Turn Raw IoT Data Into Real-Time Intelligence
Connect directly to InfluxDB, MongoDB, TimescaleDB, Cassandra, and any REST API. Blend IoT sensor data with relational sources on the fly. Build live dashboards your team can act on - no ETL, no data movement, no waiting.
TRUSTED BY TEAMS IN FINTECH, HEALTHCARE, MEDIA AND SAAS
How It Works
From IoT data to dashboard in three steps
Skip the months-long ETL setup. Knowi connects directly to your IoT infrastructure and gets you to insights in minutes.
Connect natively
Plug directly into InfluxDB, MongoDB, TimescaleDB, Cassandra, Elasticsearch, REST APIs, and dozens more. No drivers to install, no data to move. Knowi queries your IoT data where it lives.
Blend any data source
Join IoT sensor data with relational databases, CRMs, ERPs, or any REST API in a single query. All join types supported. Just specify the join key - Knowi handles the rest across SQL and NoSQL boundaries.
Visualize and embed
Build real-time dashboards with 30+ visualization types. Embed them directly into your IoT applications with full white-label support. Your brand, your data, your customer experience.
Capabilities
Built for the complexity of IoT data
IoT data is high-volume, high-velocity, and spread across dozens of systems. Knowi is purpose-built to handle it.
Real-time data streaming
Ingest and visualize streaming sensor data as it arrives. Set refresh intervals down to seconds for live operational monitoring across your entire device fleet.
Anomaly detection and alerts
Automatically detect outliers in device telemetry and trigger alerts via email, Slack, or webhook. Catch equipment failures and safety hazards before they escalate.
Natural language querying
Operations teams ask questions in plain English- show me devices with temperature above 90 in the last hour, and get instant visualizations. No SQL required.
Cross-source data joins
Combine time-series sensor data with customer records, maintenance logs, or ERP data in a single query. Join across NoSQL and SQL boundaries without moving data to a warehouse first.
Embedded analytics / white-label
Embed dashboards directly into your IoT product with iFrame, JavaScript SDK, or API. Full white-label support lets you deliver analytics under your own brand to customers and partners.
Integrated machine learning
Apply built-in ML models for predictive maintenance, demand forecasting, and classification - directly on your IoT data. No separate ML infrastructure needed.
Dashboard Examples
See how teams use Knowi for IoT
Monitor operations, reduce downtime, and make faster decisions with real-time IoT dashboards.
IoT Analytics Dashboard
Give operators a single pane of glass to monitor device capacity, throughput, and health in real time. Built-in anomaly detection flags irregular patterns — temperature spikes, traffic surges — so your team acts before issues become incidents.
See the dashboard
Fleet Management Dashboard
Track vehicle status, fuel consumption, and maintenance schedules across your fleet. Combine GPS telemetry with maintenance records to predict when servicing is needed — reducing unplanned downtime and extending asset life.
See the dashboard
Smart Cities Dashboard
Combine data from traffic sensors, cameras, and bike-share systems into one view. Optimize signal timing, identify high-risk intersections, and measure the impact of infrastructure changes — all in real time.
See the dashboardWhy Knowi
What other IoT analytics tools can't do
Most BI tools require you to warehouse your data first. Knowi connects directly to your IoT infrastructure and gives your team AI, anomaly detection, and cross-source analytics out of the box.
Faster time-to-insight
Eliminate months of ETL pipeline setup. Connect to your IoT data sources and build your first dashboard in minutes, not quarters. No data engineering required.
Other tools require a warehouse. Knowi doesn't.
Any data source. No warehouse required.
Connect directly to time-series databases, NoSQL, SQL, REST APIs, and flat files. Join across sources on the fly — no ETL pipeline, no staging layer, no waiting for data engineering.
Your IoT data doesn't all live in Snowflake. Your analytics tool shouldn't require it to.
Self-service for every team
Operations managers, field engineers, and executives explore IoT data using natural language search and drag-and-drop dashboards — without waiting on data teams or writing queries.
Your operations team shouldn't need SQL to understand their own data.
Monetize with embedded analytics
Turn analytics into a revenue stream. Embed white-labeled Knowi dashboards into your IoT product and deliver data insights directly to your customers and partners.
Stop giving away insights. Start charging for them.
See how teams monitor IoT operations with Knowi
Real companies using Knowi to unify IoT data and act on it in real time
How intlx Solutions powers intlx360 with Knowi
Replaced fragmented monitoring tools and slow dashboards with a unified operational intelligence platform. intlx360 connects alarms, incidents, assets, and analytics across telecom operations in a single view.
Verizon ThingSpace Intelligence
Knowi powers the embedded analytics layer inside Verizon's ThingSpace IoT platform, delivering real-time device monitoring, usage analytics, and anomaly detection across one of the world's largest connected device ecosystems.
Data Connectivity
Connect to everything. Join across anything.
Most IoT analytics tools require a warehouse. Knowi connects directly to your operational databases, APIs, and time-series stores.
Cross-source joins, no ETL required
Combine data from any of the above on the fly. A single dashboard widget can pull from InfluxDB and PostgreSQL in the same query. No warehouse. No staging tables. No waiting for a data pipeline.
Frequently Asked Questions about IoT Analytics
IoT data is distributed and disparate in nature. This means that to enable real-time IoT data streaming and analytics, you must have an efficient method of data ingestion or integration. The ingestion step usually involves automated data collection across different data sources, aggregating everything into a data warehouse or data lake. Depending on the nature of the data collected, the design of the ingestion process and storage will vary widely.
In data transformation, you merge or join the collected data as needed and run any additional operations to get it into the optimal format.
Gartner has predicted that by early in the 2020s, that more than half of major new business entities will incorporate some elements of IoT in their systems. The complexity of the vast volumes of data generated through these IoT systems creates a need for deep data analytics tools and skillsets. However, IoT data tends to be far messier than common business data, incorporating large streaming volumes of data that are often geospatial in nature. With such complex data, gleaning any insights or understanding from it will require an IoT specific analytics solution.
IoT analytics can be used to simplify that enormous volume of data into actionable insights and understandable dashboards.
See IoT analytics with your own data
Connect your IoT data source or send us a sample dataset. We'll build a working dashboard in your first call.