01
Connect
Bring structured and unstructured inputs into one workflow model across ERP, SQL, files, APIs, and documents.
N2ONE CORE AI
Governed AI execution for enterprise data, documents, and operational workflows.
N2ONE CORE AI extends enterprise integration into AI-enabled execution. Structure fragmented knowledge, orchestrate prompt-driven workflow steps, prepare private RAG, and support controlled agent action on governed business data.
SAP SQL Server PostgreSQL + pgvector PDF JSON CSV RAG MCP
Enterprise integration becomes a governed AI layer: what AI can read, retrieve, reason over, and act on — with traceability.
AI capability position
Not just AI on top of files. A governed AI layer built on top of operational workflow.
N2ONE CORE AI combines enterprise ingestion, deterministic orchestration, prompt-driven reasoning, retrieval preparation, and controlled execution into one practical foundation.
The result is a production-capable path to document intelligence, private RAG, workflow AI, and future agent enablement without surrendering governance.
Platform story
From fragmented inputs to governed AI action
N2ONE CORE AI creates the controlled layer between enterprise knowledge and AI-driven outcomes.
02
Structure
Transform content into chunks, metadata, prompts, and controlled context that AI can use meaningfully.
03
Retrieve
Support private RAG and semantic search on governed enterprise knowledge instead of relying on model memory alone.
04
Execute
Route outputs back into business process with traceable workflow logic, approvals, and controlled action boundaries.
Workflow AI
Use AI inside governed process flow
N2ONE CORE AI places AI inside a deterministic execution model. Prompts can be scoped to individual steps, updated dynamically by prior step output, and routed through conditional logic rather than uncontrolled autonomy.
Prompt per step
Dynamic prompt injection
Conditional branching
Traceable execution path
AI as part of governed workflow execution
Document intelligence
Transform PDFs and enterprise content into structured knowledge
A practical starting point is large-scale document ingestion. Read PDFs, extract content, create chunks, attach metadata, and prepare retrieval-ready knowledge for downstream AI use.
Mass PDF reading
Chunking and metadata
Source traceability
Retrieval-ready structure
Enterprise knowledge prepared for governed retrieval
Why it matters
What N2ONE CORE AI gives the enterprise
Private RAG foundation
Ground outputs on governed enterprise content with chunking, embeddings, metadata, and retrieval controls.
Traceable AI execution
Understand what context, workflow path, and logic produced the result instead of relying on black-box behavior.
Enterprise workflow fit
Keep AI connected to real process, real systems, and real operational controls instead of isolating it in chat alone.
Agent-ready architecture
Prepare approved CORE capabilities for future API or MCP-based agent interaction without abandoning governance.
Starting points
Where organizations typically start
Start with one controlled pattern. Expand into a broader AI foundation over time.
01
Document Intelligence Starter
Read, chunk, enrich, and structure large document sets for governed retrieval and downstream AI use.
02
Private RAG on Core
Build a retrieval foundation using PostgreSQL + pgvector, metadata-rich chunks, and explainable grounding.
03
Workflow AI Enablement
Insert AI steps into production-capable enterprise workflows with prompt control and routing logic.
04
Agent-Ready Architecture
Prepare for controlled API or MCP-based interaction with approved CORE workflows, tools, and permissions.
Get an N2ONE CORE AI fit-check
We help define the right starting point — document intelligence, private RAG, workflow AI, or agent-ready architecture — and the governed path to production.
Book AI fit-check Run ISA-M assessment See platform story
Windows-based orchestration • enterprise connectors • private RAG path • controlled agent readiness