Neoby Nura Labs

the behavioral memory layer

Not just another context store. Neo captures the DNA of how your team actually builds to give every agent persistent, model-agnostic memory across your entire stack.

SkillMCP ServerDashboard
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pattern detected
decision captured
GitHub
Linear
Notion
Agent traces
·GitHub·Linear·Notion·Agent traces·MCP server·Claude Code·Cursor·Codex·Copilot CLI·Windsurf·GitHub·Linear·Notion·Agent traces·MCP server·Claude Code·Cursor·Codex·Copilot CLI·Windsurf

The problem

Every AI starts
from year zero.

Your team spends years developing patterns, resolving recurring errors, and making architectural decisions. None of that knowledge reaches any AI agent automatically.

01

Configuration fragmentation

Claude Code uses CLAUDE.md. Cursor uses .cursorrules. Codex uses AGENTS.md. Every tool switch means rewriting context from scratch.

02

Redundant tokens in production

Agents re-explore decisions already made in every new session. At scale, that's a cost that compounds with every interaction.

03

Org knowledge that exists nowhere

No system captures how your specific team operates: patterns, recurring mistakes, reusable components. In a way that's model-agnostic, auto-updating, and tool-independent.

What is Neo

A persistent context layer
for your entire org

Neo captures how your company operates in code, and makes that knowledge available to every AI tool your team uses. Without training, without configuration, without lock-in.

Auto-captures everything

Every PR merged, code review comment, commit message, and agent trace feeds the graph automatically.

No training, no fine-tuning

Not a model. Not RAG. A knowledge graph that grows with each real event from your team. No epochs, no GPU.

One connection, every tool

Connect via MCP once. Claude Code, Cursor, Codex, Copilot CLI. Every tool your team uses receives context from the same graph.

Model-agnostic by design

Models improve constantly. Your organizational graph stays relevant because no model knows how your specific team works.

Organizational knowledge layer
live
PatternsErrorsDecisionsComponentsGitHubcommits · PRs · reviewsLineartickets · decisionsNotiondocs · architectureAgent tracestool calls · errorsClaude CodeCursorCodexWindsurfSOURCESKNOWLEDGE GRAPHAVAILABLE VIAFig. 1.1 · Neo data flow

How it learns

Every event makes it smarter.
No training required.

PR merged

Detects the pattern. Reinforces it in the graph for the relevant module.

Code review rejects

Learns that approach doesn't apply in this codebase. Context grows more specific.

Agent tool call fails

Records that path as problematic for this organization. Prevents repeat.

Component gets reused

Increases relevance of that node. Future agents discover it before building from scratch.

Pricing

Plans that scale with you

Builder

popular
$19/month

For professional developers

14-day free trial

Knowledge nodes2,000
Sources5
Queries5,000/mo
Dream CycleWeekly
DashboardFull
Seats1
SupportEmail
Self-hosted

Team

$49/seat/mo

For growing teams

Knowledge nodes10,000
Sources25
Queries25,000/mo
Dream CycleDaily
DashboardFull
SeatsUp to 25
SupportPriority
Self-hosted

Business

$149/seat/mo

For scaling organizations

Knowledge nodesUnlimited
SourcesUnlimited
QueriesUnlimited
Dream CycleCustom
DashboardFull + analytics
SeatsUp to 50
SupportDedicated
Self-hosted

Enterprise

Custom

For large organizations

Knowledge nodesUnlimited
SourcesUnlimited
QueriesUnlimited
Dream CycleCustom
DashboardFull + analytics
SeatsUnlimited
SupportDedicated onboarding
Self-hosted

Who uses it

Built for every scale

Developers

You switch between Claude Code, Cursor, and Codex constantly. Neo makes your working context follow you. No rewriting, no reconfiguring.

Engineering teams

popular

Your team builds patterns and learns from mistakes. Today that knowledge lives in people's heads. Neo captures it and makes it available to every AI the team uses.

AI infrastructure

Production agents spend tokens re-exploring decisions already made. Neo eliminates that redundancy. The savings compound with usage.

vs. alternatives

Not another RAG wrapper

Augment CodeHyperspellTraditional RAGNeo
What it learnsStatic codebasePersonal user dataDocumentsOrg behavior (live)
Tool-agnosticn/a
Learns over timePartialPersonal only
No fine-tuning
Works in productionn/a

FAQ

Common questions

Get started

Give your AI the context it needs to truly understand your codebase.

Connect your development tools. Works in minutes. No training required.

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