// Case Studies

Problems we were actually asked to solve

Each of these started as a business problem rather than a technology request. Client names are withheld where we do not have publication consent — the architecture and the outcomes are described exactly as delivered.

01Manufacturing

Supply chain analytics for a manufacturing group

The problem

Plant, procurement and logistics data lived in separate SAP and non-SAP systems, so a single view of supply risk took days of manual consolidation.

Why it was difficult

Reporting could not be paused during the rebuild, and the existing BW models carried a decade of business logic that had to be preserved exactly.

What we built

A federated SAP Datasphere layer over S/4HANA and BW, with a governed semantic model and SAP Analytics Cloud dashboards for plant and category leadership.

SAP DatasphereSAP Analytics CloudBW BridgeSAP BTP

Days → hours

Supply risk reporting cycle

1

Governed semantic layer

0

Reporting downtime at cutover

02HR & Workforce

Workforce platform for multi-site operations

The problem

Attendance, leave and performance ran on spreadsheets across multiple sites, and payroll inputs were reconciled by hand every month.

Why it was difficult

Each site had grown its own local process, so the platform had to absorb genuine variation without forking into separate products.

What we built

MyWorkara deployed as a multi-tenant platform with site-level configuration, self-service for employees, and a reconciled payroll export.

Next.jsPostgreSQLReact NativeAWS

Monthly → continuous

Payroll input reconciliation

Self-service

Leave and attendance

Multi-site

Single platform, local config

03Consumer Technology

Multilingual AI assistant for a consumer platform

The problem

Support and onboarding questions arrived in several Indian languages, and an English-only help centre left most of them unanswered.

Why it was difficult

Response quality had to hold up across languages on a cost base that a consumer product could actually absorb.

What we built

A retrieval-grounded assistant built on the 3i engine, with per-language evaluation sets and a human escalation path for low-confidence answers.

RAGVector searchFastAPIAWS

Multilingual

Coverage across Indian languages

Grounded

Answers cited to source content

Escalation

Human in the loop by design

Want to talk to a reference?

For serious enterprise conversations we can arrange a reference call with a client in a comparable situation, subject to their agreement.