Data Semantics teams design, build and run the data platforms, analytics and AI agents behind intelligent enterprises, on the ERP, CRM and data platform you already have. AI does the groundwork. Our engineers govern and refine it.
For CIOs, CDOs, CFOs and operations leaders.
Data Semantics is a data, analytics and AI services firm. We modernize data platforms and migrate ERP, CRM and core banking data with AI, model it into an ontology so AI understands your business, build analytics and decision intelligence on top, design AI agents that act within guardrails, and integrate the results back into SAP, Oracle, Microsoft Dynamics 365, Salesforce and other systems. Then we run what we build, as managed services.
AI can now build a report in minutes. What it can't do on its own is understand what your data means, decide what matters and act safely in your systems. That's where most data and AI investments stall, and where leaders are asking:
What we’re best at
Most firms own one layer. We cover all four stages, plus running them, so data, decisions and action connect. Start with any service. Each one builds on the same foundation.
Modernize, migrate and govern your data, and model what it means, so it's ready for analytics and AI agents.
Moves legacy data warehouses and platforms to Microsoft Fabric, Databricks or Snowflake, with AI-assisted code conversion and proof that the numbers match.
Moves data between ERP, CRM, core banking and industry platforms, with AI-assisted mapping, coding and reconciliation, and owners approving every rule.
Builds and runs the pipelines that bring data from every source into one governed platform, on time and tested.
Sets the rules for who can use which data and how good it has to be, then checks them continuously.
Models what your data means and how it connects, so every report and every AI agent works from the same definitions.
Show people what needs attention, predict what's likely to go wrong and recommend what to do next.
Designs the reports, dashboards and semantic models leaders use every day, on one governed set of numbers.
Puts AI agents on the decisions that matter most: they spot the issue, decide within your rules, act in your systems and measure the outcome.
Lets people ask questions of policies, contracts and documents and get answers with their sources.
Put AI agents to work on exception-heavy processes, within guardrails, with people in control.
Designs and builds AI agents that investigate, decide and act within set guardrails, with a person in the loop where it matters.
Automates the approvals, forms and handoffs that still run on email and spreadsheets.
Runs AI inside your own environment, including on-premises, for organizations that can't send data to a public cloud.
Land every decision and action back in the systems your business runs on. No manual re-entry.
Connects your systems so data and actions flow both ways, including writing results back into the ERP and CRM.
Rebuilds or extends business applications so they fit how your teams work now.
We run what we build, and keep improving it after go-live.
Keeps platforms, pipelines and reports running, monitored and improving, under agreed service levels.
Monitors, tunes and governs live AI agents for accuracy, cost, guardrails and audit.
AI agents use analytics to monitor outcomes, spot patterns and improve the next decision.
On every project, AI drafts requirements, code, models and tests in hours, so our engineers spend their time on the business logic, the edge cases and the quality checks that decide whether a project succeeds. On data projects, mapping, code generation and data quality checks run in DataPrep 360.
Business needs turned into requirements, process maps, user stories and acceptance criteria.
You get: a reviewed requirements pack
Checked by: consultants and your product owner
Ingestion pipelines, transformations and data workflows generated from approved mappings.
You get: pipelines in your repository
Checked by: engineers review every line
Runs in DataPrep 360Dimensional and medallion models, DDL and documentation proposed.
You get: a documented model
Checked by: architects approve
Runs in DataPrep 360Semantic models, measures and report pages drafted.
You get: a first release in days
Checked by: BI consultants
App components, workflow logic, APIs and interfaces drafted.
You get: less boilerplate
Checked by: developers review all code
Quality, reconciliation and migration assurance checks generated and run.
You get: evidence for sign-off
Checked by: QA engineers and your owners
Runs in DataPrep 360Figures from client deployments across industries. Your own baseline and targets are set together in the first assessment.
improvement in system performance
18+ sources → 600+ reportsAP processing effort per 1,000 invoices
10M+ invoices processedcollectors needed after automating the collections workflow
One connected workflowcontact-center traffic
100,000 conversations a monthEvidence, not promises. Every engagement starts by measuring today's baseline, so improvement is proven in your own numbers.
We work on the data platform you've already chosen and connect the business systems around it.
The most common sources and targets across our clients.
Microsoft Solutions Partner for Data & AI and Digital & App Innovation. Beyond Microsoft, Data Semantics delivers on Databricks, Snowflake, AWS and Fivetran, and recommends what fits your estate rather than one vendor.
Five fixed-scope ways to start, each designed to measure a baseline and agree a first step.
We review your data platform, quality, ownership and definitions against what AI agents need, and show what blocks them and what to fix first. For platform moves it runs as the Data Platform Assessment.
Book an assessmentWe map the decisions that matter most in one function, how they're made today and what better signals would change, ending in a decision blueprint.
Plan a workshopWe profile one source system, surface the hidden business rules and show where your ERP, CRM or core banking migration really stands before cutover.
See application data migrationWe score your processes for volume, exceptions and rules, design the guardrails for the best candidate and put one agent live on real cases.
See agentic AI solutionsFor BI estates, data platforms and live AI agents: what is fragile, slow, unused, inaccurate or costing too much, and a plan to fix it.
See managed servicesPick the problem costing you most and measure today's baseline.
Deliver a bounded first release on real data, with the team that will use it.
Add sources, decisions and workflows on the same foundation.
We operate, monitor and improve it as a managed service.
Data Semantics offers data, analytics and AI services in five groups: data foundation (platform modernization, AI-powered application data migration, data engineering, governance and ontology), analytics and decision intelligence, agentic AI and automation, integration and app engineering, and managed services for data, BI and AI agents.
Both. Our teams deliver services, and our products, Serina for accounts payable, Zebo for enquiry to cash, DataPrep 360 for data migration and InsideOps for decision intelligence, make that work faster and repeatable. You can engage us for services alone, products alone, or both together.
Agent-ready data is data that an AI agent can safely act on: clean, governed and modelled with an ontology, so the agent knows what each record means, how it connects to others and which rules apply. Most data platforms are built for dashboards, not for agents.
AI drafts requirements, generates pipelines, proposes data models, scaffolds reports and apps, and runs validation rules. Our engineers review, govern and refine every output, with DevSecOps, automated testing and release controls built in.
No. Data Semantics is a Microsoft Solutions Partner for Data & AI and Digital & App Innovation, and also delivers on Databricks, Snowflake, AWS and Fivetran. We build on the platform you have already chosen.
SAP, Oracle Fusion and EBS, Microsoft Dynamics 365 and AX, Salesforce, NetSuite, JD Edwards, Temenos and industry systems such as Yardi and Opera, among many others.
Yes. Many engagements run alongside an in-house team or a systems integrator. We can take a defined scope, such as migration assurance, analytics or AI agents, without duplicating work already in progress.
Yes. We have run managed data and BI services for clients for years, and we now also run AI agent operations: monitoring accuracy, cost and guardrails for agents in production.
With a fixed-scope assessment of one problem, such as AI and data readiness, a decision discovery workshop or a migration readiness check. It measures today's baseline, so any improvement is proven in your own numbers.
Our solutions run on Microsoft Azure and can be deployed in your own tenant and preferred region. For regulated industries, private and on-premises AI deployments are available on engagement.
A migration at risk, numbers nobody trusts, or an AI pilot that never reached production. We'll show you the first step, on your own data.
