Your ERP knows everything. Now it can explain it.

1. Context Graph

Memory with meaning. Normal databases store rows. Normal vector stores store embeddings (numbers that represent meaning). SIL stores a graph — nodes are entities (a supplier, a PO, a demand signal), and edges are the relationships between them with typed, weighted connections.

The difference: a database can tell you what exists. The Context Graph tells you how everything relates to everything else. Ask "what's connected to supplier X?" and it traverses the graph in all directions, weighted by relevance.

2. Decision Intelligence

The receipts your organization has never had. Every decision becomes a first-class object — not a log entry, but a structured record with:

• What inputs caused it
• What rule or reasoning produced it
• What it caused downstream
• A causal chain you can traverse forwards or backwards

When a commission is disputed or a reorder looks wrong, you don't guess — you get the full story in one click.

3. Reasoning Engine

The rules that think. Business logic lives here. Instead of hardcoding if/else rules in application code (which nobody can see without a developer), SIL uses a Rete network — a pattern-matching engine that:

• Holds all your business rules as declarative statements
• Continuously evaluates incoming facts against those rules
• Fires consequences when conditions are met

It's blazing fast because it only processes what changed — thousands of ERP events per minute, every time, no exceptions.

4. Provenance

Show your work. Every single fact in the system carries its origin. Where did this number come from? Which API call? Which document? Which user action?

It follows the W3C PROV-O standard — the same lineage tracking used in scientific research and government data. When an auditor asks "prove this AI recommendation is trustworthy," you hand them a provenance trace that reads like a chain of custody report.