Adani Green Energy’s leadership in India’s renewable energy transition is built on scale, speed, and reliability. But as capacity surges past 20 GW, data fragmentation and operational complexity threaten margin, cash, and compliance.
SCIKIQ unifies asset, operations, and commercial data into an AI-ready fabric—enabling real-time control, root-cause insight, and autonomous action to maximize uptime, optimize yield, and protect margin across your fast-growing portfolio.
Captured from 26 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.
Consolidate real-time operational, asset, and commercial data across 20+ GW of solar, wind, and hybrid plants—eliminating blind spots, reducing integration effort by 85%, and surfacing issues before they hit output or margin.
Operational EfficiencyModel causal links between asset performance, weather, grid events, and PPA compliance—enabling root-cause analysis of output dips, yield loss, or regulatory breaches across the portfolio.
Compliance & RiskAsk ‘Why did Plant X underperform this week?’ and get a plain-language, audit-traceable answer—grounded in asset data, weather, and grid events. 90% faster to insight, 5x faster time-to-action.
Competitive AdvantageAutonomously trigger maintenance, rebalance portfolios, or alert grid operators—protecting ₹22 Cr EBITDA per 100 MW by reducing downtime and compliance risk.
ProfitabilityTrace the impact of asset outages on PPA billing, receivables, and working capital—closing the loop from field to finance and reducing DSO by up to 15 days.
Cash & Working CapitalBuilt 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 asset, operations, and commercial data across all plants, projects, and contracts—surfacing issues, trends, and anomalies portfolio-wide.
Model relationships between assets, weather, grid, contracts, and compliance—enabling root-cause tracing and impact analysis.
Conversational, grounded answers to business and operational questions—explaining complex events in context.
Autonomous agents to trigger maintenance, rebalance portfolios, or alert grid operators—closing the loop from insight to action.
Data stays in place—SCIKIQ connects, contextualizes, and models business concepts across SCADA, SAP, CRM, and partner systems, not just databases.
200+ prebuilt connectors unify SCADA, SAP, CRM, and partner data in weeks, not months.
Map and harmonize asset, event, contract, and compliance concepts across systems.
Deduplicate, link, and model relationships—building Asset 360, Customer 360, and Incident 360.
Enforce lineage, quality, and access controls for audit and compliance.
Complete view of each plant, turbine, and inverter—status, events, maintenance, and output.
Unified profile of every off-taker (NTPC, SECI, GUVNL)—contracts, billing, escalations, and DSO.
Trace every downtime, root-cause, response, and financial/compliance impact.
Link output, penalties, receivables, and cash flow for every plant and contract.
Monitor all regulatory events, penalties, and closure status.
SCIKIQ delivers a unified, AI-ready data fabric in <6 months—at 60% lower TCO and 90% less IT effort than custom builds. Proven in complex, multi-plant, multi-system environments like Adani Green’s.
SCIKIQ contextualizes data across SCADA, SAP, CRM, and partners—beyond dashboards. It enables root-cause, impact, and closed-loop action, not just reporting.
Purpose-built for asset-heavy, regulated industries—SCIKIQ models business concepts (plants, incidents, PPAs, compliance), not just tables. Knowledge Graph and Agent Factory deliver explainability and autonomous ops.
SCIKIQ grounds every answer in real, governed business data with lineage, audit, and compliance—avoiding hallucinations and ensuring trust for board-level decisions.
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.
Ask in plain language and get answers grounded in Adani Green’s real operations, contracts, and compliance 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.
Unify SCADA, maintenance, and vendor data for Asset 360—detect downtime, trace root-cause, and trigger autonomous remediation, protecting output and margin.
Link output, incident, penalty, and billing data for Finance 360—trace receivables delays to root events, automate collections, and free up working capital.
Ask ‘Why did output drop?’ or ‘Which PPAs are at risk?’—get explainable, audit-ready answers grounded in the Knowledge Graph.
Map every compliance event to its root asset, incident, and financial impact—autonomously close events and update audit logs, reducing penalty exposure.
Compare new hybrid/solar/wind projects against benchmarks; surface early risks, optimize ramp, and maximize first-year yield.
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 SCADA, SAP PM, and S/4HANA for two pilot clusters (hybrid + wind); build Asset and Incident 360.
Expand to Customer, Finance, and Compliance 360; deploy Knowledge Graph and AI Copilot for root-cause and plain-language Q&A.
Deploy autonomous agents for incident remediation, yield optimization, receivables acceleration, and compliance closure.
In 90 days, Adani Green moves from siloed reporting to autonomous, AI-driven green energy operations—protecting margin, accelerating cash, and reducing compliance risk.