The platform
The 18-month data project
becomes a signup.
Noded collapses the customer-data project — discovery, cataloguing, integration, MDM — from 12–18 months to hours, collapses the multi-million-dollar cost to nearly zero, and puts the most valuable data in your company directly into the hands of the people who carry the number.
Connect your tools and the whole pipeline — association, ranking, enrichment, caching — runs automatically, at ingest.
Production in days. Not fiscal years.
No consultants, no stewards, nothing to host. From $20/seat — priced like a productivity tool, because it lands like one.
Reading and asking are always free.
carry the number
AEs, AMs, and CSMs self-serve the full account story — the most valuable data in the company, in the hands that need it most. No ticket. No sponsor. No waiting.
Land with one seat. Spread with the team.
The how
The next generation of middleware associates unstructured data with structured data.
Agents fail for a reason IT already knows: enterprise data is a mess. The current generation of middleware moves structured records between systems. Noded is the next: ingestion chaining™ reads the action layer — the calls, threads, tickets, and forwards where work actually happens — and associates every unstructured event with its structured anchors the moment it happens. Context from the data that got it done — without the year-long cleanup project.
The emails, calls, tickets, and threads where the work actually happened — associated with their structured anchors at ingest. Dead ends get probed, marked, and released.
Warehouse tables and CRM fields — a historical artifact of what someone remembered to log. Cleaning it is a forever war.
Same enterprise, two graphs. The action layer assembles a clean, current Context Graph in hours. The storage layer grinds through its pipeline for months — and delivers a tangle of duplicates that was stale on arrival.
The short version
A central nervous system for your enterprise data.
Ingestion chaining™
We read the action layer, not the storage layer.
Your ontology reveals itself in how people work — not in your schemas. Noded follows the work to find the high-impact, high-intention data.
See it work ↓Data consistency
Semantic caching, wired to your data.
Answers are derived once, served from cache, and invalidated the moment your data changes — same question, same answer, on every surface.
See it work ↓Data enrichment
Bidirectional by design.
As conversations happen, we continuously improve the data in your business systems — Salesforce, HubSpot, wherever the field lives.
See it work ↓Agent as Operator
The model decides. The harness does the work.
Noded agents build deterministic workflows and run the model on top — dialed from human-in-the-loop to fully automated as trust builds.
See it work ↓One MCP layer
No servers to spin up or maintain.
A single governed endpoint exposes the data foundation. You define what’s exposed, who it’s exposed to, and how it’s described.
See it work ↓One agent identity
Not one login per app.
A singular identity for agent workloads, mapped to the underlying identity in each system — with tools explicitly provisioned to it.
See it work ↓The architecture
Agents on top. Your data underneath. Noded in between.
All six pieces in one picture: agent surfaces come and go on top; a consolidated MCP layer and one identity per agent govern the door; the Context Graph and its harnesses do the work in the middle — and your data stays exactly where it lives today.
Graph
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HHow it works · 01
Noded Ingestion chaining™: we read the action layer, not the storage layer.
Everyone else profiles the storage layer — schemas, tables, foreign keys, where data sits. Noded reads the action layer instead — the forwards, mentions, escalations, and edits — because how your business uses data says far more about your ontology than where it’s stored. The high-impact, high-intention data reveals itself through the work — so that’s the data your agents see:
Noded walks the chain — ticket to email to thread to issue to opportunity to plan — and the relationships write themselves. No schema mapping, no ontology project, no brittle foreign keys: every interaction is an edge, and the trail of real work becomes the map. And the chain is built from pointers — the records stay in the systems that own them.
Three signals decide what gets pulled in:
Every touch is an edge — a forward, a mention, a status change, even a read. Records the work keeps reaching for climb in rank, like PageRank for your enterprise, and earn their way into the graph.
Importance fades unless it’s renewed. A record nobody touches for a business cycle falls out of the active chain — so the graph tracks living work, never the archive.
Noded reads the sentence around every mention. “Blocked by NOD-231” pulls data in; “closing as duplicate” keeps it out. Dead ends and stale docs never enter the chain.
How it works · 02
Consistent answers. Current data. A fraction of the tokens.
Agents re-derive the same answers from raw data over and over — expensive, and every derivation is a new chance to drift. Noded caches results at the semantic layer and invalidates them the moment the underlying data changes. Every agent, every surface, every run reasons from the same current answer.
The cache isn’t a snapshot that goes stale — it’s wired to the graph. When the data landscape shifts, the answers shift with it. Nothing is re-asked; nothing is out of date.
How it works · 03
Data enrichment: the value flows both ways.
We don’t just identify the high-impact, high-quality data — we enrich it, using the structured and unstructured data across your enterprise. As conversations happen, the records in Salesforce, HubSpot, and your other business systems continuously improve.
Graph
Write-backs are opt-in, attributed, and reviewable — by default Noded reads and changes nothing. When you turn enrichment on, it lands the way your admins would want it to. The longer Noded runs, the better your systems of record get.
Sovereignty
We leave your data where it is.
A nervous system doesn’t swallow the body. Your data stays in the systems that own it — lower risk for you, and data sovereignty stays yours.
What crosses the line is a reference, not the record — plus just enough context to stay fast. Disconnect Noded tomorrow and your data is exactly where it always was: home.
Not wholesale ingestion
Ingestion chaining™ keeps pointers to where the data lives — plus just enough context to stay fast. Salesforce remains the system of record. So does everything else.
We don’t change your data
Reads are the default posture. Every write-back — enrichment included — is opt-in, attributed, and reviewable. Nothing changes until you say so.
We never train on your data
Your data trains nothing — not our models, not anyone else’s. It works for you, and only for you. More on security →
How it works · 04
Agent as Operator.
Most AI agents are the workflow — one shaky prompt away from breaking. Noded agents operate one. Each learns by building deterministic workflows that become its harness, then runs the model on top: the model decides, the harness does the work.
How to think, plan & act. One free-form note, with full graph-query access to look anything up.
Only what it needs. Scoped record types & functions — query, draft email, create task, per-permission.
Shared note of tasks, pinned to the account. The memory it reads & rewrites on every run.
Lessons that stick. “Keep emails to the top 3.” Injected into the skill, built up over time.
Edit it, tick tasks off, reassign — the operator reads the changes and adapts on its next run. Agent and team, one plan.
Testing stays simple: are the triggers firing accurately, and are the tools working? Everything else is just editing the skill until you’re happy — and dialing from human-in-the-loop to fully automated as trust builds.
How it works · 05
One MCP layer for your entire stack. Zero servers to run.
The data layer is solid — now expose it. An MCP server per app means auth sprawl, hundreds of vendor-described tools, and an agent guessing what your fields mean. Noded is one consolidated layer over the nervous system — you define the data that’s exposed, who it’s exposed to, and how it’s described to your agents.
Fewer tools, described in your terms, shown only to the agents that need them — reliability goes up because the surface area goes down.
Three things you control at this layer:
You decide which records, fields, and documents cross the line — per source, per field. What isn’t exposed doesn’t exist as far as any agent is concerned.
Exposure is scoped to the agent, not the org. The renewals agent sees renewals data; the support copilot sees tickets. No agent sees everything by default.
Tool and field descriptions are yours to write — so your ontology understands the complexities of your enterprise data, not a vendor’s generic idea of it. “ACV” means what you mean.
How it works · 06
One identity per agent. Not one login per app.
Rather than the agent logging into each system individually, it carries a single identity that maps to the underlying identity in each app. Its tools are explicitly provisioned — reducing tool-invocation confusion, and keeping agents agnostic to your infrastructure.
Read the graph. Scoped to the accounts this agent owns — not the whole book.
Draft, never send. Output lands as a draft for a human to review.
Make work visible. Tasks created under the agent’s identity — auditable, reassignable.
Doesn’t exist here. A tool that isn’t provisioned can’t be confused, coerced, or called.
Each app still enforces its own permissions and keeps its own audit trail. Swap the model, swap the framework, retire the agent — the identity and its scopes stay put. Agents stay agnostic to your infrastructure.
Who this is for
Built for the people who answer for it.
For the CIO
Nothing new to run: no MCP servers to deploy, patch, or monitor. One agent identity that maps onto the access model you already govern — every action lands in the app’s own audit trail, under the app’s own permissions. Data stays where it lives, write-backs are opt-in, and your data never trains a model.
You define the exposure. The apps keep enforcing it.
For the AI leader
Agent strategies survive contact with reality when the data layer is solid. Scoped tools cut invocation confusion; cached prompts cut hallucination drift; and because agents are agnostic to the infrastructure, you can swap models and frameworks as the market moves — without rewiring a thing.
Bet on the data. Stay flexible on the agents.
The proof
The numbers an AI leader checks first.
From teams running Noded under their agents today — and every one of them is downstream of ingestion chaining™.
The bottom line
Your agents come and go.
Your data is your most valuable asset.
The reason your agents are failing isn’t the model — it’s the mess underneath. Fix the data once, and every agent you ever deploy inherits the fix.