Data Access via Natural Language

'Contextual Dataspaces' Resolve the Separation of Search,
Database-Type Queries, Analytics and Static Data Linking

Unique Value Proposition
VALID Positioning




VALID executes NLQs on Structured Data (Left Side).
Unstructured Data are integrated via NLP or Entity Extraction (Right Side)


"View based Publishing" provides the leanest and easiest way to publish data.
VALID reads from database views and automatically creates a graph based dataspace


The query "Andy Warhol Events in Berlin Next Year"
executed in SQL, SPARQL and NLQ


Relational vs. Fact based Data


VALID Features in Comparison
with DB-, NoSQL- and Search-Technologies


Natural Language Query EXAMPLES

The following queries comes from the art world
and connect artist, artwork, gallery and event information.

The following query comes from the VC world
and connects VCs and investors with their investments (companies +field of activity).

The following query comes from the finance world
and connects quantitative (fundamentals) and qualitative (semantiment) data.

The following query comes from the world of financial news.

Typical query from the BI world (pharma & contextual analytics inside).

The following query comes from the world of web companies.

Unique Value Proposition


Unique Features for a Whole New Grip on Your Data & Decision Making

Contextual Information Drill Down
It starts with a Semantic Search but then the User contextually "Drills" the Data further "Down" through Query & Analytics.
Information Linking Across Sources
Behind the Scenes Data are Linked Automatically on an Information/Object Level.
Contextual Analytics & "Dynamic Cubing"
Embedded and Ad-Hoc Analytics are Asked on the Currently Executes Search/Query.
Seamless between Worlds
Bridge between Structured and Unstructured Data not by NLP Search Based Linking but through Automatic Relation Extraction (ARE).
Dynamic Schema Management (NoSQL)
Publish Data and Use Contextual and Precise Queries, Joins & Aggregates (Analytics) Instantly.
Contextual Data Staging
Simultaneous Data Access by Data Architects, Developers and Users During Deployment.
Automatic Inference
Query and Analytics Capabilities which are Automatically Derived from Structural Data Characteristics
(Precise & Probabilistic).
The Distributed In-Memory Cluster runs on a Redundant Array of Inexpensive Nodes (RAIN). Use the Cloud or run it In-House.
Information Layers
Trusted (Structured) and Probabilistic (Unstructured) Data Sources are Managed in Information Layers.
Unlocking the Semantics
The System Unlocks and Retains the Semantics (The Meaning) Existing but Locked in Your Data.
This Enables Deployments in Weeks instead of Month.



Seamless Contextual Search, Query & Analytics within One Grid Engine
for "Web 3.0" Applications


Context = The New Digital Goldmine

Go Beyond

Contact Us If You Are Looking to Create Partnerships

We Control the Whole Stack
The VALID LDM Engine is Highly Integrated, Secure and Performance Oriented. No 3rd Party Libaries or Products.
New Dimensions of Speed
Unique Index Management, 100% In-Memory & Stateless Architecture and Massive Parallel Execution and Scaling Allows for Next Generation Apps.
Next Generation Apps
High Sophisticated Client Components allow for Content Streaming & Highly Interactive Apps.
Web 3.0 / Machine Learning / AI
Create new Services by using the Web like a Database and turning it into an Object Oriented Dataspace.
VALID Knowledge Revolution

Only the Context within Data & Big Data Creates Real Value

Linking of Data on the Level of Identified Objects/Records constitutes "Context"
Execution of Conditions on the Level of Objects constitutes "Queries"
Intelligent Matching of Strings within Text constitutes Semantic "Search"
Aggregations, Calculations and Operations on Object Values constitutes "Analytics"

VALID is unique in that it seamlessly integrates across these within one high performance in-memory engine.

The Unique Value Proposition