You repeat an earlier decision.
As a conversation or project grows, earlier instructions may be summarized, overlooked or left out of the next request. NSGX connects recorded decisions to the work that needs them.
NSGX · Where intelligence keeps its place.
Help AI find what matters. Help people see how it connects.
NSGX organizes complex information into connected structures that people can inspect and AI can use. Explore software and data, trace decisions to their sources, and evaluate whether more focused retrieval can reduce the cost of your AI work.
- Structure
- Explore connected information
- Retrieval
- Trace the supporting source
- Evaluation
- Evaluate on your workload
The problem
Your information keeps growing. Working with it should get easier.
This is the problem NSGX is built to address: important information gets buried while people and AI spend more effort finding it again. An inspectable, connected structure makes that information easier to follow and use.
A change has hidden consequences.
A file, service or data source can affect many other parts of a system. NSGX makes those relationships explorable, from the whole project down to a specific record.
An answer needs a source.
An answer is harder to trust when you cannot see what supports it. NSGX connects information to source references so you can inspect the evidence and its relevance.
One simple example
Find the reason. Keep the connection.
Imagine coming back to a project after a week away. You should not have to reread every conversation to understand one decision.
The current plan
Launch on 18 June
Changed from 4 June
The decision
Wait for approval
Decision recorded on 28 May
The source
Approval is due 12 June; allow time for review.
Project note · 28 May
Why did the launch date move?
The answer is not the entire project history. It is the decision, the reason for it and the record that supports it.
Illustrative records and a scripted answer—not a live AI response or benchmark. The same three records stay visible throughout.
One foundation
The same information can help people and AI.
People need to understand how things connect. AI applications need relevant information to do their next task. NSGX brings these needs together; Weav brings selected capabilities into your AI workflow.
Core platformAn organized structure for complex information, with tools to inspect relationships and evaluate source-backed retrieval. Build on the platform or discuss licensing it for your own product.
- See the relationships between records
- Explore large structures one level at a time
- Retrieve context with supporting sources
- Evaluate quality, cost and integration fit
BetaPick up the work, not the pieces.
Chat · build · inspect · model · make
- Use selected NSGX tools from a supported AI app
- Keep recorded project decisions connected
- Inspect the information behind the work
- Confirm client support during beta onboarding
Meet Weav Powered by NSGX
Products
Choose the tool for the work you want to do.
Explore a system, build a new one, connect your AI workflow or integrate NSGX into your own product. These are ways to use the same underlying technology.
- Web app
Inspect
Studio
See how a project fits together, inspect a specific part and compare what changed. Move from the whole system to the detail that needs attention.
Learn more - Inside Studio
Build
Forge
Build a system with blocks and connections inside Studio, then inspect what you have made. Keep design and review in the same workspace.
Learn more - Free
Try
Visualizer
Start with a supported repository or graph file and explore its structure. See what is connected before choosing a larger workflow.
Learn more - Beta
Use
Weav
Bring selected NSGX capabilities into a supported AI app. Keep recorded decisions connected, inspect the work and explore idea-to-3D workflows.
Learn more - SDK · API · CLI
Integrate
Developers
Add an inspectable spatial view to your product. For memory and retrieval integration, start with a scoped enterprise evaluation.
Learn more
A closer look
Connected information. A useful next step.
You do not need to understand a graph engine to see the purpose: find the relevant record, follow its source and continue the work with better context.
01
Organize the information
Keep records and their relationships together so a large project can be explored in manageable parts.
A little more detail
NSG stands for Nested Spatial Graphs. Records are represented as nodes, relationships connect them, and nested layers organize the structure. The visual view makes that structure inspectable.
02
Keep the source in reach
Connect a decision or claim to the record that supports it, so a person can check what the AI is working from.
A little more detail
Source references provide traceability. Their presence is not proof that a source is correct, complete or current; those are separate checks.
03
Bring relevant context to the task
Give an AI application a way to request useful information instead of always passing it a large history.
A little more detail
Memory and retrieval integrations are evaluated for the workload, access rules and budget. Public integration details describe inputs and outputs without exposing proprietary engine mechanics.
04
Check what changed
Inspect the updated structure and compare task results before deciding that the new approach is better.
A little more detail
Retrieval quality, final-answer quality, total cost and completion time are measured separately. The supported inputs and update behavior depend on the workflow.
Proof
Know what improved—and what did not.
A convincing result needs a task, a baseline and a clear measure. These are the questions an NSGX evaluation is designed to answer.
Find the right information
Measure whether the required sources were found and how much irrelevant information came with them. Then check the final answer separately.
Define the data boundaries
Agree what can be accessed, stored, sent to a model or shared. Check the actual workflow before using sensitive information.
Inspect the result
Trace the records behind a result. Keep examples, measured tests and customer evaluations clearly distinguished.
Count the full cost
Compare model processing, preparation, storage and retrieval—not just the size of one prompt. Measure completed work as well as speed.
Who it's for
Built for the systems that have outgrown the whiteboard.
- AI agentsHelp later tasks find earlier decisions and requirements.
- CodebasesUnderstand what no one can hold in their head.
- InfrastructureSee which services depend on a change.
- Data systemsFind connected records and trace information to its source.
- PipelinesFollow the steps and find where work gets stuck.
For your business
Working with a large AI or data project?
Tell us what your system needs to remember, retrieve, or make easier to understand. Start with a focused evaluation against the way you work today.