Leo Bons

Self-initiated Rivetfern demonstration using synthetic events. This is not paid client work or a production deployment. I built a local Python HTTP receiver that validates a documented HMAC signature and strict JSON shape before recording accepted events in SQLite. A worker leases queued events, retries transient failures within a finite budget, and quarantines permanent failures. The local destination uses event IDs to avoid duplicate tasks. The reproducible scenario covers a normal event, duplicate delivery, retry, permanent failure, forged signature, and conflicting payload. Three unique events enter the queue; two produce local tasks and one enters the dead-letter state. No email, external webhook, order, or real customer action is sent. I used AI assistance during development, reviewed the code, and ran the tests. See the public case study and code bundle](https://www.twine.net/signin The sample uses its own signature contract, not Stripe's. A real integration would require the provider's schema and verification rules, HTTPS, access control, monitoring, retention and an idempotent destination.

• Back-End Developer

Self-initiated Rivetfern demonstration using entirely synthetic invoice and payment exports. This is not paid client work. I built a standard-library Python pipeline that validates an explicit CSV schema, normalizes permitted dates and amounts, quarantines duplicate or conflicting IDs, and reconciles valid payments. It keeps USD and NZD separate and does not guess ambiguous dates. Outputs include cleaned CSV files, a reconciliation report, rejected rows, payment exceptions, an audit log, and input hashes. The deterministic fixture has 90 invoice rows and 92 payment rows. The validated output has 80 invoice records and 84 payment records; six duplicate rows are excluded and twelve invalid or conflicting rows are rejected. The sample includes runnable tests and replayable fixtures. I used AI assistance during development, reviewed the code, and ran the tests. See the public case study and code bundle](https://www.twine.net/signin A real engagement would start with a sample export and agreed schema, acceptance rules, and handling for any refunds, taxes, or FX.

• Data Analyst

Self-initiated Rivetfern demonstration using synthetic support-ticket metadata. No real helpdesk or customer account is connected; this is not paid client work. The standard-library Python tool validates dates, priorities, status and supplied SLA-day inputs; quarantines conflicting duplicate ticket IDs; skips exact duplicates; and produces a sorted queue of open and pending tickets. It flags rows past or at their supplied date threshold and counts unassigned cases. Closed tickets remain in the summary without an invented resolution time. The outputs include an exception CSV, a compact JSON summary and SHA-256 file hashes. The tool sends no customer messages and updates no helpdesk. I used AI assistance during development, reviewed the code and ran the tests. See the public case study and code bundle](https://www.twine.net/signin This sample uses calendar days and treats each supplied SLA as an input. Business hours, holidays and contractual service-level policy need explicit agreement for real use.

• Data Analyst