Decompose Notion PostgreSQL seller messaging after #149

offerings/README.md

@@ -14,4 +14,6 @@ Percona offers three complementary ways to meet customer needs across the full l
 
 When the need is a defined outcome on fixed scope with Consulting and Support packaged together, see [solution bundles](solution-bundles/messaging.md).
 
+Engine-specific Support or Consulting scope (extensions, compatibility boundaries, advisory add-ons) belongs under `products/{engine}/`, not in offering files here. Offering files describe how Support, ExpertOps, and Consulting work across all supported engines.
+
 Per-file messaging: [expert-support.md](expert-support.md), [expertops.md](expertops.md), [expert-consulting.md](expert-consulting.md). For packaged sold bundles, use `offerings/solution-bundles/`.

products/README.md

@@ -6,4 +6,6 @@ This directory contains product and database-specific messaging.
 
 Each product area includes `messaging.md` for canonical product framing. Competitive positioning and internal talk tracks belong in private execution systems, not in this repository (see [reference/content-governance.md](../reference/content-governance.md)).
 
+Engine-specific Support, ExpertOps, or Consulting differentiators belong in the relevant product `messaging.md` pillar bullets (what ships in the distribution, what experts cover in production, and customer outcomes). Keep `offerings/` files cross-engine. If a product's expert-coverage scope outgrows `messaging.md`, add a sibling file under that product directory (for example `products/postgresql/expert-coverage.md`) through the new-file gate in [reference/content-governance.md](../reference/content-governance.md).
+
 Current product areas include MySQL, PostgreSQL, MongoDB, Valkey/Redis, PMM, and Operators.

products/postgresql/messaging.md

@@ -21,7 +21,8 @@ Unlike license-restricted PostgreSQL offerings and proprietary DBaaS services, P
 - High-availability and disaster recovery made simple: The Percona Distribution for PostgreSQL includes Patroni to automate failover for high availability and coordinate switchovers for maintenance tasks, and pgBackRest for backup catalog management and Point-in-Time Recovery (PiTR) when data must be restored after higher-impact incidents. Reference patterns and implementation guidance are in [High availability for PostgreSQL](https://www.percona.com/ha-for-postgresql). Distribution releases keep Patroni HA automation and its coordination stack release-tested through upgrade cadence across supported PostgreSQL majors. Automated failover minimises recovery time and outage impact.
 - Logical replication for migration and scale-out: Percona Distribution for PostgreSQL on PostgreSQL 18 supports parallel logical replication for faster initial data synchronization during replica build and major-version migration, reducing cutover risk and replication catch-up time.
 - Built-in replication lag monitoring: PostgreSQL provides native, accurate replication lag tracking through `pg_stat_wal_receiver` and WAL LSN comparison, without requiring external heartbeat tooling. PMM surfaces this data via the `pg_custom_stat_wal_receiver_lag_bytes` metric (sourced from `postgres_exporter`). Teams migrating from MySQL (where external tools like pt-heartbeat are common for lag measurement) gain this capability out of the box with PostgreSQL.
-- Horizontal scale and legacy tooling: Expert Support and consulting cover Citus sharding coordinated with Patroni HA on customer deployments where Citus runs alongside the distribution stack (Citus is not packaged in the standard distribution build; see [third-party components](https://docs.percona.com/postgresql/18/third-party.html)). Advisory Expert Support is also available for estates that still run barman or repmgr alongside PostgreSQL where migration to pgBackRest and Patroni is phased.
+- Horizontal scale and legacy tooling: Expert Support and consulting cover Citus sharding and timescale time-series workloads on customer-managed PostgreSQL coordinated with Patroni HA where those extensions run alongside the distribution stack (neither Citus nor timescale is packaged in the standard distribution build; see [third-party components](https://docs.percona.com/postgresql/18/third-party.html)). Advisory Expert Support is also available for estates that still run barman or repmgr alongside PostgreSQL where migration to pgBackRest and Patroni is phased.
+- Deep PostgreSQL observability extensions: Advisory Support covers pg_stat_kcache and pg_wait_sampling for kernel-level query resource visibility and sampled wait-event analysis; pg_wait_sampling integrates with PMM for unified wait analysis where teams deploy both.
 
 **Security, Sovereignty, and Compliance**
 
@@ -33,5 +34,24 @@ Unlike license-restricted PostgreSQL offerings and proprietary DBaaS services, P
 
 - Cloud-native operations: The Percona Operator for PostgreSQL automates deployment, scaling, and failover in Kubernetes environments, delivering consistent governance and portability across any cloud.
 - Platform portability: Percona Distribution for PostgreSQL ships packages for current Ubuntu LTS releases, including Ubuntu 26.04 on AMD64 and ARM64, so teams can standardize database deployments on their long-term support platform images without retooling the stack.
-- AI and analytics readiness: Teams run embeddings and vector search on PostgreSQL using pgvector packaged with other tested distribution components ([third-party components](https://docs.percona.com/postgresql/18/third-party.html)), avoiding a separate AI-only datastore for many workloads. Optional extensions beyond that validated set, including pgvectorscale when packaged for a given distribution release, are listed alongside other tested components in distribution documentation, which ties sizing and performance conversations to binaries customers deploy rather than benchmark scenarios that omit packaging constraints.
+- AI and analytics readiness: Teams run embeddings and vector search on PostgreSQL using pgvector packaged with other tested distribution components ([third-party components](https://docs.percona.com/postgresql/18/third-party.html)), avoiding a separate AI-only datastore for many workloads. Percona Expert Support includes advisory guidance for pgvector production tuning. pgvectorscale is available through advisory Support tiers and is not packaged in Percona Distribution for PostgreSQL.
 - Geospatial workloads: PostGIS ships as a validated third-party component; Expert Support and consulting cover coordinated PostgreSQL and PostGIS upgrades, dependency checks, and spatial workload regression planning ([PostGIS deployment](https://docs.percona.com/postgresql/17/solutions/postgis-deploy.html)).
+
+### Conversation starters
+
+- How long does it take your team to configure vanilla PostgreSQL for a new production environment? (The distribution ships HA, backup, and security components release-tested together.)
+- What do you do when PostgreSQL is down? (Percona Expert Support provides SLA-backed escalation.)
+- How do you ensure PostgreSQL infrastructure performs well under load? (Support, ExpertOps, and consulting cover tuning and architecture.)
+- How do you meet uptime and incident-response requirements from regulators or customers?
+- How much internal PostgreSQL expertise does your team have today?
+- If you already have a support contract: How has your experience been with your current vendor?
+- If migrating from Oracle or another proprietary database: How will you handle configuration, schema and data migration, compatibility, and HA architecture?
+
+### Public resources
+
+- [Percona Software for PostgreSQL](https://www.percona.com/postgresql/software)
+- [High availability for PostgreSQL](https://www.percona.com/ha-for-postgresql)
+- [pg_tde documentation](https://docs.percona.com/pg-tde/)
+- [Percona Distribution for PostgreSQL release notes](https://docs.percona.com/postgresql/latest/release-notes/release-notes.html)
+- [Support for PostgreSQL](https://www.percona.com/services/support/postgresql-support)
+- [Database comparison (MySQL, MongoDB, PostgreSQL, MariaDB)](https://www.percona.com/compare-mysql-mongodb-postgresql-mariadb)

use-cases-value-pillars/future-readiness-ai.md

@@ -20,7 +20,7 @@ AI, ML, and real-time analytics depend on data mobility and trust, but current d
 
 Percona enables AI, vector search, and hybrid data workloads through open, secure, and portable database architectures. Customers can modernize existing systems for emerging workloads without replatforming or lock-in.
 
-- **AI-ready databases:** Percona packages [pgvector](https://www.percona.com/blog/pgvector-the-critical-postgresql-component-for-your-enterprise-ai-strategy/) for PostgreSQL alongside other tested distribution components ([third-party components](https://docs.percona.com/postgresql/18/third-party.html)). Extensions such as pgvectorscale ship only where documented for a release ([release notes](https://docs.percona.com/postgresql/latest/release-notes/release-notes.html)), which ties AI workload planning to the builds organizations install. Expert Support and consulting cover PostgreSQL and pgvector performance and operations; embedding model selection and LLM application design remain with development teams.
+- **AI-ready databases:** Percona packages [pgvector](https://www.percona.com/blog/pgvector-the-critical-postgresql-component-for-your-enterprise-ai-strategy/) for PostgreSQL alongside other tested distribution components ([third-party components](https://docs.percona.com/postgresql/18/third-party.html)). Percona Expert Support includes advisory guidance for pgvector production tuning. Percona focuses on PostgreSQL performance, scalability, and security for vector workloads, not embedding-model or LLM application design. pgvectorscale is available through advisory Support tiers and is not packaged in Percona Distribution for PostgreSQL.
 - **Hybrid and multi-cloud flexibility:** Percona Operators orchestrate consistent deployments across on-prem and cloud clusters, enabling AI pipelines to train or infer near the data source while maintaining governance.
 - **Data integrity and compliance:** Encryption, RBAC, and transparent audit logs preserve control over sensitive data used in AI training, supporting GDPR, HIPAA, and ISO 27001 alignment.
 - **Predictable performance and cost:** ExpertOps tuning and rightsized infrastructure optimize indexing, caching, and query execution for AI workloads.