What Ekkono Solutions does

Ekkono Solutions AB is a privately held Swedish embedded edge AI software company founded in 2016 in Varberg, Sweden, with additional offices in Borås and Gothenburg. The technology is grounded in more than seven years of machine learning research at the University of Borås by CTO and co-founder Rikard König (PhD). Ekkono provides C and C++ software libraries that enable incremental machine learning on streaming sensor data directly on constrained edge devices, with a footprint small enough to run on hardware ranging from industrial PLCs and gateways down to the Arduino Pro Micro (2KB RAM) and even the Commodore 64. The company's products comprise the Ekkono SDK (containing Primer for model development, Edge for full inference and incremental training, Crystal for microcontrollers, and Spectral for signal processing), the Synthesis federated learning platform for fleet-wide model lifecycle management, and Ekkono Studio, a JupyterLab-based cloud development environment.

Ekkono monetizes through multi-year license agreements with product OEMs that embed its software into their products, complemented by a solution provider partnership with Etteplan and a long-standing technology partnership with Infineon (since 2019) optimizing the SDK for AURIX TC3x and TC4x microcontrollers. Named customers span industrial automation and automotive, including Volvo, Atlas Copco, Alfa Laval, Danfoss, ebmpapst, Husqvarna, Siemens, and Siemens Energy, with documented use cases such as condition monitoring, predictive maintenance, sensorless fault detection, gas burner tuning, and performance optimization.

The company employs approximately 23 people and is led by CEO Patrik Durvik (appointed March 2025; previously senior roles at Autodesk and Hexagon) and Chairwoman Petra Sundström (PhD, Stockholm University; Managing Director of TRATON Charging Solutions). Other co-founders Jon Lindén (CMO) and Anders Alneng (VP Sales) remain active. Strategic shareholder HMS Networks invested in June 2026, joining prior funding from the European Innovation Council (€2.5M grant) and earlier venture rounds. Total disclosed funding to date is approximately $8.5M.

Name

Ekkono Solutions

Legal name

Ekkono Solutions AB

Website

https://ekkono.ai

Company type

Private

Founded year

2016

Operating status

Operating

Headcount range

11–50 employees

Short description

Ekkono Solutions is a Swedish embedded edge AI software company founded in 2016 that provides C/C++ machine learning libraries enabling incremental learning on constrained edge devices, serving industrial automation, automotive, and smart infrastructure OEMs through multi-year software license agreements.

Ownership category

akta.pro rank

Product category

Edge AI Software

NAICS

Computer Systems Design Services (541512)

SIC

Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

On-Device Inference Runtimes & SDKs (mobile/embedded) (HDAAAJAB)

akta.pro secondary industries

Federated Learning & On-Device Personalization (HDAAAJAG), Edge AI Deployment, Orchestration & OTA Model Updates (HDAAAJAI)

Keywords

• Edge AI software
• Machine learning SDK
• Federated learning platform
• Predictive maintenance tools
• Embedded ML inference

Headquarters

HQ city

Varberg

HQ country

Sweden

HQ region

Europe

Offices3 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure

Revenue model

1. Software License Agreements: Multi-year license agreements for Edge AI software, sold to product OEMs for embedding in their products
2. SDK Licensing: Software Development Kit licensing for model generation, optimization, evaluation and implementation

Pricing tiers

Go-to-market motion2 records

Distribution channels3 records

Marketing channels6 records

Core offering

Ekkono Solutions develops embedded Edge AI software that runs machine learning onboard physical products using real-time sensor data. Its core offering is the Ekkono SDK (containing Primer, Edge, Crystal, and Spectral sub-components) for incremental learning on constrained edge devices, complemented by the Synthesis federated learning platform and the Ekkono Studio cloud development environment.

Product overview

Ekkono Solutions provides an embedded Edge AI software platform centered on its core Ekkono SDK, which is complemented by the Synthesis federated learning platform and Ekkono Studio development environment. The SDK is a comprehensive toolbox containing four specialized internal products: Ekkono Primer (model development and training), Ekkono Edge (full-featured inference and incremental training for edge devices), Ekkono Crystal (lightweight library for microcontrollers), and Ekkono Spectral (signal processing tools). Together they enable incremental machine learning on streaming sensor data directly at the edge, supporting predictive analytics, anomaly detection, and adaptive process automation across industrial, automotive, and building automation sectors.

Differentiator

Problem solved

Functional benefit

Brands

• Synthesis: A cutting-edge framework for federated learning that advances edge machine learning, combining sophisticated algorithms with user-friendly experiences to streamline model management, automate anomaly detection, and simplify connectivity.

Products and services

• Ekkono SDK The primary embedded Edge AI software development kit enabling machine learning to run onboard physical products. Includes four internal specialized libraries: Ekkono Primer (model development on desktop), Ekkono Edge (C++14 inference and incremental training for edge devices with a few MB of memory), Ekkono Crystal (lightweight C99 library for microcontrollers with minimal RAM), and Ekkono Spectral (signal processing tools including FFT, Wavelet, and SNR estimation). Supports streaming analytics, incremental learning, model lifecycle management, hotswappable ML models, hardware and sensor agnosticism, and no third-party dependencies.
• Synthesis A federated learning framework that aggregates models to learn collectively from what individual devices have learned locally, without exchanging raw data. Runs as microservices on a Kubernetes cluster with APIs for real-time monitoring, model management, and integration with existing infrastructure. Performs autonomous model correlation, outlier detection, and federated learning to combine learnings from individual edge devices into improved global models while preserving data privacy.
• Ekkono Studio A cloud-hosted interactive development environment based on JupyterLab for developing edge machine learning solutions. Provides LEGO-styled Python code snippets, interactive notebook tutorials, and educational videos. Models created in Studio can later be loaded into any C++ or C program for deployment on target embedded devices.

Quantifiable outcome

• Reduced NOx emissions by over 4% through automated gas burner tuning on gas turbines
• +3 more outcomes

Named customers8 records

Segments3 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability7 records

Feature10 records

Partnerships

Four partnerships are on record, tiered core and minor.

• DanfosscoreOEM/ Whitelabel/ Licensing Partner · 20 January 2026Ekkono closed a multi-year license agreement with Danfoss Power Electronics and Drives. Danfoss uses Ekkono's AI for sensorless lubrication fault detection in gearboxes using only internal signals like voltage and current in variable speed drives. The entire solution runs autonomously on embedded controllers with Ekkono's tiny footprint.
• SiemenscoreOEM/ Whitelabel/ Licensing Partner · 3 November 2025Ekkono signed a multi-year license agreement with Siemens Switzerland for Edge AI software to enhance automation and automotive features. Siemens integrates Ekkono's Edge AI to improve sustainability, efficiency, and predictive maintenance within their smart infrastructure products. This marks a major milestone for Edge AI deployment in automation.
• InfineoncoreTechnology or Integration · 20 March 2024Ekkono is an ecosystem partner of Infineon since 2019, offering an optimized SDK for AURIX TC3x and TC4x microcontrollers. This partnership enables automotive component suppliers and OEMs to create AI algorithms for embedded systems in safety-critical automotive applications. The SDK leverages advanced capabilities of AURIX for secure and safety-critical applications.
• EtteplanminorImplementation/ SI/ Consulting PartnerSolution provider partner helping implement and deploy Ekkono's Edge AI solutions to customers in industrial automation and automotive sectors.

Scale indicators5 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• Edge Impulse: Developer platform for embedded machine learning on MCUs and microprocessors, acquired by Qualcomm. Direct competitor to Ekkono SDK for industrial IoT and sensor-based edge AI use cases; overlaps strongly on predictive maintenance, anomaly detection and on-device learning.
• SensiML: AutoML toolchain for building and deploying edge AI on resource-constrained IoT devices. Closely comparable to Ekkono's Primer-to-Crystal workflow targeting microcontroller-class silicon for industrial sensor analytics.
• Latent AI: Edge AI inference optimization platform focused on model compression and efficient deployment on constrained hardware. Comparable to Ekkono's footprint-minimization and MLCM story, serving industrial and defense customers.
• Syntiant: Ultra-low-power neural decision processors for always-on edge AI on sensor data. Comparable to Ekkono Crystal on the silicon-and-software co-design axis for sensor-driven industrial and consumer devices.
• OctaiPipe: Federated learning and edge AI platform for industrial IoT deployments. Direct overlap with Ekkono Synthesis — multi-device model aggregation across industrial fleets with privacy preservation.

Emerging players

• SynSense: Neuromorphic processor and software company for ultra-low-power edge AI on sensor signals. Comparable to Ekkono's spirit of sensor-data-first inference at the extreme edge, though focused on neuromorphic silicon rather than conventional MCUs.

Broad incumbents

• Google (TensorFlow Lite / Lite Micro): Free, widely-used open-source inference runtimes for edge devices from Google. The most direct incumbent Ekkono positions against — TensorFlow Lite for microcontrollers targets MCUs but is image/DNN-centric, leaving Ekkono's sensor-data incremental learning niche.
• NVIDIA (Jetson / TAO Toolkit): Edge AI hardware plus TAO/Metropolis software stacks for industrial and automotive AI. Competes with Ekkono on industrial AI vision and analytics use cases, particularly in automotive and smart infrastructure.
• Amazon Web Services (SageMaker Edge / Panorama): Cloud-vendor edge AI platform (SageMaker Edge) and appliance (Panorama) for industrial computer vision and ML. Indirect competitor that bundles free tooling and a managed cloud backend that Ekkono customers may prefer for greenfield deployments.
• Microsoft (Azure IoT Edge / Azure Percept): Hyperscaler edge AI and IoT platform serving industrial customers. Comparable on industrial IoT and edge orchestration, but bundled with cloud rather than purpose-built for on-device incremental learning like Ekkono.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• YouTubeyoutube.com/channel/UCAcSpzSMKT4j9k3sQ0JSY7w
• Facebookfacebook.com/ekkono
• LinkedInlinkedin.com/company/ekkono-solutions-ab
• Instagraminstagram.com/ekkonosolutions
• Xx.com/ekkonosolutions

Revenue estimate

Valuation estimate

Number of profiles

Profiles5 records

Funding overview

Funding rounds6 records

Investors6 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Ekkono Solutions