Inventh business intelligence services connect data from ERP, CRM, ecommerce and finance systems into one governed platform, then deliver Power BI and Microsoft Fabric reporting leadership can trust. Advanced analytics adds forecasting and machine learning to predict what is likely to happen next.
Data, analytics and AI
Advanced Analytics and Business Intelligence Services
Our approach
Dashboards are easy. Trusted numbers are the hard part.
Most analytics programs stall because the data underneath is inconsistent, definitions differ between teams and nobody owns quality. We fix the foundations first, then build the reporting, forecasting and AI that depend on them.
One version of the truth
Shared metric definitions and a governed semantic model, so finance, sales and operations report the same number for the same question.
Decisions, not decoration
Every dashboard starts from a decision someone needs to make, and shows only what helps them make it.
Built for AI from day one
Clean, well modeled and well documented data is what AI assistants, data agents and forecasting models need to give reliable answers.
Where we create value
Analytics that answers real business questions
We start from the question each function needs answered, then design the data, models and reports to answer it.
Finance
Consolidated P&L, cash flow, budget versus actual and margin analysis across entities and currencies.
Faster month end reporting and earlier warning on cash and margin.
Sales and marketing
Pipeline, revenue, customer lifetime value and campaign attribution across CRM, web analytics and ads.
Spend moved to the channels and customers that actually produce revenue.
Supply chain and inventory
Stock levels, turns, supplier performance and demand forecasts by product, location and channel.
Fewer stock outs and less excess stock tying up cash.
Operations
Throughput, cycle times, service levels and quality metrics updated through the day, not once a month.
Bottlenecks found while there is still time to act.
Customers and service
Retention, churn risk, satisfaction and cost to serve by segment, product and region.
At risk customers identified before they leave.
Executive leadership
A small set of trusted KPIs with drill down to the detail, on desktop and mobile.
Board and leadership meetings spent on decisions, not reconciling numbers.
What we deliver
Our analytics and business intelligence services
From a data strategy to a fully managed analytics platform, delivered individually or as one program.
Data Strategy and Assessment
A review of your data sources, quality, tools and skills, with a target architecture and prioritized roadmap.
Data Engineering and Pipelines
Reliable pipelines that bring ERP, CRM, ecommerce, finance and operational data together, automatically and on schedule.
Data Warehouses and Lakehouses
Modern data platforms on Microsoft Fabric, Azure, AWS or Google Cloud, designed for scale, security and cost control.
Business Intelligence and Dashboards
Power BI and Looker Studio reports and semantic models that give every team trusted, self service insight.
Predictive and Advanced Analytics
Forecasting, segmentation, anomaly detection and what if models that look ahead, not just back.
Data Governance and Quality
Ownership, definitions, quality rules, access controls and lineage that keep data trustworthy as it grows.
Analytics and AI
From reporting what happened to predicting what happens next
Our analytics and AI teams work together, so your data platform powers both the dashboards leaders read today and the AI that will answer their questions tomorrow.
Ask your data in plain language
Copilot and data agents that answer business questions from your governed semantic models, with the numbers traceable to their source.
Forecasting
Demand, revenue, cash and capacity forecasts built on your history and refreshed automatically.
Anomaly detection
Automatic alerts when sales, costs, quality or fraud indicators move outside their normal range.
Customer and product intelligence
Churn prediction, segmentation, recommendations and price analysis built on your transaction data.
Data maturity
From spreadsheets to AI ready data
Organizations that succeed with AI almost always have strong reporting foundations first. Our roadmap builds each stage on the one before, delivering value at every step.
Foundation
Key data sources connected into one governed platform, with owners and definitions agreed.
Trusted reporting
Semantic models and dashboards that replace manual spreadsheets for the metrics that matter most.
Advanced analytics
Forecasting, segmentation and anomaly detection embedded in the reports teams already use.
AI and automation
Assistants, data agents and automated decisions built on data that has proven reliable.
Data handled under role based access, encryption and audit logging, with privacy obligations such as GDPR and the EU Data Act considered where they apply.
See our AI and machine learning servicesDecision ready outputs
What your leadership team receives
Every assessment and program produces documents your executives, finance and IT teams can use to decide and govern.
Data source assessment
Every source system mapped, with data quality, ownership and gaps identified.
KPI and metric dictionary
Agreed definitions for the numbers that run the business, with owners.
Target data architecture
How data should flow from source systems to reports and AI, and the path to get there.
Business case
Costs, benefits and payback for the analytics program, with assumptions stated plainly.
Prioritized roadmap
Phased initiatives, from quick win reports to advanced analytics and AI.
Governance model
Roles, quality rules, access policies and the process for changing definitions.
Future proof by design
Platform and regulatory changes we plan around
Analytics platforms and data rules are changing quickly. These are the developments shaping the programs we deliver.
Reviewed September 2026
April 30, 2025
Copilot on every paid Fabric capacity
Microsoft made Copilot, Fabric data agents and AI functions available on paid Fabric capacities from F2 upward, removing the earlier F64 minimum.
Since January 1, 2025
Power BI Premium moves to Fabric
Power BI Premium per capacity SKUs left the purchase flow in July 2024, and customers without an Enterprise Agreement had to move to Fabric F SKUs at renewal from January 1, 2025.
September 12, 2025
The EU Data Act applies
New EU rules on access to data from connected products and on switching between cloud and data processing providers became applicable.
July 1, 2024
Universal Analytics is gone
Google Analytics 4 is now the only version of Google Analytics. Historical Universal Analytics data is no longer available, so trend reporting must be rebuilt on GA4 and exported data.
December 2025
An open standard for data agents
The Model Context Protocol joined the Linux Foundation's Agentic AI Foundation, a common way for AI agents to connect to data sources and business systems.
Every year
Licensing and platform changes
BI and cloud vendors change licensing, capacities and features every year. Our support plans track these so costs and capabilities stay under control.
BI, analytics and AI
How the three disciplines differ
| Criteria | Business intelligence | Advanced analytics | AI and machine learning |
|---|---|---|---|
| Question it answers | What happened and why? | What is likely to happen? | What should we do, and can it be automated? |
| Typical outputs | Dashboards, reports, KPI scorecards | Forecasts, segments, anomaly alerts | Predictions, recommendations, assistants and agents |
| Data it needs | Clean, modeled historical data | Longer, consistent history | Large, well governed datasets and feedback |
| Who uses it | Every manager and team | Analysts and planners | Applications, workflows and end users |
How we work
From assessment to insight people use
Assess
Sources, quality, tools and reporting needs mapped with your stakeholders, ending in a prioritized roadmap.
Model
Data architecture, pipelines and a governed semantic model with agreed metric definitions.
Visualize and predict
Dashboards, forecasts and alerts built with the people who will use them, released in short cycles.
Adopt and improve
Training, usage monitoring and regular reviews so reports stay relevant and trusted.
Data governance
How we keep data trustworthy
Clear ownership
Every key dataset and metric has a named business owner responsible for its definition and quality.
Quality checks
Automated tests on freshness, completeness and accuracy, with alerts before bad data reaches a report.
Secure by design
Role based and row level security, encryption and audit logs, so people see only the data they should.
Change control
Definitions and models are versioned and changed through an agreed process, not quietly in a spreadsheet.
Technology
Platforms and tools we work with
Proven, well supported platforms chosen to fit your existing systems, skills and budget.
BI and visualization
Data platforms
Data engineering
Analytics sources
How we operate
Principles behind every analytics program
Numbers you can defend
Every metric reconciles to its source systems, and every calculation is documented.
Privacy respected
Personal data is minimized, protected and used only for agreed purposes.
Cost aware
Platforms sized and monitored so capacity and licensing costs match actual use.
You own everything
Data, models, reports and documentation belong to your organization, in your own cloud tenancy.
Connected capabilities
One partner from data to decisions
AI and Machine Learning
Generative AI, AI agents, machine learning and predictive models.
ExploreEnterprise Application Development
ERP and CRM integration, workflow automation and modernization.
ExploreCustom Software Development
Applications built around how your business actually runs.
ExploreSEO and Digital Marketing
Search, AI visibility and marketing analytics tied to revenue.
ExploreWeb Development
Portals and web applications that put insight in front of customers.
ExploreDedicated Development Teams
Data engineers and analysts who extend your team.
ExploreEngagement models
Ways to work with us
Data and analytics assessment
A fixed scope review of your data, tools and reporting, with a target architecture and roadmap.
Analytics program
Data platform, semantic models, dashboards and advanced analytics delivered in phases against agreed goals.
Managed analytics
Ongoing pipeline monitoring, report changes, new analysis and platform administration each month.
FAQ
Frequently asked questions
What is the difference between business intelligence and advanced analytics?
Business intelligence reports what happened and why, through dashboards and KPIs. Advanced analytics uses statistical and machine learning methods to forecast what is likely to happen and recommend what to do next.
Which BI tools do you work with?
We work mainly with Microsoft Power BI and Microsoft Fabric, as well as Looker Studio and Excel, and choose tools that fit your existing systems, skills and licensing.
Can you connect data from our ERP, CRM and ecommerce systems?
Yes. We build automated pipelines from ERP, CRM, ecommerce, finance, marketing and operational systems into one governed data platform.
How long does it take to get our first dashboards?
Priority dashboards on a first set of connected sources typically take several weeks. Broader data platforms and advanced analytics are delivered in phases.
How do you make sure the numbers are right?
We agree metric definitions with the business owners, reconcile every report to its source systems and run automated data quality checks before data reaches a dashboard.
Is our data ready for AI?
Often not yet. AI needs clean, well modeled and governed data. Our assessment shows what is ready now, what needs work and which AI use cases your data can support.
Can people ask questions of our data in plain language?
Yes. With a well built semantic model, tools such as Copilot in Power BI and Fabric data agents can answer business questions in plain language, traceable to the underlying data.
Do you provide consulting before implementation?
Yes. Many clients start with a data and analytics assessment that ends in a target architecture, business case and roadmap, whether or not we deliver the build.
How do you keep data secure?
Data stays in your own cloud tenancy with role based and row level security, encryption, audit logging and access limited to the people who need it.
Start with a clear view of your data
Book a data and analytics assessment. We will map your sources, reporting and AI opportunities, and come back with a prioritized roadmap and business case your leadership team can act on.