Explore the Third Wave of AI
with thingsTHINKING

Humans are way better than computers when it comes to common sense and understanding natural language. thingsTHINKING brings common sense to computers.
Many tasks today can only be handled by humans since working with natural language requires contextual information and the ability to understanding the subject matter. Our technology combines real-world knowledge with statistical information (deep learning, etc.) to get to the actual meaning of natural language - this is what DARPA calls the Third Wave of AI.
thingsTHINKING understands relevant and useful information from your unstructured data not unlike a human. This accelerates finding things, making contextual decisions, and - as we humans like to say - doing the job right. Think of us as a sidekick, a forklift for your brain.

Founding Member of the Federal Association of Artificial Intelligence

As winner of the prestigious new.New Festival "Industry Disruptor" Award, we are proud to being recognized for one of the leading NLP/NLU/Semantics AI platforms in 2018.

Check out the press coverage at code_n directly or at Frankfurter Allgemeine Zeitung (FAZ).

"Words exist because of meaning. Once you've gotten
the meaning, you can forget
the words."

Zhuangzi

The Shift from Pure Training to More Understanding

There are two technologies to establish AI: Bottom Up AI training (machine learns from examples) or Top Down AI teaching (man explains to machine).
Many times, AI cannot be trained automatically because of a lack of training data (/-quality). This is where we combine both technologies to make AI understand.

Different Layers of Micro Services

Applications can be built on domain-specific services. They leverage and orchestrate the basic services from the platform and the domain.

The Platform Micro Services

POS Tagging
Part-Of-Speech tagging.

Semantic Generalization
Provides access to higher-level semantic information.

Semantic Model Similarity
Finds semantic differences and similarities.

NLP Pipeline
Tokenizing, base-form, stemming, ...

Semantic Model Persistence
Stores models for later reference and re-use.

Semantic Concept Similarity
Compares the similarity to other concepts.

Language Detection
Detects language of a given text.

Semantic Model Creator
Generates a semantic model from text input.

Semantic Sanity Check
Checks for sanity according to (world) knowledge.

Semantic Collection Creator
Collects semantic models in specific domains.

Requirement Rule Execution
Detects linguistic flaws in requirements, patents, and legal texts.

Custom Integration
Standard integration into the leading RPA systems.

THE FOUNDERS

Dr. Sven J.
Körner

Chief Executive Officer

I combine and implement research results into products with our customers and partners.

Dr. Mathias
Landhäußer

Chief Scientific Officer

I connect tT with research and handle our university relations. Also I spearhead our latest research advancements and prototypes.

Abdelmalik
El Guesaoui

Chief Product Officer

I am responsible for our product management and -marketing as well as business development and customer relations.

Georg A.
Müller

Chief Technology Officer

I am responsible for our technology and software architecture.

Explore the Third Wave of AI
with thingsTHINKING