Context graph, outcome engine, agents, applications, workflows, human authority, and Decision Traces.
Company · founded 2023
Enterprise decisions need evidence that survives the decision.
Nodes builds the Outcome-Based Decision Engine for decisions that shape revenue, risk, people, customers, and operations. The company began with one failure: hiring systems recorded the decision and never learned from what happened afterward.
Nodes live since 2023 · First production deployment live since January 2025
Insurance agents studied10,765Observed
Candidates scored since January 2025900,000+Observed
Legal approval at one deployment17 daysObserved
Q1 net savings, CFO-validated$1.58MObserved
What we built
A decision engine that remains accountable after execution.
Nodes combines the full enterprise AI platform surface with a customer-specific outcome loop. Agents and workflows carry out approved work. Decision Traces preserve why it happened. Measured outcomes improve what the system recommends next.
Nodes Cloud, a single-tenant customer VPC, and customer-managed on-premises infrastructure.
Historical Replay, Shadow Mode, controlled deployment, and ongoing outcome measurement.
Customer voice · on record
“Absolutely love what you guys are doing.”
Talent acquisition leader · NYSE-listed Fortune 500 · 200+ locations · live since January 2025
Expanded two quarters ahead of schedule
900,000+ candidates scored
One production-proven decision domain
Every additional domain validated separately
Five commitments
What stays true as the platform expands.
These are operating commitments. Contractual terms, audit rights, data paths, and ownership details are documented for each customer deployment.
01
Define the outcome before evaluation.
One Decision Blueprint states the decision, population, evidence, policy, authority, action, measurement window, and success bar.
02
Keep a named human in authority.
Consequential execution waits while the accountable person questions, edits, approves, delays, or declines.
03
Preserve the complete Decision Trace.
Evidence, reasoning, versions, human input, execution, and the measured result remain part of one queryable record.
04
State the deployment boundary precisely.
Nodes Cloud, customer VPC, and on-premises deployments carry different boundary terms. Private deployments can enforce zero customer production-data egress.
05
Validate every decision type separately.
Insurance talent is the current production-proven domain. Risk, customer, and operating decisions begin with their own historical replay.
Accountability
The people who build the system stay accountable for it.
Product and engineering participate in architecture, security, deployment, and evidence reviews. The customer decision owner, technical team, finance, legal, and security inspect one operating definition.
One accountable outcome, approval path, and measurement plan before validation begins.
One controlled deployment boundary, connector path, model lifecycle, and trace implementation.
One inspectable record for security, legal, finance, model-risk, and business owners.
Replay one past decision
Bring one bounded decision and the outcome you already measure.
We will map the historical systems, evidence requirements, human authority, deployment boundary, and stop conditions before the replay begins.