Knowi
Analytics platforms
Predictive analytics software
IoT analytics platforms
Dashboard software
Healthcare BI software
KPI software
Reporting software
Report writing software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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What is Knowi
Knowi is an analytics and business intelligence platform that connects to multiple data sources and supports building dashboards and reports. It is used by analysts and business teams to query, visualize, and distribute metrics, including use cases that involve operational and IoT-style time-series data. The product emphasizes broad data-source connectivity and embedded analytics options for delivering insights inside other applications.
Broad data-source connectivity
Knowi supports connecting to a range of databases and data services, including SQL and NoSQL systems, which can reduce the need to move data into a single warehouse for basic reporting. This is useful for organizations with heterogeneous stacks and multiple operational data stores. It can also help teams prototype analytics quickly when data is spread across systems.
Dashboards and scheduled reporting
The platform provides dashboards and reporting features that cover common BI needs such as KPI tracking and recurring distribution. This supports operational reporting workflows where stakeholders expect regular updates without logging into a separate tool. It fits teams that need both interactive views and routine report delivery.
Embedded analytics capability
Knowi is positioned to support embedding dashboards/visualizations into other applications and portals. This can be relevant for software teams that need to expose analytics to customers or internal users within an existing product experience. Embedded delivery can reduce context switching compared with standalone BI consumption.
Smaller ecosystem and mindshare
Compared with larger, widely adopted analytics platforms, Knowi typically has a smaller community footprint and fewer third-party extensions. This can affect the availability of prebuilt templates, connectors maintained by partners, and the depth of peer-to-peer implementation guidance. Organizations may rely more on vendor support and internal expertise.
Advanced modeling may vary
Teams that require robust semantic modeling, governed metric layers, and complex enterprise data governance may find capabilities differ from tools designed primarily for large-scale enterprise BI programs. Depending on requirements, additional data modeling work may be needed upstream in the data warehouse or transformation layer. This can increase implementation effort for highly standardized reporting environments.
Predictive features not primary focus
While the product is used for analytics and can support data exploration, organizations seeking end-to-end predictive analytics workflows (feature engineering, model management, and deployment) may need separate specialized tooling. Predictive use cases may require integration with external ML platforms and operationalization processes. This adds complexity for teams expecting a single platform to cover BI and full ML lifecycle.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Basic | Contact sales / Not publicly listed | 5 login users; Unlimited queries, widgets, dashboards; Native SQL/NoSQL/REST/JSON integrations; ElasticStore up to 2M records; Scheduled reporting, exports (ppt/pdf/csv), alerts, Push API, 2‑factor auth; Cloud deployment. |
| Team | Contact sales / Not publicly listed | Custom number of login users; Unlimited queries & dashboards; Native integrations; ElasticStore up to 15M records; additional enterprise features/checks vs Basic; Cloud deployment. |
| Enterprise | Contact sales / Not publicly listed | Custom users and limits; Full feature set including OEM/embedding/white‑labeling, Management API, DBWrite, AI Analytics; ElasticStore/custom record limits; Deployment: Cloud/On‑Premise/Hybrid. |
