Integration Middleware for AI

In 2020 our team started building, a distributed database capable of storing and featurizing any form of multimedia in the most efficient way possible. This research required looking at the problem similar to the math for streaming points into a video game renderer, and also required representing the data. We brought together the best of both worlds, in a math process we call GAVINĀ® short for General Artificially Vectorized Intelligence Normals. The discovery of this process has made possible. It is efficient and provides all with creative equity.

With a simple and intuitive suite of visual tools, makes it easy to connect existing tools and services. Combine any type of multimedia to form AI Models that maintain oversight of an organization and its infrastructure. provides all users:
  • Free access to share data and speed up intense procressing jobs
  • Advanced file compression, saving money on long-term storage
  • Your data, your devices, your privacy. Export cloud data anytime

Available for Mac, Linux, and Windows.
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Administration and self service
easy administration of accounts by setting access types, inviting users including observers, and setting the root access for each account to compartmentalize access where needed. Self Service of integration middleware in many cases makes it as simple as click to integrate, in other cases a simple form will active advanced integrations instantaneously extracting valuable information and routing data from devices and yielding decisions.

Normalize system and application data
Combine and observe any type of multimedia
normalize and map log, system, application, and platform data into a unified enterprise service bus either in the cloud, on premise, or within hybrid distributed computing environments.

Observability of events, objects, and distributed processing
observe the structure and important datapoints associated with events, objects, queues, and process ETL/ELT pipelines at the edge.

Manage event and transactional workflows
Configure complex sequences and track transactions
Compose conditional events, and sequences with a drag-and-drop studio that empowers everyone up and down and organization to leverage the power of automation.

Performance and AI driven analytics
Utilize historical data and enterprise integration middleware data to construct benchmarks and understand where applications, networks, and microservices bottleneck. Get to the root cause easily. Deploy AI to predicatively analyze events and drive enhanced analytics.

Convert ESB data into AI models using AutoML
Compress large sets using automatic machine learning and retrain with transer learning
convert historical data collected from logs, streams, events, and databases into highly compressed foundational models that can recall logical organizational data as inferences in real-time both in the cloud, and at the edge in State-of-the-art speed.

Orchestrate data for the next generation

Peer beyond state of the art is powered by standard-setting innovations validated by Researchers, Engineers, and IT Professionals from:

Managed Services Self Service
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Easily connect data sources to enterprise service bus

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