Sprint AI project – Daily Dashboard

Project Goal

Deploy an AI/ML analytics platform for ENEC — under the corporate DAIO 2 (Analytics & AI Program) — that replaces manual, average-based forecasting and reporting with automated, driver-based AI across Finance, Supply Chain, and Outage operations, improving forecast accuracy, cutting manual effort, and accelerating decision-making.

Objectives

Finance

Automate monthly variance analysis and forecasting — replace manual extraction and simple-average forecasting with driver-based AI models and auto-generated variance commentary.

Spare Parts

Forecast demand and optimize inventory / reorder levels via AI/ML integrated with SAP, reducing stockouts and procurement costs.

Post-Outage

Analyze historical outage data to identify root causes and recurring issues, feeding lessons learned into future outage planning across the fleet (C1–C2–C3).

Delivery

Take each use case from UAT through to Production per the Sprint AI roadmap — Finance Go-Live 21 Oct, Outages 5 Oct, Spare Parts 26 Oct.

Foundation

Build reusable data foundations (Databricks / Unity Catalog) as part of ENEC's broader Corporate Analytics & AI Program.

Expected Business Impact

Finance

Variance analysis commentary with forecasting of actuals

AI drafts the monthly budget-vs-actuals commentary and forecasts actuals, so analysts and budget owners go straight to decisions.

4–5FTE

of capacity freed every year

across finance analysts and 67 budget owners

−67%analyst time on monthly variance commentary

−25%forecast rework for budget owners

Plant Maintenance

Spare parts forecasting & inventory optimization

ML forecasts spare-parts demand from maintenance history, failure rates and supplier lead times, and sets optimal reorder levels in SAP.

−7%

spare-parts stock value

less excess safety stock and fewer write-offs

32man-days a year of manual planning work freed

Outages

Post-outage analytics & continuous lessons learned

AI analyses past outages (T-Clock, work orders, deviation logs) to pinpoint root causes and carry lessons learned into the next outage plan.

−10%

planned-outage overrun

6.7 → 6.0 days per outage

−3%unplanned outage days per year

−50%time to produce the post-outage analysis

Expected impact per use case, from the business cases agreed with ENEC business stakeholders and ADQ. Figures are planning assumptions, not contractual KPIs.

ENEC · Data Platform — Technical Delivery

Presight.ai · Reporting Week 15 Oct 2026 · Overall Status At Risk

Delivery Roadmap

Overall progress: —

Completed In Progress At Risk Not Started Milestone

Variance Analysis Commentary with Forecasting of Actuals

Business: Finance

Stakeholders: Salma Al Hameli, Ahmed Al Kendi

At RiskGo-Live 21-Oct

Material and Spare Parts Procurement Forecasting

Business: Supply Chain

Stakeholders: Jalal Hussain, Mona El Tantawy, Meera Hasan Alhosani

At RiskGo-Live 26-Oct

Post-Outage Analytics & Continuous Lessons Learned

Business: Outage

Stakeholders: David Williams, Charles Montana III, Vincent Dietler

At RiskGo-Live 5-Oct

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▼ Team & Org Structure

Resource	Role	Allocation	Experience	Location	Onboarding	Expire Date
Ivan Doronin	Project Manager	25%	10+ yrs	Onsite/Remote (UAE)	Cleared	27.07.27
Tisha Mohammed	Engineering Manager	15%	10+ yrs	Onsite (UAE)	Clearance pending	—
Pratyaksha Raval	Sr. Data Engineer	100%	8–10 yrs	Onsite	Cleared	24.03.27
Abhishek Kumar	Data Engineer	—	—	—	—	—
Chetan Anand	Sr. Data Modeler	100%	8–10 yrs	Onsite	Cleared	02.02.27
Akash Goyal	Data Science Lead	100%	10+ yrs	Onsite	Cleared	02.02.27
Shu Yu	Sr. Data Scientist	100%	7–9 yrs	Onsite/Remote (UAE)	Cleared	30.01.27
Vladislav Sheverda	Sr. QA Engineer	50%	7–9 yrs	Onsite/Remote (UAE)	Cleared	—
Akanksha Shreya	BI Developer	100%	—	—	Clearance pending	—
Maryam AlMazrouei	SRE Engineer	25%	5–7 yrs	Onsite/Remote (UAE)	Cleared	—

6.15 Total FTE

10 Headcount

10 Onsite (UAE)

2 Clearance pending

Roles, Responsibilities & Key Skills

Project Manager

IDIvan Doronin25%

Responsibilities: Engagement leadership, scope, schedule, risk, action log, client communications, sprint cadence, status reporting.

Skills: Agile/Scrum, stakeholder management, JIRA/Confluence, vendor governance, AI/ML delivery.

Engineering Manager

TMTisha Mohammed15%Clearance pending

Responsibilities: Technical delivery oversight across DE/DS/BI/QA workstreams; unblocks engineers, reviews technical approach, coordinates handoffs between team members, enforces code and data-quality standards, escalates technical risks.

Skills: Technical leadership, software/data engineering background, sprint & delivery management, code/design review, cross-team coordination, stakeholder communication.

Data Engineer

PRPratyaksha Raval100%

Responsibilities: Build and operate ingestion, transformation and serving pipelines; data quality, lineage and orchestration.

Skills: Spark, Python, SQL, Airflow, Databricks/Snowflake, dbt, Kafka, CI/CD.

Data Engineer

AKAbhishek Kumar

Responsibilities: Build and operate ingestion and incremental load pipelines; job flow documentation; number matching and validation support.

Skills: Spark, Python, SQL, Databricks, ADF, incremental load design.

Sr. Data Modeler

CAChetan Anand100%

Responsibilities: Conceptual, logical and physical data models; semantic layer; data dictionary and modelling standards.

Skills: Dimensional & Data Vault modelling, ERwin/Erwin, SQL, metadata management, governance.

Data Science Lead

AGAkash Goyal100%

Responsibilities: Lead model design, experimentation, evaluation and deployment; technical mentoring of the DS team.

Skills: Python, scikit-learn, PyTorch/TensorFlow, MLOps, statistics, GenAI/LLM evaluation.

Sr. Data Scientist

SYShu Yu100%

Responsibilities: Feature engineering, model development, validation and deployment; partner with engineering on productionisation.

Skills: Python, SQL, ML/DL frameworks, experiment tracking (MLflow), feature stores.

Sr. QA Engineer

VSVladislav Sheverda50%

Responsibilities: Test strategy, automation, data and model QA; defect triage and release sign-off.

Skills: PyTest, Selenium/Playwright, API testing, data quality frameworks (Great Expectations), CI/CD.

BI Developer

ASAkanksha Shreya100%

Responsibilities: Build dashboards, semantic models and reports; partner with business on KPIs and self-service enablement.

Skills: Power BI / Tableau, DAX, SQL, data modelling, performance tuning.

SRE Engineer

MAMaryam AlMazrouei25%

Responsibilities: Reliability of data & AI services; observability, incident response, infra-as-code and release engineering.

Skills: Kubernetes, Terraform, monitoring stack, Linux, cloud operations, automation scripting.

Source: ENEC × Presight — Project Structure, Sprint AI Program (Team Structure, Roles & Resource Allocation), April 2026.

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