A reliable data pool
All verified data and documents centrally in Microsoft Azure (OneLake), enriched with external market data.
The solution:
The bracket across all data from all IT applications
kanQ combines technical depth with operational simplicity. Data is extracted from documents and source systems and checked for consistency, standardised, merged and stored centrally. With kanQ this becomes a data basis with a central control system for your entire company:
- All relevant data in one place instead of data silos
- Current, reliable KPIs for portfolio, properties and units
- Better decisions in less time
- Full cost and risk transparency
Your advantage: You steer actively – instead of chasing after things.
In short: complex portfolios become plannable and comparable. And you don't have to change anything in your source systems, because data enrichment is possible directly in the source system. As a result you receive reliable information that you can transfer directly into Power BI or other analysis tools.
kanQ AM · The data platform that maintains quality
All data in one place – verified and ready for analysis.
kanQ AM brings verified data and documents from all source systems together in one place and makes them analysable – in KPI dashboards, in Power BI or by simply asking the LLM. The Quality AI Manager detects and prioritises new deviations in ongoing operations (in development). kanQ forms the bracket across all data from all IT applications.
All raw data on property / tenant
Rent roll
Preparatory DD → red flag
Indexation clauses and index adjustment
Analysis without Excel prep work
KPIs, cockpits and standard reports – flexibly adaptable, seamlessly integrated into your reporting environment.
Quality AI Manager
New deviations are detected and prioritised. The expert decision stays with a human.
Microsoft Azure & Fabric
gif-compliant data model
GDPR-compliant · EU-hosted
150+ API interfaces
All languages via LLM
Integrable step by step
The reality
The reality: manual processes, data breaks, inefficient work …
Limited data analysis
No company-wide dashboards, lots of Excel sheets.
High manual effort
Data maintenance costs time, errors are frequent.
Backward-looking data
No valid basis for forecasts or decisions.
Media breaks in the process
Excel, email, screenshots, different tools.
Inconsistent data sources
No standards, different files, lack of consistency.
Lack of data integrity
No automatic checking or validation.
No central system
Data has to be produced several times, results are unreliable.
Low transparency
Data is not unambiguous and cannot be traced back to its source.
The result is a lack of repeatability, poor comparability and inefficiency.
The ideal…
All real estate data is always up to date and correct?
New information is integrated into the IT system automatically, without manual re-keying?
Evaluations and analyses are done simply by asking a question?
You can see at the push of a button which properties carry the highest potential or risk?
The entire real estate portfolio is intelligently connected: documents, KPIs, analyses and forecasts in real time?
Data maintenance effort becomes a minor issue?
Checking complex portfolio data takes minutes instead of hours?
With kanQ, the entire real estate portfolio becomes intelligently transparent with the help of AI.
Everything. Always. Everywhere.
The ecosystem of kanQ
OpenAI
Predictive Valuation & Market Intelligence
Hyper-Targeted Lead & Opportunity Finder
AI-Powered Portfolio & Asset Management
Precision Valuation & Risk Engine
- AI enrichment of the ecosystem
BI
KPI, Filters, Maps, Drilldowns
CoPilot
Azure Purview
- KPIs
- Analyses
- Cockpits
Data Lake / OneLake
Real Estate Quality AI Manager
- Data aggregation for BI – single source of truth
- De-duplication of data, cleansing and harmonisation
- Import and merging of historically complete source data
- Return of cleansed data to source systems
Documents
API
Excel/CSV
IoT
ESG
- Documents
- Measurement data
- Data import from other systems
Bronze · Silver · Gold – the medallion architecture in Microsoft Fabric / OneLake: from raw data to verified, analysable information.
Extraction – Validation – Analysis – AI solution
Source: documents and all source systems
1. Extraction
Fully automated read-out:
- Documents (lease agreements, etc.)
- Measurement data
- Data import from source systems
AI data quality manager & data lake / OneLake
2. Validation
The data lake is the single source of truth and represents the central, application-independent data pool.
- Data aggregation for BI – single source of truth
- De-duplication of data, cleansing and harmonisation
- Import and merging of historically complete source data
- Return of cleansed data to source systems
Analyse and decide
3. Analysis
- Cockpits
- Dashboards
- KPIs
- Standard reports
- Talk to the documents – LLM
AI-supported ecosystem
4. AI solution
- AI enrichment of the ecosystem
- Agents
- Automated processes (end to end)
- Automated workflow organisation
From practice · anonymised
Example: retail park
From the rent roll to proactive asset management
Starting situation:
Rent rolls from 25 consecutive months.
> 1,000 data fields from 25 months
Available information: property data, tenant data, unit data, indexation data, agreements, …
Objective:
Establishing transparency and clarity.
Making the data and information from the rent rolls available for proactive asset management.
The result: trust in the data
Efficiency & economics
- Less manual effort in data preparation and reporting
- In a few weeks, integrable step by step (without downtime) for any portfolio size, data volume or company size
- No changes to source systems required
- Fast decision cycles thanks to reliable, structured data
- Reduced costs for data management and coordination between departments
- Higher productivity in the asset, property and reporting teams
- Shorter project durations e.g. for ESG or due diligence analyses
Data quality & traceability obligations
- AI-supported verification of all real estate data for completeness, plausibility and consistency
- Rule-based and learning validation mechanisms
- Automatic error detection, duplicate and anomaly checks
- Traceable, audit-proof data history for internal and external audits (audit trail)
- Increased transparency towards investors and supervisory bodies
- One central, verified source – “single source of truth”
Standardisation & compatibility
- Uniform data structure based on the extended gif standard*
- Comparability and interchangeability between systems and portfolios
- Standardised KPI logic for reporting, ESG and financial analyses
- Clear semantic mapping of data to property and contract structures
- Future-proof basis for data integration and automated reporting
Integration & automation
- Direct connection to ERP, property management, energy and service charge systems
- Easy data import via API, Excel/CSV, IoT or documents
- Automatic synchronisation and real-time updating of data
- Seamless integration into Microsoft environments (Power BI, Teams, Excel, Azure)
- Minimal IT implementation thanks to the existing Microsoft architecture
Reporting & analysis
- Power BI connector for usable dashboards
- Uniform KPIs at the push of a button – without manual preparation
- Real-time visualisation of portfolio, financial and ESG data
- Drill-downs to property or contract level
- Automatic updating of dashboards when data changes
Future-proofing & scalability
- Fully Microsoft-based – future-proof and compatible
- Extendable at will for ESG reports, finance, AI analyses, risk and performance models
- Basis for AI-supported process automation, predictive and prescriptive analytics
- Available in all languages
*Gesellschaft für Immobilienwirtschaftliche Forschung e.V. (German Society of Property Research)
Result · anonymised
Initial overview, rent development KPIs, individual rent roll, location and first information.
Questions & answers
Frequently asked questions about kanQ AM
What is kanQ AM?
kanQ AM is a data platform on Microsoft Azure. It brings verified data and documents from all source systems together in one place.
How can I analyse the data?
In KPI dashboards, in Power BI or by asking the AI a simple question in plain language. No spreadsheet preparation is needed.
Does the AI change data on its own?
No. New deviations are detected and prioritised; the professional decision stays with a human.
Where is the data stored?
Exclusively in European data centres on Microsoft Azure (Germany West Central region, Frankfurt). Customer data is not used to train public AI models.