Start with the question
Model only the entities and relationships needed to answer a real operational question.
The Agency
Knowledge Graph Systems
Devzilla builds operational knowledge graphs, graph-backed agent memory, and durable company knowledge systems with explicit provenance.
Direct answer
When should a company use a knowledge graph?
A knowledge graph is useful when the relationships among people, systems, assets, events, and decisions matter as much as the records themselves. Devzilla uses graphs when teams need durable identity, provenance, connected retrieval, explainable paths, or shared memory that cannot be represented reliably as isolated documents and embeddings.
When it fits
Situations that justify the work
- Important entities have inconsistent names and identifiers across operational systems.
- Users need to follow relationships and provenance rather than retrieve a similar paragraph.
- Agent memory needs durable facts, permissions, and source links instead of an opaque transcript.
- Institutional knowledge disappears across documents, tickets, conversations, and staff changes.
Outputs
What the client receives
- Entity and relationship models tied to concrete operational questions.
- Ingestion, identity resolution, provenance, and update pipelines.
- Graph queries, APIs, interfaces, and agent retrieval patterns.
- Governance for ownership, permissions, conflicting facts, and lifecycle changes.
Approach
How Devzilla approaches the system
Preserve provenance
Keep the source, time, and ownership of facts visible so conflicts can be examined rather than silently merged.
Resolve identity deliberately
Define how records become the same entity and how uncertain matches are reviewed.
Expose useful paths
Build queries and interfaces that help people and agents understand why an answer is connected to the source data.
FAQ
Frequently asked questions
Is a vector database a knowledge graph?
No. Vector search finds semantically similar content. A knowledge graph represents explicit entities and relationships. They can work together when a system needs both fuzzy retrieval and connected facts.
Can a knowledge graph support agent memory?
Yes. A graph can preserve entities, events, permissions, and provenance across sessions, giving an agent durable structured memory instead of relying only on conversation history.
Do we need to model the entire company first?
No. Begin with one valuable operational question and the smallest graph that can answer it. Expand the model only when new use cases justify the additional maintenance.
Does this match the hard part?
Tell us what the system must do, what it touches, and what failure costs.
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