data remains in existing systems; SCIKIQ integrates business concepts across Wipro’s SAP, Oracle, CRM, and delivery platforms to create a unified, AI-ready data fabric.
200+ pre-built connectors integrate structured and unstructured data from Wipro's global systems, with no heavy IT lift.
Business rules and metadata engines harmonize client, asset, SLA, and incident data across BUs and geographies.
Entities and relationships are resolved and modeled for 360-degree views—enabling cross-system lineage and impact analysis.
Automated lineage, quality, and compliance controls ensure trustworthy, auditable data for AI and business activation.
Unified view of clients, contracts, SLAs, and service history across all BUs and geographies.
Real-time status and history of critical assets—cloud nodes, delivery platforms, infrastructure.
All incidents, root causes, and remediation actions linked to affected clients, assets, and SLAs.
Performance, escalation history, and compliance of all key vendors.
Continuous mapping of data flows and incidents to regulatory and client compliance obligations.
SCIKIQ delivers 85% faster data integration and 90% lower IT integration cost, with 200+ connectors and no-code orchestration—eliminating multi-year, high-risk internal builds.
Unlike dashboards or point BI tools, SCIKIQ unifies, contextualizes, and activates data—enabling reasoning, root-cause analysis, and autonomous action, not just reporting.
SCIKIQ’s AI-first, business-contextualized fabric creates actionable 360s and knowledge graphs—enabling agentic AI and monetizable data products, not just storage.
GenAI Copilot is grounded in real, governed enterprise data—not hallucinations—delivering explainable, compliant answers and triggering real-world workflows.
When the four layers are in place, leadership sees a single live view — every number traceable to its source, every alert to its root cause.
Entities and their typed relationships as one connected, physics-driven graph. Drag nodes, scroll to zoom, click to inspect — or trace the live scenario from root cause to business outcome.
GenAI Copilot provides plain-language answers, grounded in real operational data and graph context. Language models supply the fluency; the graph supplies the truth.
Every agent draws on the same graph and semantic layer — then closes the loop with a real transaction in the source system.
“Can we trust it?” — answered by design, not by promise.
Every leader sees themselves — each use case builds on a business 360 and the four pillars it needs: 1 Enterprise 360 · 2 Knowledge Graph · 3 AI Copilot · 4 Agent Factory.
Finance leaders get real-time visibility into revenue at risk from SLA breaches, with root-cause paths and forecasted impact across business units.
Ops managers monitor asset health, detect incidents instantly, and trigger automated remediation—reducing downtime and manual effort.
Risk teams receive automated alerts and audit trails for data exposure, regulatory breaches, and vendor risks—mapped to GDPR, RBI, and client contracts.
Delivery leads are proactively alerted to client-impacting incidents, with automated communication and recovery workflows—improving client trust.
BU leaders access unified dashboards, ask plain-language questions, and trace incident impact across clients, assets, and vendors.
Built once, the context layer becomes shared infrastructure — so each new AI initiative starts from enterprise context, not a blank integration backlog.
We would prove the context layer in three focused sprints — earning the right to scale with evidence, not slideware.
Connect core systems and build initial business 360s for one priority business unit.
Layer contextual relationships and enable plain-language Q&A for business leaders.
Deploy autonomous agents to automate incident response, compliance, and client comms.
Wipro achieves unified, actionable data fabric—enabling AI-driven operations, faster client impact, and lower cost-to-serve.