Data. Driven. Insight.

Foundational data.
Embedded AI.

The data layer your organisation runs on, and the intelligence built into it.

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Accredited Microsoft Solutions Partner Claude Partner Network

The platform

Where the intelligence actually sits.

Some data arrives clean and goes straight in. Most of it needs a model before it is worth storing at all.

Sources AI processing The data asset AI serving Outcomes

ERP Finance, stock, procurement

Plant & SCADA Process and production

Telemetry & IoT Fleet, sensors, energy

Lab & quality Assay and test results

Documents & email Invoices, contracts, forms

Imagery & video Cameras, drone, inspection

Signal & anomaly Clean, fill, flag drift

Document AI Extract, validate, score

Vision models Detect, classify, measure

DataHub Governed · Azure

AI enrichment Classify, match, reconcile, forecast: written back as derived data

Semantic layer Your terms and KPIs

Data agents Reason and act

Guardrails Access, audit, escalation

Conversational answers Ask in plain language

Automated reporting Live, board to shop floor

Process automation Straight through, logged

Predictions & alerts Before it becomes a problem

Actions written back to the source systems

Raw, as it leaves the source system After a model has processed it Outcomes written back to source

Live capabilities, not roadmap

What the AI actually does.

Explore Dataloop X →

AI-native apps

Concept to working product in weeks.

Document AI

Contracts and invoices in, structured data out.

Process automation

Manual workflows replaced end to end.

AI reporting

Natural language over your data platform.

Agentic workflows

Agents that research, reason and act across systems.

Predictive models

Forecast outcomes, recommend the next action.

Computer vision

PPE compliance, asset and conveyor monitoring.

Embedded AI

Inside ERP, CRM, Power BI and beyond.

AI enablement

Foundational AI, inside your business.

Not a pilot we run for you. A capability your teams own, built layer by layer on the data asset underneath.

04 Your people Teams running agents inside the tools they already use

03 Skills & agents Packaged, versioned capability for each function

02 Context & rules Your terminology, KPIs, thresholds and access control

01 The data asset Integrated, governed, trusted. The part nobody can skip

We stand each layer up with your team, then hand it over.

New in DataHub

Ask your data anything.

Agents query your live warehouse in plain language, grounded in your data, not the internet.

Conversational Live Source-backed

datahub.dataloop.co.za/agent

Which conveyors are overdue for inspection?

Three conveyors are past their inspection interval as of this morning. CV-02 is the most critical at 100 days since last service.

Asset Last svc Days Status

CV-02 31 Jan 100 Critical

CV-07 25 Mar 47 Overdue

CV-10 28 Mar 44 Overdue

Answered from your warehouse · 1.4s

[Illustrative interface, sample data]

Business process automation

Let the routine run itself.

Capture Email, portal or field form

Extract Document AI, per-field confidence

Match Three-way against the PO

04 Live

Post to ERP Straight through, fully logged

The argument

AI in a complex business is a data problem before it is an AI problem. We fix the data problem. Then we build the AI that runs on it.

40+ clients.

Selected work

Not a portfolio. Proof.

Mining

Vision on the conveyor.

Material on the feed was being estimated by eye. Vision models now measure it frame by frame, landing beside every other operational source.

Key result Vision output reports like any other data source. In deployment

Financial services

Month-end, automated.

A group of legal entities consolidated its accounts by hand, days after close. We built the hub straight against the accounting API, with an AI layer on top.

Key result Consolidation automated across every entity. Delivered · in active use

Engineering & construction

The foundation, three years on.

A structural steel and platework contractor built its monthly reporting by hand. We replaced the whole path (integration, ingestion, warehouse, reporting) and still run it.

Key result Three years in continuous production use. Delivered · managed service

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Trusted by industry leaders

Before you ask

Straight answers.

What happens after you build it?

We don't hand over a system and disappear. Dataloop stays on as the managed service provider. The same team that built the integration keeps it running, watches for drift in the data, and extends it as your systems and requirements change.

How fast can we see something working?

Depending on scope, weeks rather than quarters. Delivery follows a set process (baseline, build, review cadence), the same discipline whether it's an integration, a report, or an AI agent. You'll see something real running on your own data early, not a slide deck first.

How do you charge?

There's no published rate card, because the answer depends on the systems involved and what needs to be built. Tell us what's not working and we'll scope it honestly, including telling you if the fix is smaller, or different, than what you came in asking for.

Do we have to replace our existing systems?

No. We build the integration and data layer around the systems you already run (ERP, plant and SCADA systems, accounting platforms) and layer reporting and AI on top. Nothing gets ripped out for the platform to work.

What happens to our data?

It stays on Microsoft Azure, under your own governance model. That's the same platform behind every engagement we run as a Microsoft Solutions Partner.

Does the AI just make things up?

No. Agents answer from your own warehouse, grounded in your data, not the open internet. Every answer traces back to a live source system, the same one your team already trusts for reporting.

See it running on your data.

A short walkthrough, your systems, no slideware.

Book a walkthrough

Foundational data.Embedded AI.