Construction planning, blueprints, tenders, site coordination, materials, maintenance and reporting — structured, predictive and with clear early-warning signals.
Use case 01
Project status, deadlines, materials, costs, safety and compliance — condensed in one interface, always up to date.
The AI construction dashboard condenses operational and strategic KPIs from project steering, sites, materials, costs and quality assurance into one interface. Delays, cost deviations and early-warning indicators are surfaced automatically — without manual reporting work.
Management, construction leadership and foremen see at any time where projects and sites stand — and can intervene exactly where needed.
How it works
We connect construction management, project, tendering and time tracking systems and other data sources — securely, locally and without data leaving your company.
KPIs, reports and early-warning rules are tailored to your construction types, trades and reporting obligations.
We support and optimise continuously — the dashboard grows with your processes and requirements.
Use case 02
A direct contact point for construction leadership, foremen, costing and administration — based on your own plans, contracts and construction files.
The AI assistant answers concrete questions about construction plans, bills of quantities, contracts, standards or construction progress — context-aware and traceable, based on your internal documents and files.
Construction leadership, costing, foremen and administration save time on research, inquiries and preparing meetings, reports and analyses. Complex questions are answered in natural language — with references to the underlying sources.
Use case 03
Plans, bills of quantities, standards, construction files and experience — accessible through a single question.
The knowledge management platform provides an intelligent, central access point to all construction-relevant documents: plans, bills of quantities, contracts, standards, site reports, internal instructions and experience from past projects.
Research times drop to minutes, new employees are productive faster, and senior know-how is preserved when people leave. Knowledge becomes a shared tool for all construction and administrative teams.
Use case 04
Ten areas where AI agents relieve construction planning, tendering, site coordination, materials and maintenance and accelerate processes.
Automatically analyses project status, supports schedule planning, resource management and progress analyses and detects potential delays at an early stage.
Construction projects can be managed more transparently and efficiently.
Processes plans and documents via OCR, classifies content automatically and supports the analysis of technical documents.
Relevant information can be found and processed faster.
Automatically compares bills of quantities, supports costing and analyses tender documents for deviations or missing content.
This significantly reduces manual review and processing effort.
Supports deployment planning, scheduling and continuous status monitoring of sites and teams.
Bottlenecks, schedule deviations or resource problems can be detected at an early stage.
Automatically analyses operations and service data, identifies potential failures early and supports technician dispatch.
Maintenance can be carried out more predictively and efficiently.
Continuously analyses sensor data, detects anomalies in energy consumption and supports the optimisation of technical equipment.
Consumption deviations or potential faults can be detected at an early stage.
Automatically analyses image and process data and supports inspections and safety checks through pattern recognition and compliance monitoring.
Risks or quality deviations can be identified faster.
Analyses consumption and project data, produces demand forecasts and supports ordering processes and delivery monitoring automatically.
Material shortages or delays can be detected earlier.
Automatically creates daily site reports, minutes and structured reports based on existing project and site data.
Documentation processes can be handled significantly more efficiently.
Analyses faults, prioritises tickets and supports the optimisation of technical operations through continuous data analysis.
Recurring problems and inefficient processes can be detected faster.