When AI lives outside the database, every insight costs an integration. Oracle Database 23ai brings vector search, natural language querying, and generative AI natively inside Oracle – where your enterprise data already lives. Rapidflow implements it.
Enterprise AI strategies typically fail at the data layer – not because the models are wrong, but because the data infrastructure was not designed to support them. Oracle Database 23ai eliminates that gap by building AI capabilities natively into the database itself. Vector search, natural language querying, and generative AI integration are no longer bolt-on additions. They are built-in features of the same database running your ERP, supply chain, and financial workloads.
Rapidflow’s oracle AI database transformation practice helps enterprises activate these capabilities in production.
Oracle Database 23ai is Oracle’s latest major database release – purpose-built to make AI a first-class database capability rather than an external dependency.
Oracle Database 23ai AI insights enterprise applications do not require a separate vector database, a separate ML platform, or a separate analytics engine. The same database storing transactional data now natively handles vector embeddings, semantic search, natural language SQL, and generative AI data strategy workflows – reducing architectural complexity and keeping AI operations within the governed, secure Oracle data environment where enterprise data already lives.
Oracle AI Vector Search is the most consequential new capability in Oracle Database 23ai for enterprise AI applications. It stores vector embeddings – mathematical representations of meaning generated by large language models – directly inside Oracle Database, alongside relational data.
The operational implication is significant. Traditional keyword search matches exact terms. Semantic search matches meaning.
A query for “late supplier deliveries impacting production” returns relevant records even when those exact words do not appear in the data – because the vector representation of the query matches the semantic content of the records.
For enterprises building Retrieval-Augmented Generation (RAG) applications – where a language model answers questions grounded in enterprise data – Oracle 23ai AI Vector Search eliminates the need for a separate vector database.
Embeddings, relational joins, and SQL aggregations run in a single query against a single system, under Oracle’s existing security and governance model.
Rapidflow implements Oracle AI Vector Search for:
Oracle SELECT AI enables business users to query Oracle Database using plain English sentences rather than SQL syntax. The feature translates natural language input into valid SQL – executed against the live database with full row-level security, access controls, and audit logging intact.
The enterprise use case is not replacing SQL developers. It is removing the query bottleneck between business users and data.
Finance analysts, supply chain planners, and operations managers who currently wait for BI reports or analyst availability can ask direct questions of Oracle data and receive answers – with AI-driven enterprise data insights surfaced through standard Oracle tooling without separate BI – layer dependencies.
SELECT AI works with Oracle’s own large language models on OCI and with third-party LLM providers via Oracle’s AI infrastructure – giving enterprises flexibility in oracle predictive analytics modernization without locking into a single model provider.
Oracle SELECT AI enables business users to query Oracle Database using plain English sentences rather than SQL syntax. The feature translates natural language input into valid SQL – executed against the live database with full row-level security, access controls, and audit logging intact.
The enterprise use case is not replacing SQL developers. It is removing the query bottleneck between business users and data.
Finance analysts, supply chain planners, and operations managers who currently wait for BI reports or analyst availability can ask direct questions of Oracle data and receive answers – with AI-driven enterprise data insights surfaced through standard Oracle tooling without separate BI – layer dependencies.
SELECT AI works with Oracle’s own large language models on OCI and with third-party LLM providers via Oracle’s AI infrastructure – giving enterprises flexibility in oracle predictive analytics modernization without locking into a single model provider.
| Feature | Oracle Database 19c | Oracle Database 23ai |
|---|---|---|
| AI Vector Search | Not available | Native vector storage and VECTOR datatype with similarity search |
| Natural Language SQL | Not available | SELECT AI - plain English to SQL with LLM integration |
| JSON Support | JSON columns, SQL/JSON | JSON Relational Duality Views - same data as JSON or relational |
| Boolean Datatype | Workaround required | Native BOOLEAN datatype |
| In-Memory Caching | Database In-Memory | True Cache - application-tier in-memory caching |
| Graph Analytics | Separate graph engine | Property Graph Views - graph queries on relational data |
| AI Integration | External only | Native OCI AI Services and third-party LLM connectivity |
| Annotation Support | Not available | Domain and annotation framework for data governance |
Oracle Database 23ai is available on Oracle Cloud Infrastructure as a fully managed Base Database Service – eliminating on-premise infrastructure overhead while delivering the complete 23ai feature set including AI Vector Search, SELECT AI, and native OCI AI Services integration.
Oracle enterprise AI architecture on OCI with 23ai benefits from native service integration that on-premise deployments cannot replicate at equivalent cost:
Rapidflow’s Oracle 23ai on OCI deployment engagements cover provisioning, network security configuration, AI feature activation, LLM connectivity setup, and performance baseline validation – ensuring the deployment is production-ready, not just provisioned.
Activating Oracle 23ai’s AI capabilities in a production enterprise environment requires more than an upgrade. It requires an oracle AI-enabled database services engagement that covers feature configuration, integration design, and governance alignment simultaneously.
Rapidflow’s 23ai implementation scope covers:

























































Oracle Database 23ai is Oracle's latest database with native AI including AI Vector Search for semantic similarity search, SELECT AI for natural language SQL, Boolean datatype, True Cache, and JSON Relational Duality Views. Rapidflow is one of the Oracle partners with dedicated 23ai implementation expertise.
Oracle AI Vector Search stores and queries vector embeddings inside Oracle Database 23ai - enabling semantic search and RAG applications without a separate vector database, reducing AI architecture complexity.
AI Vector Search, SELECT AI (natural language to SQL), Boolean datatype, True Cache, JSON Relational Duality Views, and Property Graph Views.
Oracle 23ai enables natural language reporting queries, AI-driven anomaly detection on financial data, semantic product catalog search, and GenAI supply chain insights - directly in the database tier.
Yes. Rapidflow provides 23ai upgrade services including compatibility assessment, upgrade execution on OCI, AI feature configuration (Vector Search, SELECT AI), and performance validation with minimal production downtime.
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