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Services · Data Integration & Governance

The data foundation every AI workload depends on.

Enterprise data integration with native lineage, metadata catalogues, master data management, and policy-as-code. The unsexy work that makes the AI demo become an audited production workload.

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40+
Enterprise data programmes shipped
100%
Critical data flows under audited lineage
12×
Analyst productivity uplift on automated pipelines
What we do

Capabilities under one accountable team.

01

Data integration & pipelines

Batch, streaming, and CDC patterns on Confluent, Kafka, Airflow, dbt, Fivetran, Informatica IDMC. Schema contracts, idempotent jobs, replayability.

02

Catalogues, lineage & quality

Column-level lineage, business glossary, data contracts, freshness SLOs, anomaly detection — Collibra, Alation, Atlan, Unity Catalog, or open-source.

03

Master data & reference data

MDM hubs (Reltio, Informatica MDM, Profisee), reference data services, golden-record stewardship — for the entities your business actually argues about.

04

Governance & policy-as-code

Policy-as-code on data access (Immuta, Privacera, Unity Catalog), row/column-level security, GDPR / PDPL / DPDP-ready right-to-be-forgotten flows.

What to expect

Outcomes you can hold us to — by horizon.

0–90 days

Foundations

Outcome tree, baseline metrics, and a working pilot in production by day 90 — defensible with finance, signed off by risk.

3–12 months

Scale

Squad expansion across the next 2–3 value pools. Live-parallel cutovers. Capability uplift inside the client team.

12+ months

Run & optimise

Managed run with named SLOs, quarterly value reviews, and a continuous-improvement budget reserved for innovation, not toil.

How we deliver

Five steps. One accountable team.

Audit

2 weeks

Map current pipelines, identify trust gaps, baseline pipeline reliability and cost.

Foundation

6–8 weeks

Catalogue, lineage, contracts, governance guardrails — opinionated but extensible.

Pilot domain

6 weeks

One business domain end-to-end (e.g. customer or claims) on the new foundation with measurable KPI.

Scale

Q2 onward

Roll out by domain on quarterly cadence; track ROI per domain.

Sustain

Continuous

Data contracts as a programme, not a project. Quarterly trust reviews.

Anchor case study

Tier-1 GCC bank stands up an audited data fabric in 9 months — feeds 4 AI use-cases under regulator review.

Banking · GCC
Problem
14 data lakes, no lineage, AI pilots blocked by data-quality reviews, regulator demanding lineage evidence.
Solution
Lakehouse fabric on Databricks + Unity Catalog, Confluent for streaming, dbt for transformations, Collibra for business glossary, Immuta for policy-as-code.
Impact
Lineage to source-of-record on 100% of regulator-relevant flows · 4 AI use-cases passed model-risk review first time · Analyst productivity 12× on automated pipelines.
Field-tested in data integration & governance

More programmes we have shipped.

All case studies →
BFS
AI underwriting
9 days → 14 min
Banking & Financial Services · GCC · UAE

GCC sovereign bank deploys AI underwriting in 11 months

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Banking
Loan origination
14d → 3h
Banking & Financial Services · India

National bank ships modern Loan Origination System on Mendix in 11 months

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Banking
Open banking
240+ TPPs
Banking & Financial Services · East Africa

Leading African bank ships open-banking rails across 7 markets

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How we engage

Three commercial models. One outcome standard.

We avoid open-ended retainers. Every model names its outcome and its measurement window in the contract.

01 · Diagnose

Fixed-price diagnostic

2–4 week engagement. Outcome tree, baseline metrics, prioritised value pools, and a board-ready 18-month roadmap. Stop-go decision in week 4.

From USD 80k · 2–4 weeks
02 · Pilot

Outcome-linked pilot

8–12 week engagement to ship one value pool, end-to-end, with a measurable KPI commitment. Joint squads with the client team. Live-parallel before cutover.

Outcome-linked + capped fee · 8–12 weeks
03 · Scale & run

Programme + managed run

Multi-quarter scale-out with managed services on top. Quarterly value reviews. SLO-tied annual incentive. Capability transfer by design.

T&M + outcome incentive · Multi-quarter
FAQ

Frequently asked questions

Build or buy on the catalogue? +

We deliver Collibra, Alation, Atlan, and Unity Catalog. Choice depends on integration footprint and budget — we share the comparison matrix.

Do you support open-source? +

Yes — OpenLineage, OpenMetadata, Apache Atlas, Marquez, dbt — when they fit the target operating model.

Can you handle streaming and batch? +

Both. Confluent / Kafka, Flink, Kinesis, Pub/Sub for streaming; Airflow, dbt, Fivetran, Informatica for batch. CDC for hybrid.

How does this connect to AI workloads? +

Directly. Your retrieval layer, feature store, and decisioning service all read from this fabric — with citations, lineage, and right-to-be-forgotten honoured at the index.

GDPR / PDPL / DPDP compliance? +

Policy-as-code on access, row/column-level security, data-classification automation, audited deletion flows. Audit packs delivered at every release.

Pricing? +

Per-domain build engagements; managed-service rates for sustained run. We avoid open-ended retainers; outcome-based pricing for sustained programmes.

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