Knowi

by Knowi  · Based in United States → — The AI analytics platform for SQL, MongoDB, Elasticsearch, APIs, and documents.
Family Medicine Hospital Medicine Internal Medicine
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Overview

Knowi is an AI analytics platform that offers seamless data integration from over 70 sources, including SQL, NoSQL, REST APIs, and cloud databases, without requiring ETL. It provides private AI capabilities, ensuring data privacy by running its own AI models, inference, and vector search within its infrastructure, meaning data never leaves the user’s boundary. Users can query data in plain English, generate dashboards from natural language, and gain machine learning insights without coding. Knowi also features Agentic BI, which utilizes specialized AI agents for tasks like querying, dashboard creation, report delivery, and document analysis across various connected data sources. The platform supports embedded analytics for white-labeling and offers robust security and governance with role-based and row-level security. Deployment options include on-premise, cloud, or hybrid models, and it’s built to handle petabyte-scale data volumes.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • 70+ native data integrations
  • Private AI (no third-party data leakage)
  • Natural language querying
  • Agentic BI for automated analytics
  • Embedded analytics
  • 40+ visualization types
  • Multi-tenant & row-level security
  • On-premise, cloud, or hybrid deployment
  • Scalable for petabyte-scale data
  • Document AI

Use Cases

  • Sales & Marketing analytics
  • Engineering data-as-a-service
  • Customer Success optimization
  • Healthcare data analysis
  • Financial reporting
  • Operational intelligence

What Physicians Need to Know

Healthcare API Support (FHIR/HL7)
Knowi connects directly to Epic (Clarity/Caboodle), Cerner (Oracle Millennium), FHIR R4 APIs, and HL7 feeds, eliminating the need for middleware or ETL pipelines. It can also connect to custom REST APIs and any SQL or NoSQL database where EHR data resides.
HIPAA-Compliant Infrastructure
Knowi supports HIPAA-compliant deployments through on-premises installation (Docker, Kubernetes, or bare metal) and a SOC 2 Type II certified cloud option. It signs Business Associate Agreements (BAAs) with all healthcare customers. The platform includes role-based access controls, row-level security, audit logging, and data encryption in transit (TLS 1.2+) and at rest (AES-256). Knowi's Private AI runs its AI engine entirely within your deployment, ensuring PHI never touches external LLMs like OpenAI or Google.
Clinical NLP Capabilities
Knowi offers Natural Language Processing (NLP) for self-service analytics, allowing non-technical users to ask questions in plain English and receive insights and visualizations. This includes capabilities for natural language queries across all datasets and within widgets, with auto-complete suggestions and the ability to specify datasets. Knowi's Document AI also allows users to upload documents and ask natural language questions to get answers directly from the content.
De-Identification Tools
While Knowi focuses on secure data handling within its platform, it emphasizes that de-identification for analytics must follow HIPAA Safe Harbor or Expert Determination methods. Knowi's architecture, by querying data directly at the source without requiring a data warehouse, reduces PHI duplication and thus the number of systems that need to be secured and de-identified.
Medical Terminology Support
Knowi's NLP capabilities enable users to ask questions in plain English, which can be applied to clinical and operational data. This implies an understanding or ability to process medical terminology within natural language queries to generate relevant insights.
Sandbox/Testing Environment
Knowi offers a 21-day free trial. While not explicitly called a 'sandbox environment' for developers, the platform's ability to connect to data sources directly and rapidly deploy dashboards (within 2-3 weeks) suggests a flexible environment for testing and development.
SDK Languages
Knowi provides a Python SDK (knowipy) for Python 3.6 and above, which streamlines API programming for managing dashboards, widgets, datasources, queries, users, and natural language queries. A JavaScript SDK is also available for embedding analytics into modern front-end frameworks like React, Vue, and Angular.
Rate Limits & Pricing
Knowi uses annual licensing with predictable pricing not based on per-user or per-query volume, meaning costs remain flat as teams grow. Pricing starts at $20,000/year for up to 5 users, with custom pricing for embedded analytics and regulated industries. Knowi handles API rate limits and pagination automatically for connected sources, including auto-retries with exponential backoff on 429 errors.
Physician Tip

Knowi's natural language query capabilities allow clinicians and operations leads to ask questions in plain English and get immediate insights from live data across EHRs, claims, and operational systems, without needing IT support or data analysts. This can significantly reduce the time to get answers on critical operational questions like readmission rates or staffing, empowering data-driven decision-making at the point of care and in administrative functions. The 'Private AI' feature ensures patient data privacy by processing all AI queries within your secure environment, addressing major HIPAA concerns for AI adoption in healthcare.

Knowi offers native connectivity to over 70 data sources, including SQL, NoSQL (MongoDB, Elasticsearch), REST APIs (including FHIR endpoints), EHR systems (Epic, Cerner), and HL7 feeds. It can join data across these disparate sources in a single query at runtime without requiring ETL or a data warehouse, keeping data in its original location. This allows for blending EHR data with claims, billing, scheduling, and IoT device feeds. Knowi also supports embedding analytics into third-party applications with full white-labeling and multi-tenant capabilities.

Details

Category Developer Tools & APIs, Practice Analytics & BI
Pricing Contact for pricing — Custom plans available; contact sales for details.
DeploymentOn-premise, Cloud, Hybrid
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Unknown AI-estimated
Integrations
EHR Not specified
Specialties Family Medicine, Hospital Medicine, Internal Medicine

What the Web Says

Knowi is an AI-powered analytics platform that unifies diverse data sources, including SQL, NoSQL, and REST APIs, to provide real-time insights and reporting. It is praised for its ease of use, robust data integration capabilities, and exceptional customer support, making it suitable for both technical and non-technical users.

Overall: Positive

Strengths

  • Seamless integration with various data sources (SQL, NoSQL, APIs) without complex ETL processes.
  • User-friendly interface and no-code options for dashboard creation and data analysis, making it accessible to non-technical users.
  • Exceptional and responsive customer support, including proactive feature implementation and personalized guidance.
  • Real-time data processing and visualization for immediate insights and faster decision-making.
  • AI capabilities, including natural language processing for conversational queries and AI-generated dashboards.
  • Ability to embed interactive dashboards into other platforms and applications, streamlining reporting for clients.

Limitations

  • Learning curve for some of the more advanced features and complex data sets.
  • Some users desire more widget filtering options and the ability to save shareable prebuilt/favorite filters.
  • Limited reviews from specific healthcare IT professionals or physicians, though a case study with Lemonaid Health exists.
  • One Reddit thread from 2022 suggests some users hadn't heard of Knowi, indicating potentially lower brand recognition compared to larger BI tools.
  • Only one review on Trustpilot with a mixed rating.

Based on reviews from: G2, Capterra, SelectHub, Research.com, Reddit, Trustpilot

Last updated: 2026-06-23

Ratings & Reviews

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Press & Coverage

Knowi
Healthcare Analytics Tools: 9 HIPAA-Compliant Platforms Compared (2026)
This article compares 9 HIPAA-compliant healthcare analytics platforms for 2026, highlighting Knowi as the only one offering on-premises deployment, private AI (no external LLM calls), and native connectivity to SQL, NoSQL, and APIs without ETL. It emphasizes the importance of keeping Protected Health Information (PHI) within an organization's infrastructure and the limitations of cloud-only platforms for many health systems.
2026-06
Knowi
Knowi New Launch and Product Update u2013 Aug 2024
This press release announces Knowi's AI Service, enabling auto-generated dashboards, instant insights, machine learning predictions, and natural language processing for data interaction. It also highlights the ability to integrate data with documents to unlock untapped information.
2024-09
Knowi
Healthcare Data Management Challenges in 2026 (Interoperability, PHI, AI)
This article discusses the major healthcare data management challenges for 2026, including interoperability gaps, PHI security, patient identity matching, governance, unstructured data complexity, and AI deployment risk. It positions Knowi's platform as a solution for connecting siloed healthcare data sources without requiring ETL, thereby strengthening security.
2026-06
Knowi
Customer Stories: Transformative Data Journeys Unveiled - Knowi
This page showcases various customer stories, demonstrating how organizations utilize Knowi for diverse applications, from healthcare compliance to music licensing analytics, to connect, analyze, and act on data from any source.
2026-06
Knowi
Healthcare Analytics Statistics 2026: Key Data and Trends - Knowi
This article presents key statistics and trends in healthcare analytics for 2026, noting that healthcare organizations generated 30% of the world's data in 2025, yet 97% of hospital data goes unused. It also highlights the high cost of healthcare data breaches and the widespread adoption of AI in the industry.
2026-06

Videos

Product demos, reviews, and walkthroughs for Knowi.

View all on YouTube

Frequently Asked Questions

Knowi is a business intelligence platform that can integrate data from various sources, including clinical systems, to provide insights into practice performance, patient outcomes, and operational efficiency. For physicians, this means better data-driven decision-making to optimize patient care and practice management.
Knowi emphasizes its commitment to data security and compliance, including HIPAA. It employs robust security measures such as encryption, access controls, and audit trails to protect patient health information.
Knowi's pricing is generally subscription-based and can vary depending on the features, data volume, and number of users. While specific healthcare-centric tiers aren't always explicitly advertised, it's common for them to offer customized plans or enterprise solutions that can be tailored to the needs of medical practices.
While Knowi excels at data aggregation and analysis, its primary limitation for physicians might be its role as a separate analytics platform rather than a direct, real-time clinical decision support tool embedded within an EHR. While it can integrate with EHRs, it typically provides insights retrospectively or near real-time, rather than instantaneous point-of-care guidance.
Knowi differentiates itself by its ability to integrate with a wider variety of data sources, including NoSQL and unstructured data, which can be beneficial for diverse healthcare data. While Tableau and Power BI are powerful general BI tools, Knowi often offers more flexibility in data connectivity and a stronger focus on embedded analytics, which can be advantageous for healthcare applications requiring custom dashboards and reports.
While Knowi aims for user-friendliness, some technical expertise is generally beneficial for initial setup, data source integration, and complex dashboard creation. Many practices may find it helpful to have IT support or work with Knowi's professional services to optimize implementation and ongoing management, especially for intricate data models.

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Suggest an Edit → | Last Verified: 2026-06-23 | First Added: 2026-06-23
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