UUFlexExecutive Cockpit

Tech Overview

The architecture under the cockpit — how data flows from many disconnected business, plant and overseas-entity systems into one governed truth, how that truth becomes a decision, and how two 360s still deliver over real data gaps.

UFlex Limited · FY26 (Mar'26, audited consolidated anchor)
India's largest multinational flexible-packaging & solutions company
12,000 employees · 14 plants & units · 9 plant countries
Under the hood

One governed brain over
many disconnected systems.

No big-bang migration. The platform federates each business, plant and overseas-entity system, resolves it to one ontology, and serves a single trusted number — then turns that number into a decision, and the decision into an owner's action.

10/12
Sources fresh
19,058
Records governed
6/10
Lines at actuals grain
90%
Revenue at plant grain
Technical architecture

The governed stack — eight tiers, federated not centralized

Each business, plant and overseas-entity system stays where it is. The platform layers ingestion, master-data resolution, a shared ontology and a semantic layer on top, then serves one governed truth to the apps and AI. Data flows top → bottom.

Sources
12 systems of record
SAP S/4 · entity ledgersPlant MES · film-line historiansAsepto plant systems (Sanand)Order desk / CRMHRMS · payrollBSE/NSE filings · newsCommodity feeds (resin · crude)
Ingestion
adapters · lineage · SLA
Source adaptersCDC & batch loadsFreshness / SLA monitorLineage capture
Store
raw → curated
Raw landing zoneCurated storeVersioned snapshots
MDM · Resolution
many codes → one node
Entity resolutionGolden recordsSurvivorship rulesDedup · term-conflict
Ontology
the knowledge graph
T-Box · 10 classesA-Box · instancesTyped predicatesPlant = keystone
Semantic
defined once, federated
Metric definitionsGrain tagsFederation engineAllocation + confidence
Serving
governed access
Governed metrics APIQuery layerReconciliation tests
Consumption
apps + intelligence
360 views · Next.jsExec briefs · deterministicAzure OpenAIAgentsweb-grounding
Data flow

How one record travels — source to served truth

A single transaction's journey through the stack. A confidence flag and a reconciliation tie-out ride along with it the whole way.

1
Extract

Adapters pull each business, plant & entity system's events on schedule / CDC.

2
Land

Raw records stored verbatim, with lineage + timestamp.

🧩
3
Resolve

Codes matched to one canonical entity.

🧬
4
Model

Mapped onto the ontology — classes & relationships.

📐
5
Define

Native fields → governed metrics; estimates flagged.

🔌
6
Serve

One metrics API; reconciliation gates the numbers.

🔭
7
Consume

360 views, exec briefs & AI read one truth.

🏷 A confidence flag (Actuals / Allocated / Region-only) and a reconciliation tie-out travel with every value — so a number is never shown without knowing how bankable it is.
From data to action · the decision flow

How one number becomes a decision

The governed truth doesn't sit in a warehouse — it routes itself to the right view, the right action, and the right owner.

The agentic layer

An agent on every value pillar

The four value-creation pillars don't just have dashboards — each has a standing agent that reads its governed data products and recommends the next move. Same ground truth, automated.

📦Value-Added & Specialty Mix
Watches

value-added mix (33%→40%), specialty share of films (28%→35%) & the margin path to 15%

Grounds on
business_unit · service_line · signal · kpi
Acts in Value-Added & Specialty Mix
🧃Aseptic (Asepto) Scale-Up
Watches

packs sold (7.97 bn vs 12 bn capacity), the Egypt greenfield critical path & account wins vs Tetra Pak / SIG

Grounds on
ops_metric · ma_target · project · goal
Acts in Aseptic (Asepto) Scale-Up
♻️Circularity & Recycling Leadership
Watches

recycled volume (30,000→100,000 MT), the Noida rPET ramp & EPR recycled-content mandates

Grounds on
goal · signal · project · brand
Acts in Circularity & Recycling Leadership
⚖️Deleverage Through the Cycle
Watches

net debt/EBITDA (4.35× vs the 5.5× ceiling), DSO 92→75, capex moderation & covenant headroom

Grounds on
kpi · ar_aging · debt_tranche · covenant_qtr
Acts in Deleverage Through the Cycle
The hard part

Two 360s that work before the data is clean

Some overseas entities and new plants aren't fully on the common SAP grain yet, so the line→plant mapping and plant-grain detail are incomplete (Russia/CIS and Nigeria feed manual FX workpapers; Dharwad is under construction). These views still answer — by resolving, allocating-and-flagging, then reconciling. The estimate is labelled, never hidden.

🗂Org Roll-up 360
Open →
The gap
4 of 10lines not yet at actuals grain

Some entities report at their own grain — so the line → plant → business → legal-entity rollup is partly missing or inferred, and consolidation still crosses manual FX-translation workpapers.

How the platform bridges it
1
Resolve. AI maps each entity / plant / leader code to one canonical org node.
2
Allocate + flag. Where an entity isn't mapped, revenue is disaggregated from its geography on learned drivers — and marked an estimate.
3
Reconcile. Allocated parts must foot back to the consolidated total; breaks are surfaced, not hidden.
~90%grain coverage

of revenue already at true plant grain; the rest labelled & closing as entities cut over

📍Plants & Network 360
Open →
The gap
4 sitesallocated or region-only

For entities not yet on the common grain, line-asset, value-added-revenue and revenue detail isn't available at plant grain — so the plant twin would otherwise be blank.

How the platform bridges it
1
Estimate. Plant figures are modelled to ~91% coverage from geography totals and line-telemetry signals.
2
Flag confidence. Every estimated plant carries an Actuals / Allocated / Region-only badge and a coverage %.
3
Flip to actuals. As each entity cuts over to the common ledger, its plant grain rises and estimates become ledger actuals.
~91%grain coverage

avg plant-grain coverage today — transparent where it's modelled

The harness catches the gaps
13 of 14 governed identities tie out to the cent

Reconciliation runs live on the data. The 1 known break below is the plant-grain gap surfaced on purpose — exactly what a CFO or auditor wants flagged, not buried.

Open Data Health →
⚠ flagged
Value-added = Σ site value-added
13
tie to the cent