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Knowledge Graphs and Grounded AI Memory

enhanced

Rubix Code DOO

Cognee

Knowledge Graphs and Grounded AI Memory

Cognee

Seed to Series A Startup
Company Type
Berlin, Germany
Location
Team augmentation
Engagement Model
1 - 5 people
Team Size
3 - 6 Months
Duration
$21K - $50K
Budget

About

Cognee is an AI memory engine that uses knowledge graphs to give large language models reliable, grounded, auditable memory.

Challenge, approach, and impact

Unverified outputs

AI agents and analytics systems hallucinate, producing confident but unverified outputs that cannot be deployed in regulated or high-stakes environments.

Graphs Difficult to Build

Knowledge graphs at scale are difficult to build, maintain, and query efficiently, especially when the underlying data is unstructured and constantly changing.

Accessible Grounding Layer

Making the grounding layer accessible to engineering teams through a clean SDK and a reliable cloud platform, not just a research artifact.

How we built

AI & ML Solutions

Testimonials

Nikola Zivkovic, CTO @ Rubix Code DOO

Rubix Code DOO

Verified Testimonial

Working on Cognee feels like being early on something that actually matters. It is not another wrapper around an LLM. The pace is relentless in the best way. Ideas turn into shipped code within hours, and everyone around me is sharp enough to keep pushing my own thinking further.

Team structure

Client team

V M

CEO and Founder

The client stakeholders at Cognee were working closely with the team at Rubix Code DOO

Agency team

AI Developer

Production

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