Clean, standardise, reconcile
Cleaning, standardisation, normalisation, enrichment, transformation, mapping, validation and reconciliation across every connected source.
Your data is scattered across SAP, cloud apps, legacy systems and spreadsheets — and every team walks into the room with a different number. SCIKIQ Data Hub unifies them into one governed layer without moving or replacing a single source system, so analytics and AI run on data everyone can trust — live in 60–90 days.
No complex pipelines. No ripping out existing systems. Just a clean path from your scattered data to reliable intelligence.
Point SCIKIQ at any data source — on-prem databases, cloud warehouses, SaaS tools, APIs, flat files. No-code connectors get you live in minutes, not months.
SCIKIQ maps relationships, enriches metadata and enforces data quality rules automatically. Your data arrives structured, labelled and trustworthy.
Every team — finance, ops, sales, engineering — queries one consistent, governed dataset. Cross-departmental visibility with zero duplication.
Feed GenAI agents, ML models and BI tools with clean, semantically rich data. Your intelligence layer is finally ready for the AI era.

Connect every source, curate it into trusted data and consume it any way your teams work — all on one lakehouse foundation. Explore each module below.
SCIKIQ unifies fragmented data from Excel, business apps, SQL Server, Oracle, Teradata, Db2, Snowflake, SAP and more — into one intelligent, governed layer. Real-time, multi-cloud, multi-vendor. No manual exports, no broken pipelines, no replication.
15 of 187+ connectors shown · connect on-prem and cloud sources without replication — bring compute to your data, not the other way around.

Connecting data is only half the job. The Data Hub curates it too — cleaning, standardising, enriching and reconciling every source, then modelling it logically and semantically so business and technical teams work from the same trusted definitions. ML-driven optimisation and an orchestrator keep curation running in real time.
Cleaning, standardisation, normalisation, enrichment, transformation, mapping, validation and reconciliation across every connected source.
Describe entities, attributes, keys and relationships, then define and edit metadata — models built once in Data Prep Studio and reused everywhere.
ML-driven optimisation for real-time data curation, enabling faster access, proactive crisis management and predictive decision-making.
Automated listing, scheduling and tracking of the tasks, jobs and emails that keep your curated data fresh — with no manual babysitting.

A BI semantics layer separates users from the complexity of the underlying databases, so governed data reaches everyone in the shape they need it — dashboards, APIs, ready-to-use models or packaged data products. Six consumption models, one governed source.
Intuitive, integrated reporting with self-service analytics on top of a BI semantics layer — no database expertise required.
Enterprise APIs for scalable data-as-a-product, with a centralised hub offering full read/write access across the organisation.
Deploy ready-to-use ML models for real-time intelligence, embedded straight into the applications and workflows that need them.
Convert raw data into AI-ready, monetisable products and share them securely across partners for innovation and new revenue.

The Data Hub unifies integration, curation, governance and visualisation in a single lakehouse — with Auto ML and GenAI built in for real-time summaries, profiling and insights from any source. Scalable, cost-effective and flexible enough for data scientists, analysts and researchers alike.

Whether you are closing the books or training ML models, every team queries the same governed data — and finally stops arguing about whose number is right.
Reconcile data across ERP, banking systems and spreadsheets automatically. Close the books faster with a single source of truth your CFO can trust.
Live visibility across procurement, inventory and logistics. Spot bottlenecks before they become problems.
Merge CRM, support, billing and behaviour data into a unified profile — without building a warehouse from scratch.
Full data lineage, access control logs and audit trails across every source system. Audit-ready without separate tooling.
Feed models clean, labelled, semantically enriched data from day one. Eliminate the 80% of ML project time lost to data preparation.
A live, cross-functional view of the business. One governance layer, zero conflicting numbers in the boardroom.
Most data platforms were built before GenAI existed. Every layer here — ingestion, governance, storage, delivery — is designed to feed models what they need: answers from your actual data, not hallucinations.
The old answer to fragmented data is a hand-built pipeline stack or a lift-and-shift onto a single cloud — both take quarters, and both start with ripping something out. The Hub activates the data you already have.
Have a data or AI challenge on your mind?
We would love to think through it with you — no pitch, no form maze.
Data Hub connects, unifies and governs data from SAP, cloud apps, legacy systems, data lakes and warehouses into a single governed intelligence layer.
SCIKIQ ships with 187+ connectors for enterprise integration out of the box.
Data Hub is typically live in 60–90 days.
No. Data Hub unifies and governs data across your existing sources without a rip-and-replace migration.