Tata Steel’s ambition to be the world’s most respected and valuable steel company demands a new level of intelligence: not just collecting data, but activating it for real-time, enterprise-wide impact.
SCIKIQ’s AI-first, no-code data fabric transforms Tata Steel’s global operations by unifying siloed data, modeling relationships, and enabling autonomous action—directly supporting strategic priorities in agility, customer focus, and operational excellence.
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.
Unify production, supply chain, quality, and commercial data across Tata Steel’s Indian and European operations for a single, real-time view of plant health, order fulfillment, and customer impact.
Unified ViewModel the relationships between assets, vendors, customers, and events to trace root causes—such as a blast furnace outage cascading into missed deliveries and revenue loss.
Root CauseLet plant managers and executives ask natural-language questions—like 'Which asset failures most impact our top customers?'—and get actionable, explainable answers.
Conversational InsightDeploy autonomous agents to re-route orders, trigger preventive maintenance, or notify customers—closing the loop from insight to action, at scale.
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.
Real-time, unified data fabric spanning production, quality, supply chain, and commercial systems.
Contextual graph models link assets, events, vendors, and customers for transparent root-cause analysis.
Conversational analytics and GenAI Studio—grounded in Tata Steel’s data, not generic LLMs.
Autonomous agents execute corrective actions—order re-routing, maintenance, customer comms.
Enterprise 360 is the foundation every layer above reuses. We don't integrate systems — we integrate business concepts. Tata Steel's data stays where it is; SCIKIQ connects, contextualizes and resolves it into trusted entity 360s.
200+ no-code connectors pull from every source — no rip-and-replace, no data movement.
The metadata & contextualization engine maps each field to a shared business glossary.
Entity resolution stitches records across systems into one record per real-world entity.
Lineage, quality & access control attach to every entity — so the 360 is trusted.
One trusted profile per customer — across every channel and system.
Every asset with its live health, history and failure risk.
Orders, service levels and capacity in one operational view.
Every supplier with SLA, spend and delivery risk.
Revenue, cost and exposure traceable to their operational drivers.
SCIKIQ delivers 85% faster integration and 90% lower IT cost versus custom builds—no-code, proven at global scale, and ready for Tata Steel’s complex, multi-system environment.
Goes beyond dashboards: SCIKIQ unifies data, models relationships, and enables autonomous action—closing the loop from insight to execution, not just reporting.
Purpose-built for contextualization and activation—knowledge graphs, GenAI, and agentic automation, not just storage or ETL pipelines.
Grounded in Tata Steel’s real data, with explainability, lineage, and compliance—no hallucinations, no black boxes.
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.
Conversational, explainable answers for plant managers and executives—grounded in Tata Steel’s real data. 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.
Unified asset and event data enables predictive maintenance, rapid incident response, and reduced unplanned downtime.
Track order status, reroute shipments, and respond to disruptions—minimizing revenue loss and customer impact.
Monitor SLA risks, automate customer notifications, and quantify revenue at risk from operational incidents.
Trace incidents to root cause, automate compliance reporting, and reduce audit effort by 70%.
Accelerate analytics delivery by 30-50%, with explainable, auditable insights for leadership and the board.
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.
Rapid integration of core systems at Jamshedpur and Kalinganagar plants.
Build knowledge graph, control tower, and root-cause tracing for top incidents.
Launch AI Copilot and deploy first autonomous agents.
Unified, contextualized data and autonomous action across Tata Steel’s core operations—delivering measurable business impact in under 4 months.