Visual Centric Workflow
See first, then decide
Unique visual-supported workflow approaching the nature of a programming-based data science workflow to optimize the human-data interaction
Sensor-Data Analytics
Cope industrial complexity -
process sensor data sufficiently
Considering deep scientific-methods with strong capabilities in signal processing & multi-domain Feature Engineering tailored for industrial processes.
End-to-End Coverage
More than just Analytics
All-in-one Platform covering the whole AI workflow. From Idea to Business case, from Raw Data to trained AI Models, from Product Ownership to running AI Apps.
Role-Based Pricing
Consuming vs. Building

Consumers benefit from running AI Apps. Reach large-scale access with fair Consumer vs. Builder pricing model.
Loosely-coupled Architecture
Interact, not interfere

Import and Export possibilities after every step. Transfer your data, models, analytics pipelines into your own technology territory - traceable and re-usable.
Open-source support
Leveraged by community
Technology boost and increased capabilities with the use of community-driven Open-Source Tech Stack (Tensorflow, Keras, XGBoost, Apache Nifi…)
From Raw Data to running AI Apps…
... Build, deploy & maintain analytics pipelines
Infrastructure
innoSEP’s Platform runs on-premise or in the cloud, supporting Amazon Web Services (AWS), Google Cloud Platform (GCP), Oracle Cloud, Microsoft Azure... It contains a fully containerized deployment structure that supports both popular container management systems like Kubernetes and a standalone deployment - deployable wherever, whenever
Elastic Computing and Job Management
Leveraging the power of Kubernetes, innoSEP’s Platform offers an efficient, scalable and loosely coupled compute engine. innoSEP integrates modern technologies like Apache Spark, Apache Nifi or Apache Kafka, in addition to our own state-of-the-art AI algorithms framework, to allow Analytics pipelines take full advantage of your hardware. Manage, monitor and configure each task on the innoSEP AI Platform as a job and be in full control of your own AI pipeline – From long-running, resource intensive calculations to real time stream processing
Project Administration and Governance
innoSEP’s Platform provide full permission control throughout all project phases. Assign roles from project responsible, builder, domain expert and consumer across the enterprise to guarantee successful project implementation. Decide who can read, process and change data. Manage pipelines and apps in all stages – fully organized from data access to productive Analytics Apps.
innoSEP translates a programming-based analytics
process into no-code, enriches it with visual elements…
... and guides customers through the entire workflow
with following end-to-end product modules - from data
ingestion to running analytics pipelines in Kubernetes.
Organize and prepare your Projects
Create and manage Projects including full permission control and User set-up
- Create and organize Projects
- Define User’s access, roles and rights
- Multi-roles – Project Responsible, Builder, Domain Expert, Computer Scientist and Consumer
Create data connections and flows in no-code
In innoSEP’s Connect module you can manage multi-lateral data pipelines between common Database systems (SQL, Kafka, MongoDB etc.) in few clicks – Ingest relevant data into the exploratory building stage for hands-on data processing
- Empowered by Apache Nifi as professional data flow controller for data consumption, real-time data flow and synchronization
- Fully flexible connection modes with buffering & streaming capability
- Data importing tool for a manual upload (csv, xlsx, tdms, mdf4, dat, wav etc.)
- Big data & partial loading capability
Multi-Domain Visualization and step-wise Data Engineering
Holistic operation panels from idea to trained data models – in innoSEP’s Explore module you can explore your data, execute operations in no code – fully guided in in a visual-centric Workflow for improved human-data interactions
- Seven pre-configured dashboards for multi-domain data exploration (transient, spectral, correlation, counting, descriptive statistics…)
- Multi-functional build-in functions in the areas of Data Wrangling, Data Enrichment, Feature Engineering and Data Modeling
- Diverse repository of Machine & Deep Learning algorithms using state-of the arts python-based and Spark libraries (Ski-Kit Learn, Tensorflow, Keras, XGBoost…)
- Considers multiple deep-tech methods & signal processing (e.g. filtering, spectral analysis, counting methods…)
Build, Manage & Maintain user-defined Analytics Workflows
Build custom Analytics stories in innoSEP’s Story module through linking relevant operations and visualization steps from exploratory building stage – transparent, collaborative and traceable through visual expression and version control
- Easy-to-maintain analytics pipelines
- Collaborative processing
- Full Transparency of workflow
- Improved interface between explorative steps and automatized flows
Design business Apps based on AI Pipelines
Create Apps based on Stories, define relevant data node, set notification, or build dashboards through fully flexible selection of visual outputs. In innoSEP’s App module you can collaborate as a Builder with Consumer and seamlessly close the gap between development and production stage.
- Design Customer-specific AI Apps
- Build Dashboards & Notifications system in few clicks
- Fully managed & no-code App building
- Return calculated data nodes back to origin systems
Deploy, Consume and Maintain AI Apps
In innoSEP’s Pipeline module production ready apps can be packaged and deployed as containerized applications through an easy-to-use interface. Either feed data back into the explore mode for further processing or connect apps directly to your existing systems and gain benefits of AI in production.
- Live dashboards with real-time feedback
- Fully containerized AI Pipelines – supported by Kubernetes
- Export apps and integrate them into existing MLOps solutions (Kubeflow, MLFlow, …)
- Performance monitoring & management of AI models in production
Collaboration
Organize, optimize and adapt pipelines simply and collaboratively – visual illustration of pipelines and platform executions allows fully centralized project flow from all perspectives
Productivity
Focus on what you are best in – In building stage you can connect your analytics pipelines with a custom dashboards and deploy an app in a few clicks.
Transparency
Every data processing and visualization step in exploratory building stage is traceable, re-usable und fully transparent – understand, adapt and consume operation settings, data input and results with meaningful plots and tables everywhere
Accessibility
Gain access to your data and understandability fincreaseor Non-Coders – innoSEP’s unique visual-centric processing workflow delivers insights for business analyst after every step