α
Revenue model
Finance-grade outputs. Reconcile contracts, usage, and account state into numbers the business can trust.
Product | Ontology
Decouple GTM from engineering. Turn messy production data into clean revenue data.
Ontology gives GTM teams a stable revenue, customer, and sales model even while engineering systems keep changing underneath it. psi* consumes replicated production data, normalizes contracts, usage, and account relationships, and turns that into accrued revenue, clean customer analytics, product usage, sales attribution, and compensation data.
The painful middle layer disappears. Engineering can keep shipping, while GTM stops rebuilding business logic in spreadsheets, BI models, and brittle one-off pipelines. psi* also runs a self-healing replica and refresh pipeline so the data layer stays current without turning your team into part-time data plumbers.
What the layer gives you
One clean data layer for the numbers GTM teams actually have to run the company on.
Ontology is not another BI export. It is the system that turns replicated production data into stable business data the team can operate from every day.
β
Customer model
Clean operating context. Give GTM one stable customer view without waiting on engineering cleanup.
γ
Product usage clarity
Business-facing usage. Translate raw product activity into usage the team can reason about across finance, growth, and operations.
δ
Sales model
Attribution plus comp. Keep sales attribution and compensation tied to the same underlying customer and revenue model.
Digital Twin for Revenue
Engineering systems can keep moving fast while GTM reads from one stable data layer.
Ontology consumes replicated production data, heals the pipeline when syncs drift, and publishes clean business-facing data for revenue, customer, and sales operations.
GTM decouples from engineering
Engineers can keep evolving production schemas while GTM operates from a stable business data layer.
Self-healing pipeline
Replica sync, repair, refresh, and runtime diagnostics keep the ontology current without constant manual cleanup.
Tenant-isolated data store
The system runs on bare-metal Postgres with tight access control and anonymization at replication time.
Digital Twin for Revenue
Why it changes the org
Engineering keeps shipping. GTM keeps one stable data model.
This is the organizational win. psi* removes the old split where engineering owns raw systems, BI owns fragile models, and GTM waits for someone else to explain the numbers.
Engineering systems
Product databases, search indexes, CRM fields, and marketing metadata keep changing as the product evolves.
- Schemas move fast
- Raw data is system-shaped, not business-shaped
- GTM logic gets pushed into downstream cleanup
Ontology layer
psi* consumes replicated production data, applies contract and usage logic, and keeps the repair and readiness model inside one backend-owned runtime.
- Stable curated business surfaces
- Self-healing replica and refresh path
- One place for revenue and customer logic
GTM model
Revenue teams, finance, and operators read from the same clean model for accrued revenue, customer analytics, attribution, and comp.
- Fewer spreadsheet versions
- Less BI-versus-GTM drift
- Faster answers without engineering dependency
Revenue data flow
The job is not modeling for its own sake. The job is turning raw systems into usable business data.
This is the business path Ontology makes easy: land the data, normalize the hard parts, reconcile the money, and publish clean surfaces the team can actually use.
Ontology operating path
replicate normalize reconcile publish
Replicate source systems
Normalize contracts + usage
Reconcile revenue
Publish clean surfaces
product postgres
elasticsearch
salesforce
marketo
customer and vendor contracts
product usage mappings
account relationships
lifecycle rules
accrued revenue
customer-level revenue state
attribution inputs
compensation inputs
customer reporting views
product usage views
revenue and contract surfaces
sales and marketing analytics
What teams get out of it
One ontology layer can power the finance-heavy and GTM-heavy questions at the same time.
Buyers should see the outputs immediately: better revenue reporting, cleaner customer analytics, and fewer broken handoffs between finance, ops, and go-to-market.
Revenue reconciliation
Reconcile product activity, contract state, and account relationships into accrued revenue that survives real-world complexity.
- Credit card reconciliation
- Banking-style customer relationships
- Revenue modules for different business models
Customer analytics
Publish clean customer reporting surfaces so the team can reason about accounts, cohorts, and operating performance without translating raw schemas by hand.
- Customer summary views
- Enriched customer reporting
- Stable operating metrics
Product usage
Translate raw product events and service state into business-facing usage that sales, finance, and success teams can actually use.
- Service and provider mappings
- Product configuration context
- Usage linked to the customer model
Attribution + comp
Keep sales attribution and compensation grounded in the same underlying customer and revenue model instead of separate manual systems.
- Sales and marketing attribution
- Compensation inputs
- Shared downstream model
Related surfaces
Ontology compounds with the rest of psi* once the business data layer is stable.
The data layer matters most when the rest of the system can read from it directly.
Product
Flows
Use clean ontology-backed data inside the automations that enrich, reconcile, route, and update the business.
Open productProduct
Agent Orchestration
Give the GTM team an agent that can reason over the same customer and revenue data the business already uses.
Open productProduct
Agentic App Builder
Build the operational surfaces your team uses on top of the same customer, usage, and revenue model.
Open productPlatform
All products
See how ontology, apps, flows, and orchestration compound when they run as one GTM operating system.
Open platformGet started
How many products does your company have, and how much contract logic is hiding in spreadsheets, BI models, and brittle pipelines?
psi*'s ontology revenue and cost modules can handle everything from credit card reconciliation and complex banking relationships to LLM model usage on a per-customer, per-day basis, while keeping GTM and finance aligned on the same underlying model.