QBench is a cloud-based Laboratory Information Management System (LIMS) designed to help laboratories manage samples, workflows, data, inventory, reporting, quality processes, and client interactions in one platform.
Labs use QBench to manage laboratory operations from order placement and sample processing through results and automated reporting. The platform is highly configurable, allowing laboratories to build workflows, define custom data fields, and automate processes around the way their lab already operates.
QBench also helps laboratories reduce manual work by connecting instruments, software, and other systems through file parsers and a robust API. These integrations can automate data transfer between systems, reducing repetitive data entry and the risk of transcription errors. Labs can connect QBench to business intelligence tools, including Tableau, Power BI, Domo, and Looker, via REST API.
Key QBench capabilities include:
Sample and workflow management
Configurable laboratory workflows and custom data fields
Workflow automation
Instrument and system integrations
File parsing and API connectivity
Inventory management
Client portal access
Automated reporting
Analytics and operational insights
Business intelligence integrations with Tableau, Power BI, Domo, and Looker via REST API
Integrated Quality Management System (QMS) capabilities
Unlike LIMS platforms that require extensive custom development to accommodate laboratory processes, QBench is designed to be configurable and adaptable as workflows change. Laboratories can modify processes, fields, and automations without relying heavily on custom code.
QBench is cloud-based, giving laboratory teams secure access to their LIMS while bringing laboratory data, workflows, automation, quality management, and reporting together within a centralized platform.
QBench also supports customers with a team that includes former bench scientists who understand laboratory workflows and can provide guidance throughout implementation and ongoing use.
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AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets.
AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes.
Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering.
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Antares BI Migration
Antares is a BI migration tool for enterprise BI and analytics teams. It connects to a source BI environment, analyzes it automatically, and converts dashboards to the target platform, including deployment.
The Analyzer is free and fully deterministic: it inventories the environment, surfaces migration risk and effort per dashboard, and helps teams scope the work, so unused and orphaned dashboards are excluded before anyone pays to move them. The Converter then automates the rebuild, using predefined mapping tables for visual types, aggregations and calculations so results are consistent run to run rather than improvised. AI is used only for semantically complex cases, always inside deterministic validation.
Available today: Tableau to Power BI, including deployment to Microsoft Fabric, and Tableau to Databricks AI/BI.
Pricing is a flat $200 per migrated dashboard, with no per-user licensing and no time limits. LLM costs are separate, typically under $20 per dashboard.
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