Naboo vs Modern Relay
Modern Relay's Omnigraph is a git-style versioned graph DB primitive. Naboo ships the complete Reasoning Layer on top - Decision Graph, deep ETL, and a Forward Deployed Agent.
The thesis in one paragraph
Modern Relay's Omnigraph is an open-source, git-style versioned graph database - nodes, edges, branch, and merge as first-class semantics. It's the most architecturally aligned primitive in the market: a serious substrate a serious team could build a Reasoning Layer on top of. Naboo is the Reasoning Layer: Decision Graph with decisions as first-class nodes, deep ETL across code / tickets / PRs / Slack / internal services, native RBAC at retrieval, and a Forward Deployed Agent who ships it end-to-end in 2-4 weeks. Modern Relay gives you the building blocks. Naboo gives you the finished layer.
Side by side
Category
Naboo
Reasoning Layer (complete Decision Graph + ETL + agent surface)
Modern Relay
Open-source Omnigraph - a git-style versioned graph database primitive
Primary abstraction
Naboo
Decisions as first-class nodes - owners, triggers, blockers, evidence
Modern Relay
Nodes + edges with branch, merge, and version semantics
What you get out of the box
Naboo
A Decision Graph shipped end-to-end by a Forward Deployed Agent
Modern Relay
A graph DB you build your own schema and pipelines on top of
Enterprise ETL depth
Naboo
Live joins across code / tickets / PRs / Slack / internal services, encoded by Naboo
Modern Relay
You write the ingestion; the database stores whatever you land in it
Query interface for agents
Naboo
GraphQL + MCP - returns structured chains of decisions
Modern Relay
Graph query language - the agent (or you) interprets the traversal result
Permission model
Naboo
Native RBAC at retrieval, mirrored from source ACLs
Modern Relay
Application-level - you enforce it around the DB
Deployment
Naboo
On-prem or VPC, zero data egress, enterprise-grade
Modern Relay
Self-hosted (open-source) - operate it yourself
Primary buyer
Naboo
Enterprise R&D and Platform leaders wanting agents in production
Modern Relay
Infrastructure and platform engineering teams building custom graph products
Time to value
Naboo
2-4 weeks to a production-grade Decision Graph via Forward Deployed Agent
Modern Relay
Weeks to months - you're building your own schema, ingestion, and query layer
Compose with each other?
Naboo
Yes - Modern Relay could theoretically be a storage layer, but Naboo is complete without it
Modern Relay
Yes - a team could build a Decision-Graph-like product on Omnigraph over months
| Feature | Naboo | Modern Relay |
|---|---|---|
| Category | Reasoning Layer (complete Decision Graph + ETL + agent surface) | Open-source Omnigraph - a git-style versioned graph database primitive |
| Primary abstraction | Decisions as first-class nodes - owners, triggers, blockers, evidence | Nodes + edges with branch, merge, and version semantics |
| What you get out of the box | A Decision Graph shipped end-to-end by a Forward Deployed Agent | A graph DB you build your own schema and pipelines on top of |
| Enterprise ETL depth | Live joins across code / tickets / PRs / Slack / internal services, encoded by Naboo | You write the ingestion; the database stores whatever you land in it |
| Query interface for agents | GraphQL + MCP - returns structured chains of decisions | Graph query language - the agent (or you) interprets the traversal result |
| Permission model | Native RBAC at retrieval, mirrored from source ACLs | Application-level - you enforce it around the DB |
| Deployment | On-prem or VPC, zero data egress, enterprise-grade | Self-hosted (open-source) - operate it yourself |
| Primary buyer | Enterprise R&D and Platform leaders wanting agents in production | Infrastructure and platform engineering teams building custom graph products |
| Time to value | 2-4 weeks to a production-grade Decision Graph via Forward Deployed Agent | Weeks to months - you're building your own schema, ingestion, and query layer |
| Compose with each other? | Yes - Modern Relay could theoretically be a storage layer, but Naboo is complete without it | Yes - a team could build a Decision-Graph-like product on Omnigraph over months |
FAQ
Is Modern Relay a direct Naboo competitor?
Architecturally the closest of any competitor. Modern Relay's Omnigraph is a git-style versioned graph database - nodes, edges, branch, merge - designed as a shared graph substrate for AI agents. It's a well-designed primitive. But Modern Relay ships you the database; you build the schema, the ingestion, the joins, the query surface, and the deployment. Naboo ships the whole Reasoning Layer: Decision Graph, ETL depth, agent surface, and a Forward Deployed Agent who encodes it all in 2-4 weeks. Different level of the stack.
Isn't a versioned graph DB with branch/merge exactly what agents need?
It's a useful primitive, but by itself it's not what agents need. What agents need is a queryable model of your company's decisions, owners, triggers, and blockers - along with evidence pulled live from source systems - accessible via a stable schema they can rely on. A raw graph DB gives you the primitive to store all that; a Reasoning Layer gives you the model, the pipelines, the ACL enforcement, and the query surface already built. If you're a large infra team that wants to build your own Reasoning Layer, Modern Relay is an interesting substrate. If you want the answer in 2-4 weeks, that's Naboo's job.
What does the Forward Deployed Agent actually change?
It closes the gap between 'a graph DB is available' and 'my agents produce correct answers across five source systems.' A Naboo FDA - a specialist in ETL and data science - sits with your tech lead and encodes the joins your team knows but never wrote down: how a branch name links a ticket to a PR to a feature flag to an internal service that carries the live on/off state. The result is a Decision Graph tuned to your org's private definitions, not a generic schema. With Modern Relay, all of that is a build project on your side.
Could a team build Naboo on top of Modern Relay?
Theoretically, yes - given a large infra team, a data engineering team, an agent integration team, and 6-12 months. You'd be reimplementing the Decision Graph model, the ETL joins across code / tickets / PRs / Slack / internal services, source-ACL mirroring at retrieval, the GraphQL + MCP surface, and the Forward Deployed Agent engagement. That's what Naboo does as a product, staffed by Naboo. Buy vs. build applies here the way it applies to any infrastructure category.
When is Modern Relay the right choice?
When you're building infrastructure for a broader set of graph-based use cases, need branch/merge semantics as a first-class primitive, and want an open-source base you control end-to-end. Great for infra platform teams, custom knowledge graph products, and R&D on agent-native storage models. If your goal is shipping AI agents that reason across your enterprise stack, Naboo is the shorter path.
Can I run both?
In principle - Naboo doesn't preclude a graph DB substrate underneath. In practice, most enterprises deploying Naboo don't stand up a separate Omnigraph cluster; the Reasoning Layer ships with its own execution model. If you already run Modern Relay for other reasons, we're happy to talk about how they'd coexist.
Related reading
Reasoning Layer for Enterprise AI Agents
Definition, architecture, and the two tiers - Topic Graph and Decision Graph.
Read moreDefinitionWhat is a Decision Graph for AI Agents?
Decisions as first-class nodes - owners, triggers, blockers, evidence. The primitive AI agents need to act.
Read moreHow-toHow to Build a Decision Graph
Seven concrete steps from elicitation to a queryable graph. Two to four weeks via Forward Deployed Agent.
Read moreCFO briefHow to Reduce LLM Token Costs
Don't meter the waste, cut the cause. Reasoning Layer vs observability and caching, compared.
Read moreGuideImprove AI Agent Accuracy
Accuracy is upstream of evals. Four causes of enterprise AI inaccuracy and how a Reasoning Layer fixes them.
Read moreArchitectureConnect Enterprise Data Sources
Live joins vs stale copies. Warehouse, ETL, knowledge graphs, and Reasoning Layer compared.
Read moreGuideOvercome GenAI Hallucinations
Hallucinations are a context-handoff problem, not a model problem. Four causes, one upstream fix.
Read moreROIHow Naboo Saves Cost
Five places Naboo cuts cost in enterprise AI deployments. Four-minute explainer video.
Read moreHubCompare Naboo
Every category enterprise AI buyers weigh against the Reasoning Layer - in one place.
Read moreComparisonNaboo vs Helicone
Reasoning Layer cuts the cause; Helicone measures the waste. Composable.
Read moreComparisonNaboo vs Langfuse
Different layers. Langfuse versions + traces; Naboo grounds the agent.
Read moreComparisonNaboo vs LlamaIndex
RAG framework vs Reasoning Layer. When to use each.
Read moreComparisonNaboo vs LangChain
Orchestration vs substrate. Compose them.
Read moreComparisonNaboo vs Cognee
Open-source agent memory vs enterprise Reasoning Layer. Different primitives, different jobs.
Read moreComparisonNaboo vs Hyperspell
Cloud 'Company Brain' API vs enterprise Reasoning Layer with on-prem, RBAC, and FDA.
Read moreBackgroundWhy retrieval was the wrong foundation
How enterprise AI agents got built on RAG, why it falls short, and what a reasoning layer fixes.
Read moreComparisonNaboo vs RAG
Retrieval vs reasoning - head-to-head benchmarks, architecture, and when to use each.
Read moreComparisonNaboo vs Glean
Enterprise search vs reasoning layer - when each fits.
Read moreConceptAI Search vs Reasoning Layer
Search returns links; the reasoning layer returns the chain. When to use which.
Read moreCategoryAgent Memory vs Reasoning Layer
Memory recalls what the agent saw. A Reasoning Layer returns what the company decided. Different primitives, different jobs.
Read moreCase studyGlobal-E case study
How Global-E (NASDAQ: GLBE) gave AI agents secure access to customer data.
Read moreComparisonCompare alternatives
Naboo vs other enterprise AI agent infrastructure platforms.
Read moreA graph DB isn't a Reasoning Layer.
If you want to ship agents that reason across your enterprise stack in weeks - not build the layer yourself over months - talk to us.