Honeycomb Architecture

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Problem Statement

The absence of Agentic AI adoption across both the commercial and government sectors is fundamentally due to lack of confidence & reliability. The three main contributing factors are:

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1. Sub-optimal LLM or Model Performance

2. Absence of Security

3. Absence of Information Control

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The first factor regarding model performance is progressively diminishing and is comprised of a saturated market of hyperscalers and large tech companies. Recent trends suggest models will surpass the theoretical threshold to satisfy performance requirements.

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The second and third factors are arguably more important for wide-scale adoption; the ability to deploy agentic solutions at various levels of security & the ability to strictly define guardrails for information underpin the very infrastructure agents and their tools must operate within. Even more so, no company has satisfied this need and very few are attempting to do so.

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The Solution

This is where Honeycomb AI comes in. With our Honeycomb architecture, users may intuitively create, secure, monitor, and deploy predefined or custom agentic solutions.

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With minimal overhead, this architecture is perfect for all single or multi-agent applications. Whether accessing sensitive information, managing external connections, or interacting with other agents, be confident that your application can handle malicious or unexpected events.