About Query.AI
Query.AI is a data discovery software from Query.AI that helps organizations manage and analyze their data resources. It provides tools for data visualization, integration with various data sources, and advanced search capabilities so users can quickly find relevant information. Designed to assist in complex data environments, Query.AI supports efficient data querying and reporting functionalities. Users benefit from its ability to facilitate compliance, governance, and decision-making processes by using data insights. Key capabilities: data visualization data integration advanced search reporting tools compliance support Best for: data analysts and business intelligence professionals that need to navigate extensive data sets for informed decision-making.
Query.AI delivers a transformative approach to cybersecurity data analysis through its federated detection model, addressing one of the most persistent challenges in modern security operations: the need for unified insights from decentralized data sources. Rather than relying on traditional data ingestion and centralization models—which are costly, time-consuming, and difficult to scale—[Query.AI](http://Query.AI) allows security teams to access and analyze data exactly where it resides, whether in the cloud, on-premises, or across SaaS platforms. This shift is not only more efficient but also dramatically reduces infrastructure expenses and complexity, while maintaining full-fidelity access to real-time and historical data for faster investigations, threat hunting, and response activities. The software’s ease of use is strongly implied through its "quick and easy API connectors" and an abstracted query layer that eliminates the need for users to understand specific data structures or search languages. This design decision enhances accessibility for analysts and engineers alike, enabling them to search across diverse sources through a single pane of glass and receive normalized results via the Open Cybersecurity Schema Framework (OCSF).
Pros & Cons
- +No Data Movement Required Access and analyze data in place—no need to ingest or centralize into a SIEM.
- +Faster Investigations Enables direct, real-time querying across multiple sources, accelerating threat detection.
- +Cost-Effective Architecture Reduces expenses related to storage, data pipelines, and log duplication.
- +Unified Schema (OCSF) Normalizes data across platforms, simplifying alerting and detection rule creation.
- +Extensive Integration Supports a wide range of cloud, SaaS, and on-prem tools like AWS, Azure, Google, CrowdStrike, Splunk, and more.
- +Cloud + On-Premise Flexibility Designed to work across hybrid environments—modern and legacy infrastructure alike.
- −Emerging Model Federated detection is still maturing and may not fully replace all SIEM features yet.
- −API Access Dependency Relies on availability and proper configuration of source APIs—which may not always be feasible.
- −Technical Onboarding Curve Setup and effective use may require familiarity with schema mapping, detection logic, and API-based workflows.
- −Data Freshness Limitations Real-time querying can miss ephemeral data if logs aren’t retained at the source.
Features
Key features
- Federated Search and Detection
- Enables users to search and trigger cybersecurity alerts from distributed data sources without needing to centralize or ingest the data.
- Quick & Easy API Connectors
- Provides a wide array of pre-built API connectors to various cloud, SaaS, and on-prem technologies, simplifying data access.
- Vendor-Agnostic Normalization (OCSF)
- Normalizes search results from disparate sources into a common, vendor-agnostic format (OCSF) at the time of the query.
- Cost Control
- Helps reduce security data storage and access costs by avoiding the need to centralize and duplicate data in a SIEM.
- Real-time Data Access
- Allows security teams to access and search both real-time and historical data where it resides, without pipeline delays.
- Full Data Visibility
- Expands visibility for security investigations by allowing searches across a broad range of data sources, including non-security data.
Additional features
- Federated Detection Solution
- The core platform provides a federated detection solution for security.
- Quick & Easy API Connectors
- Offers pre-built API connectors to various Cloud, SaaS, and On-Prem technologies.
- Cloud Infrastructure & Security Connectors
- Integrates with technologies like Amazon, Azure, and Google Cloud security tools.
- Data Lakes & Data Warehouses Connectors
- Connects to data storage solutions like Amazon S3, Redshift, Snowflake, and Databricks.
- Data Security Connectors
- Connects with data security platforms like Cyera DSPM.
- Email Security & Communication Connectors
- Integrates with services like Google Messages and Workspace APIs.
- Endpoint Connectors
- Connects to endpoint security platforms like CrowdStrike, SentinelOne, and VMWare Carbon Black.
- Identity & HR Connectors
- Integrates with identity management solutions like Auth0, Okta, and Microsoft Entra ID.
- IT Service Management Connectors
- Connects with platforms like ServiceNow.
- Mobile Device Management Connectors
- Integrates with tools like JAMF and Microsoft Intune.
- SIEM & Log Management Connectors
- Connects to SIEM and log management platforms like Splunk, Microsoft Sentinel, and Datadog.
- Threat Intelligence & Enrichment Connectors
- Integrates with threat intelligence feeds and services like VirusTotal and Shodan.io.
- API Management
- Manages APIs to put security data to work.
- Federated Search
- Enables searching data where it resides without centralization.
- In-flight Data Normalization
- Normalizes data as it is being searched.
- OCSF Normalization
- Results are returned in the normalized OCSF (Open Cybersecurity Schema Framework) format.
- Centralized Insights from Decentralized Data
- Unifies distributed data to provide immediate context for investigations.
- Real-time and Historical Data Access
- Provides access to both real-time and archived data sources.
- Increased Visibility
- Allows access to more data sources for security investigations and threat hunting.
- Accelerated Investigations
- Speeds up security investigations, threat hunting, and incident response.
- No Data Ingestion
- Eliminates the need for data pipelines and centralization, reducing costs and delays.
Pricing
Countries & Languages
Interface languages
Billing currencies
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About Query.AI
Query.AI is a data discovery software from Query.AI that helps organizations manage and analyze their data resources. It provides tools for data visualization, integration with various data sources, and advanced search capabilities so users can quickly find relevant information. Designed to assist in complex data environments, Query.AI supports efficient data querying and reporting functionalities. Users benefit from its ability to facilitate compliance, governance, and decision-making processes by using data insights. Key capabilities: data visualization data integration advanced search reporting tools compliance support Best for: data analysts and business intelligence professionals that need to navigate extensive data sets for informed decision-making.
Query.AI Details
Query.AI's In-App Market Place
Does Query.AI have an in-app market place?
Yes
How many Mini-Apps in the marketplace?
1
Mini Apps
N/A
Pricing Options
Accepted Payment Currencies
USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (Fr), CNY (¥), SEK (kr), INR (₹), CDF (FC)
Pros & Cons
- No Data Movement Required Access and analyze data in place—no need to ingest or centralize into a SIEM.
- Faster Investigations Enables direct, real-time querying across multiple sources, accelerating threat detection.
- Cost-Effective Architecture Reduces expenses related to storage, data pipelines, and log duplication.
- Unified Schema (OCSF) Normalizes data across platforms, simplifying alerting and detection rule creation.
- Extensive Integration Supports a wide range of cloud, SaaS, and on-prem tools like AWS, Azure, Google, CrowdStrike, Splunk, and more.
- Cloud + On-Premise Flexibility Designed to work across hybrid environments—modern and legacy infrastructure alike.
- Emerging Model Federated detection is still maturing and may not fully replace all SIEM features yet.
- API Access Dependency Relies on availability and proper configuration of source APIs—which may not always be feasible.
- Technical Onboarding Curve Setup and effective use may require familiarity with schema mapping, detection logic, and API-based workflows.
- Data Freshness Limitations Real-time querying can miss ephemeral data if logs aren’t retained at the source.
Query.AI's Support Options
Documentation
https://docs.query.ai/docs/introducing-queryQuery.AI's Alternatives
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