Architectural Requirements

To reliably support both sales-led and self-serve workflows, the platform must meet the following requirements, derived from first principles:

Unified CPQ and Billing

CPQ and billing functionality must be combined within a single platform and a single data model. Quotes, contracts, entitlements, usage, and billing must operate on the same underlying objects and lifecycle.

Enterprise-Grade Channel-Agnostic Product Catalog

The platform must expose a single, enterprise-grade product and pricing catalog that can support:

Simple yet feature-rich self-serve plans
Complex enterprise pricing (custom terms, ramps, credits, usage)
Business models like subscriptions, one-time, consumption and credits

The same catalog must be reused across all channels without duplication.

API-First

The platform must expose a fully API-first architecture in which all monetization primitives are programmatically accessible and composable. This enables direct integration not only with customer-facing surfaces such as websites and applications, but also with the broader revenue stack, including:

Payment processors and gateways e.g, Stripe, Adyen etc.
Tax calculation and compliance systems e.g., Anrok, Taxwire, Avalara etc.
Identity and entitlement services e.g., Auth0, Descope etc.
Data warehouses and analytics pipelines e.g., BigQuery, Snowflake etc. • Internal backend services

Core monetization objects—including products, prices, contracts, subscriptions, amendments, usage, and invoices—must be fully accessible via APIs to support automated provisioning, real-time updates, and reliable downstream synchronization.

Intentional CRM Integration for Sales-Led Workflows

The platform must provide robust and intentional CRM integrations that ensure self-serve customer activity is reliably reflected in the upstream CRM without data loss or manual intervention.

Reliable synchronization at scale Self-serve events such as sign-ups, upgrades, downgrades, renewals, and cancellations must be propagated to the CRM in a reliable and fault-tolerant manner. The integration must account for CRM-imposed constraints such as API rate limits, bulk processing limits, and object-level restrictions by employing batching, retries, backoff, and asynchronous processing where required.
Use of standard CRM objects Self-serve data should map cleanly onto standard CRM objects (e.g., Accounts, Contacts, Opportunities, Contracts) wherever possible to ensure compatibility with existing sales, finance, and reporting workflows.
Minimal reliance on custom objects Custom objects should be used sparingly and only when required, in order to reduce operational complexity and ongoing maintenance burden.
Consistent system of record The CRM must remain a reliable source of truth for customer and contract state, regardless of whether changes originate from sales-led or self-serve workflows.

Cross-channel Synchronization

The platform must support bidirectional synchronization between self-serve and sales-led workflows to ensure a consistent system of record across channels.

If a customer is initially acquired via a sales-led workflow, any subsequent contraction events—such as downgrades, quantity reductions, or plan changes—initiated through self-serve APIs must automatically synchronize back to the CRM (SLG → PLG).

Conversely, if a customer is initially acquired via a self-serve workflow, any expansion events—such as enterprise upgrades, contract negotiations, or sales-assisted renewals—must synchronize from the CRM back into the monetization platform (PLG → SLG).

This bidirectional model ensures that:

Contract state, entitlements, and billing remain consistent regardless of entry point
Sales, finance, and product teams operate on a shared source of truth
Channel transitions do not require manual reconciliation or data migration

Environment and Sandbox Management

The platform must support on-demand environment management, including:

Creating and destroying sandboxes programmatically
Instantly provisioning full product catalogs in sandbox environments via APIs

This enables safe testing, experimentation, and implementation without impacting production systems.