Healthcare analytics on your clinical, billing and operational data. No warehouse in between.
Knowi connects to Epic, Cerner, FHIR endpoints, claims databases and scheduling systems where they already run, joins them at query time, and keeps PHI inside the boundary you control. HIPAA, signed BAA, on-premises or cloud.
What you leave with
- A working dashboard on one of your real sources, built on the call.
- A deployment plan: Knowi cloud, your VPC, or fully on-premises.
- A straight answer on whether your EHR reporting database is reachable without an ETL project.
See Knowi for Healthcare
Healthcare analytics does not have a data problem. It has a warehouse problem.
Healthcare analytics starts with three systems that never agreed
Clinical, billing and operational data sit in different databases, owned by different teams, on different refresh cycles. The warehouse-first answer is to copy all three somewhere new. Knowi's answer is to query all three where they are.
EHR and clinical data
Epic through the Clarity or Caboodle reporting databases, or Epic's FHIR R4 APIs. Cerner through the Oracle-based Millennium database or FHIR R4 endpoints. HL7 feeds, and any SQL or NoSQL store your clinical data flows into.
Encounters, readmissions, census, care qualityClaims and revenue cycle
Claims, payments and denial tracking in SQL databases and billing APIs. Knowi joins a claims table to encounter data in one query, so denial rate and net collection rate come from the same dataset the clinical team reads.
Denials, net collection rate, revenue leakageScheduling, HR and devices
Scheduling systems, HR platforms holding hours and holidays, spreadsheets, survey tools and device feeds over REST APIs. This is the data that explains provider productivity, and it rarely makes it into the warehouse.
Provider productivity, patient flow, staffingOne Knowi dataset can hold a FHIR query, a SQL Server claims query and a REST call to your scheduling tool. Each runs in its own language and the results are joined.
What changes when healthcare analytics skips the warehouse step
Every healthcare analytics project runs through the same five steps. Where the PHI goes at each step is the difference.
The warehouse is not wrong. It is a second, optional project. Knowi lets you start healthcare analytics without finishing it first.
Connect to the EHR where it runs.
Epic Clarity is SQL Server. Cerner Millennium is Oracle. Both are ordinary databases to Knowi, reached over an SSL or SSH tunnel with IP allowlisting, no vendor gateway appliance in the path. FHIR R4 endpoints are REST APIs and are handled the same way.
Where the network cannot expose a port at all, Knowi installs inside it. Docker or Kubernetes, in your own cloud VPC or fully on-premises, so nothing routes out to an external service.
Knowi's own AI by default. Third-party models only if you turn them on.
Clinical directors and operations managers ask questions in plain English across patient, claims and operational data and get a chart back. The model answering is Knowi's. Inference, vector search and Document AI run on Knowi infrastructure, and on-premises customers run all of it locally, agents included.
OpenAI and Claude are options you enable per feature and can switch off again. No third-party model is in the path unless you put one there.
This is what healthcare buyers usually mean by private AI: inference runs inside your deployment, and no outside model sees PHI unless you enable one.
The compliance stack behind HIPAA healthcare analytics
Every control below is published on knowi.com/security. Bring your own checklist and match them line by line.
At rest and in transit
- AES-256 for credentials and cached results at rest
- TLS 1.2 or later for all traffic in transit
- SSL or SSH tunnelling to databases behind firewalls
- Optional IP allowlisting by network
Who sees which patient
- Role-based access control and row-level security
- SSO via SAML and OpenID Connect, 2FA, LDAP
- Multi-tenancy isolation with per-tenant data boundaries
- Full audit trail of data access, queries and user actions
Paperwork and placement
- HIPAA, with a BAA available for customers handling PHI
- SOC 2 Type II report, available on request
- On-premises on Docker, Kubernetes or bare metal; cloud VPC; hybrid; air-gapped
- Cached results auto-expire; no PHI persisted beyond your configured window
Self-service healthcare analytics for the people who run the clinic
Operations managers, clinical directors and compliance officers build their own reports. IT provisions the connection once.
Readmission rates, census, care quality and patient flow across facilities, even when each location runs a different system.
Claims, payments and denials from SQL and billing APIs, joined to encounters. Find revenue leakage without waiting for IT to build the report.
Audit-ready reports that pull from every required system automatically, with query logging behind them.
Type "show readmission rates by facility last quarter" and get a chart. Readmission rate, net collection rate and census are defined once in Knowi's dataset layer, so every dashboard, alert and AI answer uses the same definition.
Alteas Health replaced Python scripts with self-service analytics.
Before Knowi, every analysis at Alteas Health meant someone technical writing a Python script. Now HR systems, clinical records and financial reporting sit in unified dashboards that everyone from new hires to the CEO uses, under HIPAA and SOC 2 Type II. They evaluated Tableau and Power BI first.
Read the full story →"Knowi's powerful Natural Language Processing capabilities and dynamic data visualization tools have empowered our team to access and analyze data with unprecedented ease and accuracy. This has significantly elevated the quality of care we provide to our patients by streamlining our operational processes."
Yaakov G., Co-Founder & CEO, Alteas Health
Healthcare organizations on Knowi
Healthcare analytics questions buyers ask before the call
Is Knowi HIPAA compliant for healthcare analytics?
Yes. Knowi runs HIPAA-compliant deployments on-premises (Docker, Kubernetes or bare metal) and in a SOC 2 Type II certified cloud, and a BAA is available for healthcare customers handling PHI. Controls include role-based access, row-level security, a full audit trail, AES-256 encryption at rest and TLS 1.2 or later in transit.
Can Knowi connect to Epic, Cerner and other EHR systems?
Yes. Epic through the Clarity (SQL Server) or Caboodle reporting databases, or Epic's FHIR R4 APIs. Cerner through the Oracle-based Millennium database or Cerner's FHIR R4 endpoints. Knowi also reads HL7 feeds, custom REST APIs, and any SQL or NoSQL database your EHR data flows into. No separate ETL pipeline is required.
Does PHI leave our environment when we run healthcare analytics in Knowi?
On-premises, no. Knowi runs inside your infrastructure and queries your databases directly. In Knowi cloud, only query results leave the source, never raw tables or exports. Results sit in a temporary cache that auto-expires, encrypted at rest with AES-256, and no PHI is stored long term.
Which AI model answers natural language questions on patient data?
Knowi's own AI by default. Models, inference and vector search run on Knowi infrastructure, and on-premises customers run the full platform and their own LLM locally. OpenAI or Claude can be enabled per feature if you want them, and switched off again. No third-party model is in the path unless you turn one on.
Do we need a data warehouse before starting healthcare analytics?
No. Knowi queries EHR databases, claims systems, REST APIs and cloud sources directly and joins across them in a single query. If you already have a warehouse, Knowi connects to it as one source among several.
How long does a healthcare analytics deployment take?
Most healthcare teams have first dashboards live within 2 to 3 weeks, because there is no warehouse build or modelling phase in front of them. Complex multi-source implementations across EHR, claims and operational systems typically complete within 30 to 60 days.
Can clinical and operations staff use Knowi without writing SQL?
Yes. A clinical director can type "show readmission rates by facility last quarter" and get a chart. Self-service report builders and drag-and-drop dashboards cover users who want to build their own views. At Alteas Health, a new hire with a non-technical background took on most of the dashboard workload after training.
How does Knowi handle multi-tenant analytics for a healthcare SaaS product?
Row-level security filters data by the authenticated user's organization, role or tenant before any query runs. A hospital client logging in through SSO sees only its own patient, claims and operational data. You build one set of dashboards and deploy them across every tenant.
See healthcare analytics running on your own clinical data.
Thirty minutes with a solutions engineer. Connect one of your real sources, or send a sample dataset, and leave with a working dashboard and a deployment plan.
See Knowi on your clinical data →Bring your EHR reporting database name and your deployment constraints.
"Knowi has had a transformative impact on our organization's data analytics. Knowi's powerful NLP capabilities and dynamic data visualization tools have empowered our team to access and analyze data with unprecedented ease and accuracy. This has significantly elevated the quality of care we provide to our patients."
Trusted by healthcare organizations
FDA-regulated health data
Medical devices
Concierge medicine
Men's health clinics
Behavioral health
Autism services
What Knowi Does for Healthcare
Analytics built for clinical and operational complexity
Healthcare data lives in EHR systems, claims databases, operational tools, and cloud services. Most analytics platforms require you to move all of that into a warehouse before you can analyze it. Knowi connects directly to your sources, joins data across systems in real time, and keeps everything inside your infrastructure.
Direct EHR Connectivity
Connect to Epic Clarity, Cerner Millennium, FHIR R4 APIs, HL7 feeds, and clinical databases. No middleware, no ETL pipelines. Query your EHR data where it lives.
Cross-Source Data Joins
Blend EHR data with claims, billing, scheduling, and IoT device feeds in a single query. No staging tables, no intermediate warehouse. Data stays in your systems.
Private AI for Healthcare
Knowi's AI engine runs entirely inside your deployment. Ask questions in plain English across patient, claims, and operational data. No data sent to OpenAI or any third-party LLM.
Real-Time Dashboards
Monitor patient flow, readmission rates, claims denials, and operational KPIs in real time. Dashboards update as source data changes. No manual refresh, no nightly batch jobs.
Self-Service for Clinical Teams
Operations managers, clinical directors, and compliance officers build their own reports without depending on IT. Natural language queries let non-technical staff ask "show readmission rates by facility last quarter" and get instant results.
Full Compliance Stack
On-prem deployment (Docker, Kubernetes, bare metal). Role-based and row-level security. Audit logging. Data encrypted in transit and at rest. Signed BAA for all healthcare customers.
Infrastructure built for PHI.
Every layer of Knowi's infrastructure is designed for protected health information from the ground up.
Encryption at every layer
Patient data is encrypted at rest and in transit. Direct source queries mean PHI is never copied or staged outside your environment.
AES-256 at rest • TLS 1.2+ in transitAccess controls and audit logs
Role-based access, row-level security, SSO/SAML, and MFA. Every query and access event is logged for compliance reporting.
RBAC • SAML/SSO • Full audit trailPrivate AI, no third-party exposure
Knowi runs its own AI infrastructure. Your data never touches OpenAI, Google, or any external LLM.
On-prem availableWhy Knowi
Built for healthcare. Not bolted on.
Tableau and Power BI were built for general BI. Knowi was built for environments like yours: EHRs, FHIR, MongoDB, multi-source joins, and full compliance out of the box.
| Capability | Knowi | Tableau | Power BI | Sisense |
|---|---|---|---|---|
| HIPAA compliant | Yes | Yes | Yes | Yes |
| Signed BAA | Yes | Yes | Via Microsoft | On request |
| On-premises deployment | Yes (Docker, K8s, bare metal) | Yes (Tableau Server) | Gateway only | Yes |
| Native EHR/FHIR connectivity | Yes (Epic, Cerner, FHIR R4) | Via connectors | Via connectors | Via connectors |
| Native NoSQL queries (MongoDB, Elasticsearch) | Yes, natively | No, requires ETL | No, requires ETL | Requires ElastiCube |
| Cross-source joins without warehouse | Yes | No | No | No |
| Private AI (no third-party LLMs) | Yes | No | Copilot uses Azure OpenAI | No |
| White-label embedding | Full (CSS-level control) | Limited | Power BI Embedded | Yes |
| Time to first dashboard | Days to weeks | Weeks to months | Weeks | Weeks to months |
| Data warehouse required | No | Yes (extract/warehouse) | Yes (import mode) | Yes (ElastiCube) |
No ETL, no warehouse
Knowi queries your clinical databases directly. You skip the 3-6 month warehouse project and the compliance risk of copying PHI into another system.
Private AI stays private
Other platforms route AI features through OpenAI or Azure. Knowi's AI engine runs inside your infrastructure. Your patient data never touches a third-party service.
Live in weeks, not quarters
Most healthcare teams have their first dashboards running within 2-3 weeks. No data modeling phase, no semantic layer to build. Connect, query, visualize.
Customer Success
Healthcare organizations using Knowi
Alteas Health: operational analytics across physician clinics
Alteas Health, a concierge medicine provider, uses Knowi to give operations managers visibility into scheduling, patient flow, resource allocation, and performance metrics across their physician clinics. Clinical teams build their own reports without depending on IT.
Read the full storyNinePatch: embedded analytics for hospital platforms
NinePatch builds mobile healthcare applications and chose Knowi over Sisense to deliver SSO-embedded analytics to hospitals. Their hospital clients create visualizations, monitor patient data metrics, and access real-time insights inside NinePatch's white-labeled interface, powered by MongoDB.
See Knowi with your healthcare data
Schedule a 30-minute demo. We will connect to your data sources live and show you dashboards on your actual data.
Schedule Demo