We combine established data technologies with software built in-house to connect your systems, organize your data and turn it into reports and answers your team can use.
We choose the components around the task, your data and your existing systems.
A conceptual view, not a fixed implementation. Not every project requires every component.
Here is how the software we use contributes to a practical analytical solution.
We use ClickHouse for analytical workloads: exploring events, transactions and business activity in a database designed for analysis.
We use CHops to monitor and manage ClickHouse: check database health, investigate queries and keep track of performance.
Trino lets us query data across supported systems using SQL. We use it where analysis needs to reach beyond a single database.
Iceberg gives analytical datasets a table format with snapshots and schema evolution. We use it when the project calls for a flexible data-lake foundation.
We work with Hive for SQL-based analysis over distributed data, including existing Hive-based environments that need to fit into a wider analytical setup.
Our own ETL software collects source data, applies the agreed transformations and prepares datasets for analysis. The workflow is shaped around your systems and reporting needs.
Our own visualization software presents business metrics through charts and reporting views, organized around the questions your team needs to answer.
We develop our own AI analytical agent to help explore business data through questions in plain language. Its sources and analytical tasks are defined as part of the project.
Third-party technologies and software developed by BI Forge are labeled separately.
Technology choices follow the workload, the sources and the way your team needs to use the result.
Clarify the decision, the data sources and the current bottleneck.
Agree on the required components, integrations and scope.
Connect the workflow and check the result with your team.
Alongside our client work, we develop products in other directions. Explore these separately from the technology stack above.
A metadata catalog being developed to help teams discover and understand data assets.
In developmentAsk about MetaForge ↗A vector database being developed for similarity search in AI applications.
In developmentAsk about Vexta ↗A browser-based tool for annotating and editing PDF documents.
Free browser toolExplore PDF Playground ↗AI-assisted research and probability analysis for prediction markets.
Research toolExplore FairPoly ↗Some products are still in development. Check the linked product sites for current details and access terms.
No. We select components for the workload, your current systems and the project scope. This page describes our toolkit, not a mandatory bundle.
CHops, the ETL software, the data visualizer and the AI analytical agent are developed by BI Forge. ClickHouse, Trino, Apache Iceberg and Apache Hive are third-party open-source projects. Our other products are listed in the lower section.
The first step is to review your sources, access and constraints. We then discuss what can stay, what needs connecting and where changes are useful.
The main section explains software we use in delivering analytical solutions. Project scope determines how our in-house software is used. Standalone tools and our products in other areas have their own links or inquiry options.
Tell us about your sources, reporting needs or a task you would like to simplify. We’ll discuss a suitable technical approach.
Prefer email? info@biforge.solutions ↗