Forward Deployed Engineering · AI Infrastructure
Every AI initiative you've greenlit is only as good as the customer context underneath it.
We deploy an engineer to fix that - in weeks. Sales has a copilot. CS has one. Support's piloting a third. Each one re-integrates the same CRM, the same tickets, the same calls - and reasons over a different, incomplete slice of the truth. We connect, govern, and unify your customer data into one context graph. Every agent inherits it from day one.
The problem
Every team is building its own agent. None of them share context.
IT gets pulled into every one of these projects and owns none of the outcome - until an agent hallucinates in front of a customer and the ticket lands on your desk. The standard fix is a unification project: 12–18 months, a warehouse migration, a cleanup sprint before anyone's allowed to build.
You don't have 12–18 months - and neither does the AI roadmap you already committed to the board. Noded doesn't ingest everything and clean it up first. It finds the high-intention data - the data that got deals done and kept accounts renewed - and builds the graph from that. The mess stays where it is. You get a governed, queryable context layer anyway.
What we actually deploy
Not a support engineer. Not a systems integrator.
An engineer who's done this before, embedded with your team - building the one context layer every agent, present and future, plugs into instead of re-integrating from scratch. Same crawl-walk-run methodology every time.
Connect & govern.
"One layer. One identity. Nothing new to audit."
- Customer Context Graph stood up - CRM, calls, tickets, Slack, and email through one governed MCP layer
- One identity - permissions inherited from what you already run
- No new access to manage - no new attack surface to audit
Ground your first agent.
"Fewer hallucinations, starting this week."
- Point an existing copilot at the graph - instead of raw tool access
- Curated context in - noisy-system guesswork out
- Immediate effect - reasoning over real context, not a blank prompt against raw systems
Scale without re-integrating.
"Nobody re-does the CRM integration a fourth time."
- Every new agent inherits - Claude, ChatGPT, Gemini, whatever ships next
- Same governed context - same caching, same audit trail, same scopes
- New use cases become configuration - not integration projects
Institutionalize.
"Infrastructure you own - not a vendor black box."
- The context graph becomes platform - sitting next to your identity provider and data warehouse
- Owned and extended internally - documented architecture, not one team's dependency
- Pilots graduate - one team's experiment becomes standing capability
At a glance
The whole plan on one line each.
| Phase | Theme | Outcome |
|---|---|---|
| Crawl | Connect + govern | One governed context layer, one identity |
| Walk | Ground | First agent reasoning over curated context |
| Run | Scale | Every new agent inherits - no re-integration |
| Scale | Institutionalize | Context as infrastructure you own |
Why forward deployed
Not self-serve. Not a systems integrator billing by the hour.
No data cleanup project
Works with the mess as-is. The usual 12–18 month prerequisite disappears - the graph is built from high-intention data, and the rest stays where it lives.
No new access to manage
Connects as you, governed by the permissions you already run. SOC 2 aligned. Never trains on your data. Pointers, not copies - your data stays home.
One integration, not one per team
Ends the department-by-department sprawl of every group standing up its own agent against the same systems - with its own credentials and its own blind spots.
Measured like an engineering project
Every phase closes with explicit technical success criteria - systems connected, latency, token cost, accuracy. Not vibes.
The platform underneath
Built for how IT actually evaluates this.
Noded is the governed context layer for your customer stack: one consolidated MCP layer, tools scoped per agent, one identity mapped to the permissions you already run - every answer cached, consistent, and current on every surface.
Your agents come and go. Your data is forever. Fix the context once, and every agent you ever deploy inherits the fix.
Packaged engagements
Three ways to deploy. One methodology.
Every engagement runs on crawl-walk-run - scoped so you can defend it to security and to the CFO.
A working, governed context layer, in two weeks.
For IT and data teams with two or three AI pilots stalled on data quality - and a mandate to show something real, fast.
- Governed MCP layer - across core systems: CRM, calendar, calls, Slack, tickets
- One identity - scoped permissions, full audit trail
- First agent grounded - real customer context inside two weeks
You leave with: a secured context layer your first agent can query - and proof it holds up before you scope anything bigger.
A repeatable pattern, not another pilot.
For orgs standing up a central AI or platform function - and tired of approving one-off integrations.
- Access & governance blueprint - least-privilege scopes, per agent, per team
- Ingestion chaining™ read-out - where your context comes from, documented from the action layer around your core customers
- Long-horizon agent deployed - defined with your team, built, shipped, and measured
You leave with: a repeatable pattern any team can be onboarded to - not another bespoke pilot to maintain.
The context graph as standing platform capability.
For organizations treating customer context like the identity provider and the data warehouse - permanent, owned, governed.
- Customer Context Graph architecture - documented and owned internally
- Full agent lifecycle governance - provisioning, auditing, deprecation
- Customer Fabric Certification - data quality, governance maturity, and risk, reported in a format security and the board both accept
You leave with: customer context as a platform capability - owned, governed, and extended by your team.
Software subscription priced separately - see pricing.
Accelerate and Transform close with a Customer Fabric Certification - data quality, governance maturity, and risk, reported in a format security review and the board both accept. Think of it as SOC 2 for customer context.
Get started
Sketch the architecture this week.
Thirty minutes to scope it: your systems, your priorities, what a rollout would look like. From there, we come back with an architecture mapped to your actual stack - systems connected, governance model, rollout plan. No data cleanup required to start.