AI-oriented reconciliation engine
An incoming high-performance reconciliation engine built around Rust, AI-assisted matching, and production-grade financial workflows.
Outcomes
Incoming
This is an incoming product direction for a high-performance reconciliation engine: a system that treats financial and operational matching as a real algorithmic problem, then uses AI only where it adds useful signal.
The center of the project is a Rust core for the expensive matching path. Rust fits the shape of the problem: memory control, predictable performance, safe concurrency, and a better foundation for processing large candidate sets without turning the engine into a slow script.
System shape
| Layer | Responsibility | Why it matters |
|---|---|---|
| Rust core | Candidate generation and scoring | Keeps high-volume matching fast and predictable. |
| Constraint engine | Amounts, dates, references, uniqueness | Preserves financial correctness. |
| AI signal layer | Similarity, clustering, anomalies | Helps rank ambiguous cases. |
| Review surface | Uncertain matches and explanations | Keeps the workflow auditable. |
Why it belongs in Work
This belongs in Work because it connects the strongest parts of the portfolio: reconciliation, hard matching problems, AI-assisted operations, and systems engineering. The goal is not an AI demo. The goal is a reconciliation engine that is fast, careful, and explainable enough to sit inside a real workflow.