Platform

HOUSTON, TX
U.S.A. M.F.G.

Reprogramming
Possibility.
MLOps

Industries have suffered long enough. The false promises. The complex, impractical technologies that under-deliver and break the bank before they even get deployed.

It’s time to escape

the oppression.

SEC — 1
About Us

About Us

It’s time to escape
the oppression.
SEC — 1

We are here to finally deliver Operational AI.

We are prepared to flash-forward everything.

We are Teknoir. This is our Platform.

Large enterprises, including industrials, have widely proclaimed their excitement for digital transformation.

This is typically followed by spending large amounts on R&D initiatives, staffing, and forming strategic partnerships with big tech companies and hardware vendors. These massive upfront investments aren’t practical and rarely deliver ROI. We need a better approach. We need Accessible AI.

SEC — 2

Deploying and maintaining AI solutions
is complex, expensive and requires organizational change. These factors do not pair well together.

Section

1/3

Industrial Operations

Industrial operations are often in remote and extreme environments, but today’s AI solutions require cloud access with robust network connectivity, making them impractical.

Section

2/3

AI Solution Architects

AI solution architects often overlook cybersecurity, regulatory, and data sovereignty considerations, leaving organizations at risk and understandably hesitant.

Section

3/3

Generative AI

A promising technology on its own, but lacks the ability to interface with the physical world. It also tends to hallucinate, rendering it ineffective when accuracy is needed.

Current AI offerings overstep their boundaries attempting to do too much when most companies have already invested millions in best-in-class IoT, automation, systems of systems, and other costly infrastructure that shouldn’t be replaced just because of the advent of a new technology.

AIoT TECH

Instead, the AI should interface and work in harmony with this legacy IT/OT and not create yet another disparate technology. Why replace it when you can connect to it with an API?

INDEX:

SECTION 03 LOADED ****

COMMAND:

/EXE:> EXTRACT FROM [TEKNOIR RESOURCE FOLDER INTERNAL]

SEC — 3

Four factors to consider, with
inherent optionality built in.
SEC — 3

Because simplicity is the only way
to efficiently process complexity.

We believe in plug-and-play.
Not rip-and-replace.

An end-to-end platform from the sensor to the dashboard with tight integration to existing IT/OT infrastructure — camera and sensor networks, SCADA systems, process historians, and ERP/MES.

Legacy
infrastructure
revived. ▶︎

The common vision presented for AI usually involves an architecture built on new infrastructure, with "smart" IoT devices all working harmoniously to provide abundant, real-time data to the AI system, down to the last data source in a distributed environment. While this paints an elegant picture, it doesn't represent reality for most companies that have spent millions of dollars over the decades amassing OT infrastructure designed with a specific goal for monitoring and control.

Rightfully so, organizations have a low propensity to have the desire or budget to replace their legacy technology with a modern counterpart. In most cases, this tech is reliable and performant in the areas it was initially intended for. However, it can be challenging to integrate with other disparate systems, especially AI, relying on low-latency data streams. This is why, at Teknoir, we take an integration-first approach for AI deployments rather than rip-and-replace.

The Teknoir platform has been designed to deploy into our customers' existing architecture with minimal effort to connect to legacy for seamless connectivity to valuable data sources located at the farthest edge nested deep within operations. Whether it is an older analog CCTV camera or sensors on packaged vendor equipment, the Teknoir platform simplifies the discovery and connection to these devices, minimizing hardware and installation costs.

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Learn about our philosophy of moving more parts without more moving parts.

Click To Expand

▶︎

Deep Learning

Edge + MLOPs

User Experience

SEC — 4

Deep Learning

Machine Intelligence

Digitally optimize
all operations.

Understanding deep learning and machine learning functionality within The Teknoir Platform.

Computer Vision Predictive AI continuous learning Multimodal AI

Computer Vision

1/4

Eyes and Ears
that Never Close.

Object Detection, Classification, Segmentation,
Tracking, & Human Pose Estimation

The Teknoir Platform acts as your ever-alert sentinel, providing immediate insights about operations. Our vision-based AI models are trained to monitor your machinery, keep your workers safe, provide quality control and assurance, and enhance security and surveillance more reliably than their human counterparts. We’re able to do all this at the edge, so you don’t need to rely on the cloud for interpretation and action.

Computer Vision

Eyes and Ears
that Never Close.

Object Detection, Classification, Segmentation,
Tracking, & Human Pose Estimation

1/4

Predictive AI

Technology for the
Day After Tomorrow.

Predictive AI refers to the use of machine learning algorithms and data analysis techniques to forecast future outcomes based on historical data patterns. It involves the creation of deep learning models that can make informed predictions, such as predicting customer behavior or equipment failures.

Anomaly detection, on the other hand, is a specialized application of AI that focuses on identifying unusual or unexpected patterns or outliers within data. Anomalies can be indicative of errors, quality defects, security breaches, or emerging issues that require immediate attention.

Both are crucial to equipment maintenance, production optimization, fault detection, and quality control, as well as equally invaluable in harnessing the power of artificial intelligence for better decision making and problem solving. The biggest challenge for any AI application is access to abundant data that can be used to train models. Our platform’s ability to access and ingest dark data at the edge from IoT sensors, cameras, SCADA, and process historians unlocks model development possibilities that were previously unobtainium.

Time-Series Analysis and
Anomalous Behavior Detection

2/4

Continual Learning

All Systems are Sentient and
Operating at Full Capacity.

Industrial machines are exposed to challenging conditions. The slightest variance can become consequential over time. These highly dynamic environments require AI models to automatically update in order to improve accuracy and change with their environment while providing detailed feedback about the variances. This is continuous machine learning.

Imagine any engine or electric-motor-driven equipment. The health and reliability of this machine can vary over time due to various reasons. Our Predictive AI, using vibration and temperature data, can identify future failures and other critical events, providing advance notice for the equipment owner to perform maintenance before there is a failure. Because the model is able to continuously and intelligently learn from varying conditions, it understands when conditions deviate from normal status without any additional context of the process or equipment physics.

The Teknoir Platform offers a novel approach to continual learning by harnessing the power of multiple devices meshed together at the edge, thereby unlocking an abundance of Operational AI use cases that were previously impossible.

Machine Learning At the Edge

3/4

Multimodal AI

Linking Perceptions
from Every Source.

Until recently, most AI deployments have been one-dimensional, focusing on a single modality, typically in either the time-series or vision domain.

But, what if there was a way to combine the visual heuristics that your cameras see with the predictive analytics from your sensors? Fusing different types of models together would afford you the ability to visually verify a future event or that a mitigation or remediation has taken place.

This also makes it possible to create complex models that combine the dark data at the edge from IoT sensors and process data with visual and audio data to address all sorts of interesting use cases across industry domains, something that was unheard of until now. Yes, the Teknoir Platform can do it because our multimodal AI Apps combine varying complex operational data to output more accurate determinations, more insightful conclusions and make more precise predictions about real-world situations.

Industries

4/4

SEC — 5

Edge+MLOps

AI Workflow

Our
Platform

AI Workflow

End-to-end platform for building and deploying AI applications, providing immediate speed-to-value for your enterprise.

Sec. 01 — ML Laboratory

Sec. 02 — The Grid

Sec. 03 — App Arcade

Sec. 04 — Console

Sec. 05 — Observatory

MODULE

Operational
AI Workflow

Personas

Build AI apps using pre-coded blocks or bring your own models.

Multimodal Models - video, audio, time series

Deploy continuous and federated learning pipelines

Data Scientist

ML Engineer

Integrator

Train and evaluate models

Configure, not code app using pre-built pipelines

Run local AI inference data at edge

Data Scientist

Business User

Partner

Publish models and apps to online store for distribution across the enterprise

Use/Buy Teknoir or partner apps and models

Data Scientist

ML Engineer

Business User

Partner

Connect existing OT infrastructure

Process data on the edge

Deploy apps and AI models

Over-the-air orchestration of apps, models, and hardware

Business User

Data Scientist

Partner

Act on actionable, predictive insights

Push notifications

Use Marvin, our natural language interface (eg. ChatGPT)

Monitor surveillance wall

ML Engineer

Data Scientist

Partner

Sec. 01 — ML Labs

MODULE

→ Evaluate

Operational
AI Workflow

Build or bring your own conventional and multimodal GenAI models

Train, finetune, and evaluate models

Optimize continual and federated learning pipelines

Personas

Data Scientist

ML Engineer

Integrator

Sec. 02 — The Grid

MODULE

→ Create

Operational
AI Workflow

Train and evaluate models

Configure, not code app using pre-built pipelines

Run local AI inference data at edge

Personas

Data Scientist

Business User

Partner

Sec. 03 — App Arcade

MODULE

→ Create

Operational
AI Workflow

Publish models and apps to online store for distribution across the enterprise

Use/Buy Teknoir or partner apps and models

Personas

Data Scientist

ML Engineer

Business User

Partner

Sec. 04 — Console

MODULE

→ Deploy

Operational
AI Workflow

Connect existing OT infrastructure

Process data on the edge

Deploy apps and AI models

Over-the-air orchestration of apps, models, and hardware

Personas

Business User

Data Scientist

Partner

Sec. 05 — Observatory

MODULE

→ Monitor

Operational
AI Workflow

Act on actionable, predictive insights

Push notifications

Use Marvin, our natural language interface (eg. ChatGPT)

Monitor surveillance wall

Personas

ML Engineer

Data Scientist

Partner

Machine Learning

The brains
behind the brawn.

Introducing our intuitive tools that get Operational AI working for you.

Select Operational AI ▶︎

Orchestration Engine (TOE)

▶︎

▶︎ ▶︎

1/8

The Grid

2/8

ML Laboratory

3/8

Label Studio

4/8

Console

5/8

Utilities

6/8

Platform
Security

7/8

Dark Data
Vault

8/8

Orchestration
Engine (TOE)

(A) Summary

The Grid is the Teknoir Platform’s low-code, graphically intuitive developer environment where clusters of code are visually represented in the way information flows through a computer. This coding canvas serves as a powerful development environment for everything from building AI applications and scheduling training pipelines to deploying and orchestrating apps at the edge.

(B) Features

Low/no code visual development environment.
Build, deploy and manage custom code.
Allows multiple AI Apps to be deployed to all devices in colony.
Power users can orchestrate new apps with “bring your own AI models” and build app flows using our built-in low-code nodes for custom functions and logics.
Identical grid dev environments in both the cloud and at the edge for true deploy and test MLOps approach.

(A) Summary

The Teknoir Platform’s ML Laboratory provides data scientists and machine learning engineers with an interactive interface to all data and machine learning services and best-of-breed tools for DS and MLOps, such as Jupyter notebooks and other software tools for monitoring model drift. Thus enabling a complete data science and MLOps lifecycle.

(B) Features

Interactive interface for all data and machine learning services.
Best-of-breed tools enabling a complete data science lifecycle.
Continual learning of models to maintain peak accuracy.
Ability to add and deploy any machine learning algorithm and making it available as a microservice through a standard RESTful API.

(A) Summary

Label Studio, within the Teknoir Platform, streamlines the process of annotating time-series, image, or video data with a graphical, task-driven interface that can be used by your internal workforce or third-party annotation teams. We are constantly updating the Label Studio with the latest annotation methods, such as Segment Anything Model (SAM) to further reduce the manual effort that goes into the labeling process.

(B) Features

Label data collaboratively from anywhere in the world, on any device.
Mislabeled data is corrected and model training pipelines are automatically updated.
Improved model performance and accuracy.

(A) Summary

The Console is the helm of the Teknoir Platform. This serves as the hub for connecting and navigating all hardware and software components, including notifications, user permissions, device provisioning, and dozens of other administrative functions.

(B) Features

Configurable, robust set of integrated notification alerts.
Role-based user access control.
Remote device fleet health monitoring.
Continual code deployment.
Firmware updates and security patching across peripherals and edge devices.
Rich audit trails that provide end-to-end traceability.
Detailed permissions and activity logging.
Metadata tagging, filtering and searching.

(A) Summary

Utilities are small software applications that operate in harmony with larger software applications and hardware to enable specific functionality. For example, automatic discovery cameras and other IP-based peripherals, geolocation data for onboard GPS, 4G/5G connectivity, backups and data storage, etc.

(B) Features

Catalog.
Real-time monitoring of state and health of any devices in the field.
Secure remote SSH connections with encrypted data transfer.
Perform live bulk updates/versioning.
Automatic peripheral detection of existing cameras for easy device onboarding.

(A) Summary

A secure platform architecture is paramount throughout the entire tech stack. At Teknoir, we take a secure-by- design approach to everything we build and integrate.

(B) Features

Enhanced Security Across the Network — Service identity and security features combined with encryption of data in transit and at rest, there is a significantly strengthened security posture. This ensures that all communication and data, whether moving between services or stored, are protected against unauthorized access and breaches.

Improved Data Integrity and Privacy — Encrypting data in transit and at rest safeguards sensitive information, maintaining its integrity and confidentiality. Fine-grained access control further enhances privacy by tightly regulating who can access which services and under what conditions, essential for compliance with data protection regulations.
Comprehensive Monitoring and Reliable Service Communication — monitoring and traffic management capabilities, alongside encrypted data flows, offer a reliable and observable network environment. This leads to quicker identification and response to security incidents and ensures dependable communication across cloud and edge environments, crucial for maintaining continuous service availability.

(A) Summary

Data persistence of unified streaming data across all peripheral types requires a multiplicity of data stores depending on the data and anticipated access and usage analysis (both on the devices and aggregated in the cloud). The Teknoir Platform uses relational databases to support transactions and complex queries, and key-value stores for data such as telemetry/vibration requiring low-latency reads and writes.

The Teknoir Platform embodies a sophisticated approach to data management, emphasizing the use of the most appropriate data store for specific data types and usage scenarios. Our platform integrates a diverse array of databases to cater to varied needs: relational databases for handling transactions and complex queries, key-value stores for efficient processing of telemetry and vibration data requiring low-latency operations, and Blob (object) storage for practically limitless storage capacity. Additionally, we utilize column-oriented databases for high-speed, real-time analytics; time series databases for insightful visualizations and dashboarding; graph databases for managing complex, interconnected data; and vector databases for conducting similarity searches in high-dimensional spaces. This multi-faceted, strategic approach ensures that the Teknoir Platform is adept at managing an extensive range of data challenges, providing a robust and versatile solution for contemporary data persistence needs.

(B) Features

Multi-Database Integration: Supports relational, key-value, Blob, column-oriented, time series, graph, and vector databases for diverse data types and applications.
Endless Storage with Blob Storage: Ideal for managing large, unstructured datasets, including multimedia files and logs.
Real-Time Analytics: Facilitates quick processing and aggregation of large data volumes with column-oriented databases.
Advanced Visualization and Dashboarding: Utilizes time series databases for effective monitoring
Complex Relationship Mapping: Employs graph databases for efficient handling and querying of interconnected data.
High-Dimensional Data Handling: Integrates vector databases for similarity searches essential in AI and machine learning applications.
Scalable and Flexible Data Management: Tailored database selection ensures optimal performance and scalability for various data challenges.

(A) Summary

A hardware-agnostic operating system for edge computing devices capable of data ingestion, app orchestration, real-time control, AI inferencing, and secure mesh communication with other devices.

(B) Features

Containerization architecture for true DevOps deployment and management.
Lightweight by design to optimize CPU resources and GPU hardware acceleration.
Secure by design utilizing device encryption and SSH tunneling.
On-device Grid development environment that replicates the form and function of the cloud Grid.
Built-in device utilities for monitoring hardware and software health related to CPU & GPU usage, available storage, memory usage, network bandwidth, and hardware temperatures.

Select Operational AI ▶︎

Orchestration Engine (TOE)

▶︎

SEC — 6

User Experience

No-Code UX

Nothing is
uncontrollable.

We are maniacal about delivering a beautiful and intuitive user experience across all products, hardware, and software. It’s in our DNA. Because the best tech stack in the world is nothing without its equal in product design.

More importantly, we understand the importance of designing a UX tailored for various user personas - frontline workers versus business users. We get it and design it, thanks to our deep roots and hands-on knowledge in the industries we support.

Sec - 07

HI-FIDELITY AI

Meet Marvin

What kind of AI would it be
if we didn’t give it a personality?

Meet Marvin, your company’s intelligent assistant. Unlike the other paranoid and depressed robot with the same name, this Marvin never complains, needs a break, or provides you with useless information.

As Generative AI advances at an unprecedented pace, we are constantly evaluating ways to enhance Marvin’s intelligence with these capabilities.

COMMAND:

[RUN]***MARVIN.EXE***

Features ▶︎

FUTURE TECH

Natural language processing for easily prompting and querying the platform

Analysis of time-series data, images, and videos to generate insights customized in the appropriate format for any type of user persona

Automated data labeling and segmentation

FUTURE TECH

INDEX:

PLATFORM TEST LOADED ***

COMMAND:

/EXE:> EXTRACT FROM [TEKNOIR RESOURCE POC KIT]

SECTION 007

MACHINE LEARNING

PLATFORM TEST

Stop reading
and start testing.

SEC — 7

Test the Teknoir^™ Platform.

Put our platform to the test deployed in your environment with your data. We’ll send you a trial hardware kit with access to our suite of cloud components, all on our dime. It’s really that easy and we’re confident you’ll love it.

Request a free trial

Demo Here

Reprogramming Possibility. MLOps

It’s time to escape the oppression. SEC — 1 About Us

It’s time to escape the oppression. SEC — 1

Large enterprises, including industrials, have widely proclaimed their excitement for digital transformation.

Four factors to consider, with inherent optionality built in. SEC — 3

Because simplicity is the only way to efficiently process complexity.

We believe in plug-and-play. Not rip-and-replace.

Deep Learning

Digitally optimize all operations.

Computer Vision

Computer Vision

Predictive AI

Continual Learning

Multimodal AI

Edge+MLOps

The brains behind the brawn.

The Grid

ML Laboratory

Label Studio

Console

Utilities

Platform Security

Dark Data Vault

Orchestration Engine (TOE)

User Experience

Nothing is uncontrollable.

Meet Marvin

Connect With Us

Reprogramming
Possibility.
MLOps

It’s time to escape

the oppression.

SEC — 1
About Us

It’s time to escape
the oppression.
SEC — 1

Four factors to consider, with
inherent optionality built in.
SEC — 3

Because simplicity is the only way
to efficiently process complexity.

We believe in plug-and-play.
Not rip-and-replace.

Digitally optimize
all operations.

The brains
behind the brawn.

Platform
Security

Dark Data
Vault

Orchestration
Engine (TOE)

Nothing is
uncontrollable.