AI data analysis and conversational BI for specialist areas
Can a controller query a plant's costs in their own words and trace the result back to the calculation? A question taken from an already verified report shows how well the answer fits the company's own data and technical terms.
T-NEX Dynamic AI Reporting is aimed at specialist areas that want to develop analyses on a reconciled data source themselves. The entry point is a business question and an existing comparison report. KPIs, data integration and test criteria are defined in the project. T-NEX is the publisher of this register; the profile describes its own offer.
Question for the first report What analysis results when the specialist area asks the same question for a different period?
Assessment: For clearly defined analyses that can be checked against known results.
Suitable tasks
Business questions as a dashboard; budget variances; cost allocations
Data and integration
Database and file sources are provided for in the architecture. The specific integration is checked and set up.
AI functions
Questions in natural language; Create reports / charts
Operating model
Data access, operational responsibility and model connection are defined in the project.
Pricing basis
Clarify project scope and terms in discussion; no public flat-rate price used as a basis.
Check before selecting
Agree data scope, KPI definition, permissible model content and acceptance before use.
ChatAible combines automated analyses with written summaries for decision-makers. The platform prioritises observations from a data set before it prepares the results. For the assessment, a data set with known influencing factors is helpful, so that the specialist team can distinguish genuine relationships from mere anomalies.
Assessment: Specialist and data teams that jointly examine extensive analyses
Suitable tasks
Exploratory analysis; explanations of KPIs
Data and integration
Company data and metadata provided for the analysis
AI functions
Draft comments
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Compare identified influencing factors with business facts known to the team.
Akkio aligns its AI platform with campaign work at media agencies and data providers. The current product description links data queries, modelling and reporting with planning and success measurement. The offer is therefore to be classified in the register as a specialised solution for marketing analytics. Companies should use their own campaign to check which data sources and target variables are supported and how results are assessed in business terms before extending the platform to further reports or planning tasks.
Assessment: Media agencies and companies with data-intensive campaign management.
Suitable tasks
Campaign reporting; marketing analytics; media planning
Data and integration
Own campaign and company data; check the exact connections for the project.
AI functions
Questions in natural language; Create forecasts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which data, model assumptions and outputs can be verified using a known campaign?
The Q assistant in Quick BI translates business requirements into charts and reports. Users can change a visualisation in conversation and relate it to the data set intended for it. For the selection, it is of interest how the visualisation proposed by the model can be checked and adjusted afterwards.
Assessment: Companies with an existing Quick BI environment
Suitable tasks
Dashboard creation; charts via dialogue
Data and integration
Data sets provided in Quick BI
AI functions
Questions in natural language; Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Clarify availability of the functions for language, region and booked plan.
Amazon Quick creates a dashboard draft from a description and selected data sets. Users review the proposed structure and can edit it before it is created. For a management report, this allows the outline to be agreed first, before individual visualisations are worked out.
Assessment: Teams with data sets already prepared in Amazon Quick
Suitable tasks
Dashboard draft; management reports
Data and integration
Data sets available in Amazon Quick
AI functions
Questions in natural language; Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Check with your own data whether the right dimensions, KPIs and periods are chosen.
With Max, AnswerRocket provides a data agent for natural-language queries and recurring analyses. The documentation describes customisable agents, semantically described data sets and an SQL explorer. Developers can modify agents and integrate them into existing workflows via interfaces. For companies with clearly defined analysis tasks, it should therefore be checked which agent configurations already fit and which business definitions or connections still have to be built up jointly.
Assessment: Teams that want to model recurring analysis tasks as customisable data agents.
Suitable tasks
Natural-language data queries; recurring reports; customisable analysis agents
Data and integration
Snowflake, Redshift, BigQuery, Databricks, PostgreSQL and Microsoft Azure according to the documentation.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are data sets, agent permissions and business checks set up in the company's own deployment?
Primary sources · checked on 31.10.2026 Max Overview
Arria describes the automated written preparation of structured financial data, for example for fund performance commentary, market updates or results reports. For the selection, the specialist area should define examples in which a change is arithmetically conspicuous but, without additional context, permits no statement about the economic cause.
Assessment: Financial companies with recurring commentary on structured KPIs
Suitable tasks
Fund commentary; market updates; KPIs prepared in written form
Data and integration
Structured financial data provided for text generation
AI functions
Draft comments
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Clarify approval rules, terminology and evidence for the figures used in the text.
Astrato creates analytics and business applications on an existing data warehouse. Users describe a task, while shared business definitions determine the basis of the figures displayed. The platform combines analyses with further input and write-back functions. For a reporting project, it should therefore be clearly separated which data is read only and where changes are permitted. A first use case can be a sales overview or margin check with known results and clear user permissions.
Assessment: Companies that build analyses and data applications on existing warehouses.
Suitable tasks
Dashboards on the data warehouse; custom data applications; sales and margin analyses
Data and integration
Existing data warehouse via live queries; check specific platform compatibility.
AI functions
Questions in natural language; Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which functions require write permissions and how are these separated from pure reporting?
Better Analyst is the new product name of Formula Bot. The platform links questions about data with charts, dashboards, reports and automated workflows. As sources, the provider names files, spreadsheets as well as several business applications and databases. The offer suits teams that want to build a delimited analysis without a large analytics team of their own. In the comparison, data scope, required connectors and business oversight of generated calculations should be checked with a known task.
Assessment: Individual specialist areas and growing companies with clear analysis tasks.
Suitable tasks
AI data analysis; dashboards from business data; automated reports
Data and integration
Google Sheets, BigQuery, Snowflake, PostgreSQL and Microsoft SQL Server, among others.
AI functions
Questions in natural language; Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which connectors are available and which are only announced as planned?
BlazeSQL creates charts and reports from questions put to a connected SQL database. The provider also provides for regular updates for recurring analyses. A test with two similarly named revenue fields shows whether the chosen definition remains recognisable and whether staff can check the query before passing it on.
Assessment: Specialist areas with SQL data and recurring reporting questions
Suitable tasks
Reports from database questions; weekly analyses
Data and integration
Connected SQL database
AI functions
Questions in natural language; Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Check query scope, business meaning of fields and recurring delivery.
BlazeSQL is an offer from the Luxembourg-based Blaze Analytics vGmbH.
Bricks offers AI-assisted dashboards, reports and spreadsheet work with a visible focus on data from files. The product page shows use cases for sales, finance, HR and operational tasks. The offer is therefore of interest if a team wants to turn existing exports into an understandable analysis. For use in the company, KPIs, recurring updates and permissions should be checked with a company's own example before reports are released to further recipients.
Assessment: Specialist areas with existing files and a need for visual analyses.
Suitable tasks
Dashboards from files; departmental reports; spreadsheet-based analyses
Data and integration
CSV and Excel files according to the product description; check further connectors in the specific offer.
AI functions
Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How can the KPI calculation, file exchange and recurring updates be traced?
camelCode creates data applications and publishable dashboards, among other things, from a description. On the current product page, data analysis is a use case of the coding assistant. A prepared KPI from Postgres, Snowflake or BigQuery is suitable for testing whether the generated application brings together query, presentation and access as desired.
Assessment: Companies that want to create an internal analytics interface from prepared data
Suitable tasks
Dashboard creation; custom data applications
Data and integration
Postgres, Snowflake and BigQuery, among others, according to the application description.
AI functions
Questions in natural language; Create reports / charts
Operating model
Hosted variant as well as documented installation with Docker Compose.
Pricing basis
Free entry level with own model key and paid variants according to the provider.
Check before selecting
Clarify publication route, data access and verifiability of generated analysis steps.
Wren AI is an analytics agent developed by Canner with an open core. Business users ask questions, while central definitions determine the business basis of the queries. The product page also shows the creation of dashboards and use via further AI interfaces. For companies, this is of interest above all where databases or warehouses already exist. Before selecting, it should be settled who maintains KPI models and how permissions and model connections can be implemented in the chosen operating model.
Assessment: Companies with existing databases and a need for jointly defined analytical answers.
Suitable tasks
Natural-language data queries; AI dashboards; analysis via further AI interfaces
Data and integration
Snowflake, BigQuery, Databricks, Redshift, PostgreSQL, SQL Server and MySQL, among others.
AI functions
Questions in natural language; Create reports / charts
Operating model
Cloud offer and open core; check the scope of functions of the variant.
Pricing basis
Price to be clarified in the project
Check before selecting
How do the open core and the cloud offer differ in operation, permissions and support?
AskYourDatabase answers questions about SQL databases and can present results graphically. The offer includes a desktop application for own analyses and an embeddable data chat. The operating documentation separates the local database connection from model requests, in which, depending on the function, information may go to the model provider.
Assessment: Teams with read-only database access or a customer application of their own
Suitable tasks
Business questions on SQL data; embed data chat
Data and integration
SQL databases with access from the desktop or from the integration
AI functions
Questions in natural language; Create reports / charts
Operating model
Desktop application and embeddable data chat according to the product description.
Pricing basis
The desktop and chatbot offers have different pricing models. Compare project needs with the pricing page.
Check before selecting
Examine SQL permissions and the content of model requests separately.
Count brings together analyses and research results on a shared workspace. The current product page shows how an agent processes sources, creates charts and reports and flags statements for review. The offer is of particular interest for tasks in which figures are discussed together with other information. For regularly recurring company reporting, the test should clarify how data is updated, calculations are traced and jointly edited results are published in a binding manner.
Assessment: Teams that bring together analysis results, sources and discussions on one workspace.
Suitable tasks
Collaborative data analysis; reports with source context; visual collaboration
Data and integration
Files and connected information sources; check specific database connections for the project.
AI functions
Questions in natural language; Create reports / charts; Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are recurring data updates and business approval implemented in the company's own workflow?
Databox connects KPIs from business applications with dashboards, reports and an AI analyst. On request, this can create analyses and describe changes in the data. The offer appeals to growing companies and agencies, among others, that produce regular performance reports. Before introduction, the required sources, KPI definitions and update intervals should be settled. A meaningful test compares an already known report with the generated analysis and then checks specific follow-up questions.
Assessment: Growing companies and agencies with reports from several business applications.
Suitable tasks
KPI reports; marketing and sales reporting; reports for agency clients
Data and integration
Salesforce, HubSpot and Google Analytics 4, among others; also spreadsheets, databases and APIs according to the provider.
With Genie Agents, Databricks offers natural-language analysis of business-delimited data sets. Subject-matter experts store definitions and example queries; a question set can check the quality of answers. The offer is relevant above all where data is already managed in the Databricks environment. For introduction, a specific specialist area with clear permissions and known comparison results should be chosen before further user groups access the same data.
Assessment: Companies with a Databricks data platform and business-curated analysis areas.
Suitable tasks
Data queries for specialist areas; analyses on Databricks; integration into own applications
Data and integration
Data and files registered in Unity Catalog according to the product description.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which data, example queries and benchmarks are released for each Genie agent?
Primary sources · checked on 31.10.2026 Genie Agents
Datapad creates a dashboard proposal from connected operational data sources and information about the task. The offer is aimed at teams that track KPIs regularly and then want to adapt the presentation to their work. Whether a proposed KPI is right in business terms can be checked using an existing report as a reference.
Assessment: Specialist areas with prepared data connections and recurring KPIs
Suitable tasks
Operational dashboards; KPI overviews
Data and integration
Connected business applications and databases
AI functions
Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Compare proposed KPI formulas, filters and updating against the reference report.
DataSquirrel supports the cleaning, analysis and visualisation of data sets and presents results in dashboard reports. The offer is aimed at people without SQL or programming skills of their own. For the check, a file with inconsistent date formats and known totals is suitable, so that changes become visible during preparation.
Assessment: Business users with recurring file-based analyses
Suitable tasks
Data preparation; dashboard reports; departmental analyses
Data and integration
Data sets provided for the analysis
AI functions
Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Compare cleaning steps and KPI results with the source file.
Domyn, formerly iGenius, describes data agents with natural-language querying and business context from a Business Knowledge Graph. The current agents page continues to list Crystal as an entry point for analysing company data. The offer also addresses regulated sectors and industrial companies. For a reporting project, specific data sources, required operating conditions and the traceability of individual analyses should therefore be examined. General platform promises do not replace a test of the company's own report.
Assessment: Companies with individual data models and particular requirements for the operating environment.
Suitable tasks
Conversational analytics; analysing company data; monitoring KPIs
Data and integration
Structured and unstructured company sources; determine specific connectors in advance.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which Crystal functions, data sources and operating variants are specifically part of the offer?
From a data question phrased in English, Draxlr generates a read-only SQL query and shows the results as a table or chart. The generated query remains viewable and can be adopted or revised. This makes business alignment easier between the people who need KPIs and the team that looks after the database.
Assessment: Specialist areas supported by a data team experienced in SQL
Suitable tasks
Check SQL queries; create result charts
Data and integration
Connected SQL databases
AI functions
Questions in natural language; Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
For composite KPIs, check the resulting query and its data scope.
Equals combines spreadsheet calculation, a managed data warehouse and AI-assisted analyses. The use cases shown concentrate on sales KPIs, recurring revenue and customer development. Users can trace figures back to the formula and data source and ask follow-up questions about dashboards. For the selection, it is particularly important to check whether the existing business applications and KPI definitions fit the data model offered and how recurring reports reach the team's workflow.
Assessment: Teams focusing on sales, recurring revenue and customer development.
Suitable tasks
Sales reporting; revenue and customer KPIs; spreadsheet-based dashboards
Data and integration
Business applications with a managed Snowflake data warehouse; Salesforce is documented in the product example.
AI functions
Questions in natural language; Create reports / charts; Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which source systems and KPIs are already covered for the company's own business model?
Evidence builds reporting on versioned files, SQL and reusable presentation elements. The current platform combines this way of working with an analytics agent that answers questions about data. For companies with development capacity, an individually designed reporting system can thus emerge. The comparison should consider how business requirements get into the source code, who reviews changes and how reports are published. Access for individual user groups should also be traced using a complete example.
Assessment: Development-oriented data teams that want to manage reporting systems in a versioned way.
Suitable tasks
Reporting as code; custom analytics portals; data agents for internal reports
Data and integration
SQL-based data sources; check the specific supported integration in the project.
AI functions
Questions in natural language; Create reports / charts; Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
What responsibility for source code, publication and ongoing operation remains with the company's own team?
Fluent concentrates on producing client reports for marketing agencies. Data from advertising and analytics platforms is combined with report templates and client-specific context. The AI creates explanations and supports revision; as output, the provider names Google Slides and shareable reports. For a company register, Fluent is therefore to be classified as a specialised marketing solution. A comparison should check above all data coverage, editorial control and the reuse of existing report templates.
Assessment: Marketing agencies and teams with regular campaign reporting.
Suitable tasks
Marketing reports; agency client reporting; AI report commentary
Data and integration
Meta, Google Ads, GA4, TikTok, LinkedIn and Shopify, among others.
AI functions
Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are statements on causes checked and client-specific report requirements adopted?
Hex combines analysis work in notebooks with reports, applications and a conversational interface. A data or analytics team can use it to develop results while specialist areas ask their own questions and build on existing analyses. For the comparison, it is decisive how traceable the calculations and definitions used remain. A suitable test covers an existing analysis, a follow-up question and the handover of the result to people without programming tasks.
Assessment: Companies with an active data team and jointly used analysis results.
Suitable tasks
Collaboration between analytics and specialist teams; notebooks and dashboards; natural-language analyses
Data and integration
Connected company data; the specific connections are to be checked for the project.
AI functions
Questions in natural language; Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How can calculations, access rights and published results be controlled in business terms?
Holistics combines self-service BI with a programmable semantic layer. The AI translates questions into its own analysis language, from which the data query is generated. This allows teams to check the calculation logic used and to define KPIs centrally. The offer is of interest to companies that want to combine business consistency with versioned BI development. The selection test should show how existing definitions are adopted and whether business users can follow the results output.
Assessment: Data teams that want to manage KPIs and report content in code.
Suitable tasks
Natural-language KPI queries; versioned reporting; self-service BI
Data and integration
Connected data sources with a semantic model; a dbt integration is documented.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
What modelling and knowledge of the analysis language are required for ongoing operation?
DataArts Insight combines visual reports and dashboards with an assistant for analysis questions. The product documentation describes how questions in natural language can be turned into charts. For international use, the selection should include suitable cloud regions and the language functions actually available.
Assessment: Organisations with a data environment in Huawei Cloud
Suitable tasks
Visual reports; data questions; dashboard analyses
Data and integration
Data sets provided in DataArts Insight
AI functions
Questions in natural language; Create reports / charts
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Have availability confirmed for the region, language and required data source type.
Hunch provides building blocks for data agents, including a semantic layer with relationships and business rules. Teams can use them to build a dialogue for their own data application. In the selection, an existing KPI should be modelled once and then queried with different phrasings.
Assessment: Development teams that build their own analytics application with data chat
Suitable tasks
Build in data chat; develop agents for specialist analyses
Data and integration
Data objects and KPIs modelled for Hunch
AI functions
Questions in natural language
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Assess modelling effort and evidence for answers across several data sets.
Julius creates structured reports with charts, tables and explanations from the data provided. According to the product description, calculations are produced by executed code; results can be revised in dialogue. The offer suits teams that evaluate existing files regularly or want to try out a report first without a comprehensive BI project. With business data, file scope, reproducibility, access rights and the checking of calculations should be tested in concrete terms before broader use.
Assessment: Teams with clearly delimited, file-based analysis and reporting tasks.
Suitable tasks
File-based business reports; sales and marketing analyses; reports from spreadsheets
Data and integration
Excel, CSV, Google Sheets, PDF and text files; database integration according to the product page.
AI functions
Questions in natural language; Create reports / charts; Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are the sources, calculations and updates of a recurring report controlled?
ktx prepares definitions, relationships and database queries for analytics agents. Data teams can check the business logic before it is used for further questions. The offer is particularly relevant where several assistants access a shared data model and are to interpret the same terms consistently across the company.
Assessment: Data teams that want to commit analytics agents to shared KPIs
Suitable tasks
Governed agent queries; shared KPI logic
Data and integration
Warehouse, semantic layer and existing modelling artefacts
AI functions
Questions in natural language
Operating model
Open-source engine for self-hosting and hosted ktx variant according to the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Clarify effort for model review, approval steps and existing BI interfaces.
Lightdash provides AI agents on a semantic layer maintained in code. Users can ask questions in the analysis interface and in connected communication tools. The query returned can be opened and checked in the regular analysis. The offer suits in particular teams that already model KPIs systematically or want to build this up. Before deciding, it should be clarified who will permanently look after definitions, access rights and feedback on incorrect answers.
Assessment: Data teams with versioned KPIs and a need for self-service analyses.
Suitable tasks
Natural-language BI; dbt-based KPIs; analyses for specialist areas
Data and integration
Data warehouse; semantic definitions in the dbt project or in Lightdash YAML.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which functions are already available and which are still in development or beta according to the roadmap?
Luzmo offers embedded analytics for software products and other working interfaces. Users can ask questions and receive visualised answers; the provider places the focus on reference to released customer data. The offer is of particular interest to companies with a portal or software solution of their own. In the selection test, data delimitation, permissions and behaviour on follow-up questions should therefore be checked using two different customer contexts, in addition to the design and integration of the analyses.
Assessment: Software providers and companies with customer-facing analytics interfaces.
Suitable tasks
Embedded analytics; customer portals with reporting; natural-language data analysis
Data and integration
Customer data provided for the embedded application; check specific connectors.
AI functions
Questions in natural language; Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How is data from different customers separated and permissions applied across follow-up questions?
Metabase offers self-service BI and complements data querying with Metabot. The AI functions generate queries, tables and charts based on the data model and support work with SQL. The provider documents cloud and self-operated variants. For the selection, companies should check the permissions and functions required in the respective edition, and determine which model service is used and how the generated analyses are accepted in business terms.
Assessment: Companies seeking open BI building blocks and choices in operation.
Suitable tasks
Self-service BI; natural-language data analysis; embedded reports
Data and integration
Connected databases or warehouses; CSV uploads are also documented.
AI functions
Questions in natural language; Create reports / charts; Draft comments
Operating model
Cloud or self-hosting; configure model integration separately.
Pricing basis
Price to be clarified in the project
Check before selecting
Which edition, model integration and additional governance functions are needed?
NLSQL translates business questions about a database into SQL. The interface can be integrated into business communication applications. For the test, a question with internal technical vocabulary is recommended, for example about booked rather than invoiced orders. This shows whether the wording leads to the right selection of data.
Assessment: Specialist areas that want to retrieve database KPIs via a dialogue
Suitable tasks
Database questions; queries in team chat
Data and integration
Databases released for the queries
AI functions
Questions in natural language
Operating model
Installation in the customer's cloud subscription is described. Define operating scope in the offer.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Clarify read permissions, technical terms and the interpretation of ambiguous questions in the pilot.
Omni combines a shared KPI definition with dashboards, spreadsheet calculation, SQL and an AI conversation. Users can narrow questions further and explore the results in more depth in a workbook. For a mid-sized company, this is particularly relevant if several specialist areas have so far calculated the same terms differently. In the test, therefore, the interface alone should not be what convinces: a known report must be reproducible with the agreed definitions and the intended user permissions.
Assessment: Companies that want to build several analysis interfaces on shared KPIs.
Polymer offers embedded analytics for software products. Developers can include reports and visualisations in their application via an interface; the interface can be adapted to the company's own look and feel. The product description also mentions AI-assisted visualisation and access control. The offer is thus relevant above all for companies with a customer portal or software of their own. For the selection, a real embedding case should be checked, including permissions, data updating and report design.
Assessment: Software providers and companies that integrate reporting into their own applications.
Suitable tasks
Customer portals with analyses; embedded reports; AI-assisted visualisation
Data and integration
Databases and warehouses via API; connectors for advertising, commerce and web analytics data.
AI functions
Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are tenants separated and the required data sources and updates connected?
Powerdrill Bloom enables queries across documents and databases in natural language. The platform describes references to the passages used. In a pilot, a controlling department can test, for example, whether a figure in an analysis is traced back to the right data set and, where necessary, to the right explanation.
Assessment: Teams that evaluate structured KPIs together with explanations
Suitable tasks
Check figures and explanations; source-based analyses
Data and integration
Documents and connected databases
AI functions
Questions in natural language
Operating model
On-premises or private cloud according to the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Test provenance evidence and permissions for figures and text sources separately.
Preset offers a commercial analytics platform based on Apache Superset. In addition to dashboards and an SQL editor, the provider describes a chatbot for exploring data and creating visualisations. The offer is thus relevant for companies that want to combine Superset functions with a managed operating model. The comparison should cover the specific operating variant, the migration of existing analyses and the permissions for internal users or customers of the embedded application.
Assessment: Teams that want to use Superset-based BI with commercial support or cloud operation.
Suitable tasks
Superset-based reporting; embedded dashboards; AI-assisted data exploration
Data and integration
Connected databases and modelled data sets; check the specific connection.
AI functions
Questions in natural language; Create reports / charts
Operating model
Cloud, managed private cloud or self-operated variant according to the provider.
Pricing basis
Price to be clarified in the project
Check before selecting
Which services distinguish the cloud, managed private cloud and self-operated variants?
Quadratic combines a spreadsheet interface with AI, formulas and executable code. Users can ask questions; the application generates calculations and charts for them. Files and connected databases serve as a starting point. This is of interest to teams that work in spreadsheets but want to automate recurring data preparation and analysis to a greater extent. In the selection test, an existing report should be rebuilt and then checked for how new data, changed formulas and joint editing have an effect.
Assessment: Teams that want to combine spreadsheet work with code and connected data sources.
Suitable tasks
Spreadsheet-based analysis; reports from files and databases; AI-assisted charts
Data and integration
CSV, Excel, PostgreSQL, Snowflake and BigQuery, among others, according to the product page.
AI functions
Questions in natural language; Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which calculations remain viewable and how are recurring updates safeguarded?
Querio combines data analysis, notebooks and dashboards with a foundation managed in Git. Business context and calculations can be maintained together with the reports; the platform also shows recurring outputs and embedded analytics. The offer suits teams that want to combine AI-assisted analyses with traceable development. A selection test should include both a simple business question and the change of a KPI, and show how this change reaches the existing reports.
Assessment: Development-oriented teams with a need for jointly maintained context and reports.
Suitable tasks
AI data analysis; versioned dashboards; recurring reports
Data and integration
Connected data warehouse; the specific connections are to be checked for the project.
AI functions
Questions in natural language; Create reports / charts; Draft comments
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are changes to KPIs, code and published analyses reviewed?
Rill offers operational BI with interactive dashboards and a natural-language analysis interface. KPIs and report elements can be managed as code; the product page also describes the investigation of conspicuous changes. The offer is of particular interest to teams that frequently query extensive operational data sets. For a comparison, typical periods, filters and detail queries should therefore be tested with the company's own data, as should the maintenance of shared KPIs and the intended user permissions.
Assessment: Teams with frequent detail queries on operational KPIs.
Suitable tasks
Operational reporting; time series and KPIs; embedded analyses
Data and integration
Connected operational data; check specific sources and update routes in the project.
AI functions
Questions in natural language; Draft comments; Detect anomalies
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
What data volumes, periods and update requirements must the company's own test cover?
Sequel connects business systems and warehouses with analysis requests from Claude or ChatGPT. According to the provider, the connections are read-only. Shared metric definitions and the visible query are intended to help answer follow-up questions on marketing, sales and revenue KPIs on the same basis.
Assessment: Teams with several SaaS data sources and an existing AI workspace
Suitable tasks
Querying distributed KPIs; marketing and revenue analysis
Data and integration
GA4, Google Ads, HubSpot, Stripe and warehouse data, among others
AI functions
Questions in natural language
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Check the assistant's access rights and the actual calculation steps for each KPI.
Cortex Agents uses Cortex Analyst to query structured data on the basis of semantic views. Snowflake recommends access via the agents for new analytics functions. KPIs already defined and verified example queries are therefore just as relevant for the selection as the language model used.
Assessment: Companies with data and maintained business views in Snowflake
Suitable tasks
Business questions on warehouse data; SQL generation
Data and integration
Structured Snowflake data and semantic views
AI functions
Questions in natural language
Operating model
Clarify provision and data region with the provider.
Pricing basis
Clarify price and scope of services with the provider.
Check before selecting
Check the transition of existing applications and results for ambiguous business terms.
Supaboard connects files, databases and warehouses with an analytics agent. Answers can be reused as a dashboard, report or recurring workflow. The product page also describes business rules, example queries and tests for answer quality. For companies, this is of interest if a clearly delimited data set is to become accessible to several business users. Before selecting, a company's own question set and known results should be defined in order to check answers and permissions in a traceable way.
Assessment: Teams that want to combine data queries and recurring report outputs.
Suitable tasks
Natural-language data analysis; dashboards and reports; recurring analyses
Data and integration
Files, databases and data warehouses; BigQuery is explicitly shown on the product page.
AI functions
Questions in natural language; Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which rules, examples and test questions does the agent need for the company's own data set?
Tellius offers an analytics platform with voice input, automated investigations and visualised results. The provider combines these functions with data integration, semantic context and machine learning methods. This is of interest to teams that, besides regular reports, also want to investigate changes in the data. In a comparison, the same business questions, known results and exceptional situations should be used so that the benefit for the company's own data can actually be assessed.
Assessment: Analytics and specialist teams with recurring in-depth data questions.
Suitable tasks
Conversational analytics; analysis of KPI changes; reports with explanations
Data and integration
Integration of company-owned data sources; check specific connectors for the project.
AI functions
Questions in natural language; Draft comments; Create forecasts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which analysis methods, data sources and AI functions are included in the package offered?
TextQL connects company data with a business ontology and the analytics agent Ana. The platform describes multi-step investigations across larger data sets and various sources. This is of interest above all to companies whose analysis questions touch several systems and many business relationships. For a selection, the scope and meaning of the data basis should be settled in advance. A known report and targeted follow-up questions help to check whether results and how they arise are sufficiently traceable.
Assessment: Companies with extensive and business-complex data landscapes.
Suitable tasks
Complex company analyses; data questions across several sources; analytics agents
Data and integration
The platform names SAP, Oracle, Teradata, Snowflake and Databricks, among others; check specific integration.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
What modelling and integration effort is required for the company's own data sources?
ThoughtSpot combines dashboards with the analytics assistant Spotter and a shared semantic layer. Specialist areas can ask questions about company data; the underlying query logic remains viewable. For the selection, it is mainly of interest how an existing KPI catalogue is adopted into the platform. The offer suits companies that want to build regulated access to their data for many users and reduce recurring follow-up questions to the data team.
Assessment: Companies with a central data set and jointly defined KPIs.
Toucan offers an analytics platform and a supported approach to custom data applications. The current presentation combines specialised AI agents with human review of the published application. There is also an offer for self-built and embedded analytics. For companies without a large in-house BI team, it is particularly worth comparing which tasks the provider takes on. A concrete report should make the scope of services visible for data preparation, KPI definition, design, acceptance and ongoing maintenance.
Assessment: Companies seeking supported implementation of data applications and reports.
Suitable tasks
Supported data applications; embedded analytics; custom dashboards
Data and integration
Company data and semantic KPIs; clarify specific connectors with the provider.
AI functions
Create reports / charts
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
Which tasks are included in the managed offer, and which does the in-house team take on?
Upsolve develops data agents for recurring questions from specialist areas. The platform stresses the knowledge of a company's KPIs, systems and terms that this requires. A meaningful pilot therefore includes questions whose correct answer depends on an internal definition, such as the status of an order.
Assessment: Companies with frequent follow-up questions to a central data team
Suitable tasks
Recurring specialist questions; data analysis agents
Data and integration
Company data and specialist context connected for analysis agents
AI functions
Questions in natural language
Operating model
The Enterprise plan mentions on-premises, self-hosting and VPC. Clarify availability in the project.
Pricing basis
Tiered plans with credits. Enterprise is agreed individually.
Check before selecting
Ask for a demonstration of how KPI definitions are stored, corrected and used in follow-up questions.
Vanna is an open framework for data agents with natural-language access to databases. The product page describes several database and model options as well as supplementary administration functions. The offer is therefore aimed particularly at development teams that want to integrate a query function into their own applications. For a commercial specialist area, it should be clarified in advance which user interface, report output and support are needed in addition to the technical foundation, and who is permanently responsible for these components.
Assessment: Development teams that want to build their own data query assistants.
Suitable tasks
Text-to-SQL; data agents in your own applications; natural-language database access
Data and integration
Including SQLite, PostgreSQL, MySQL, Snowflake and BigQuery.
AI functions
Questions in natural language
Operating model
Self-hosting of the open framework or cloud offer; optional administration functions.
Pricing basis
Price to be clarified in the project
Check before selecting
What effort is involved for the interface, permission checks, presentation of results and operation?
Phrazor focuses on the linguistic preparation of KPIs for recurring reports. The provider describes the creation of personalised reports with texts based on data. In the selection test, two recipients should receive the same data status with different specialist views, so that the consistency and comprehensibility of the explanations can be compared.
Assessment: Organisations with many recurring reports and a fixed group of recipients
Zenlytic provides an AI data analyst that uses shared specialist definitions for its answers. Access can take place in its own application and through other working environments. The focus is on combining company context, data queries and controllable user permissions. For companies with an existing data warehouse, it is worth checking how well their own terms and calculations are represented. A suitable comparison uses several questions that are equivalent in business terms and checks the figures returned for them.
Assessment: Companies that are building a shared specialist context for AI data queries.
Suitable tasks
Natural-language data analysis; KPIs for specialist areas; analysis in existing working environments
Data and integration
Company-owned data warehouse and maintained specialist context; check specific connectors.
AI functions
Questions in natural language
Operating model
Not conclusively checked
Pricing basis
Price to be clarified in the project
Check before selecting
How are KPI definitions, user permissions and incorrect answers maintained on an ongoing basis?
