Why we released codex-strict-profile for larger codebases
An experimental public Codex profile for teams that need more verification, broader code reading, and clearer risk boundaries on medium and large codebases.
ReadSecurity-aware fintech delivery for payments, ledgers, integrations, and compliance-minded operations; built to be observable, auditable, and reliable.

We design and deliver payments, ledgers, and money-moving workflows that behave predictably under real-world failure modes: verified webhooks, idempotent processing, explicit state transitions, and reconciliation that answers “what happened?” without guesswork.
Compliance is supported by architecture, not slogans: least-privilege access, audit trails for privileged actions, data minimization, and change control with verification gates and incident-ready runbooks.
We clarify goals, constraints, and success metrics so the work stays coherent.
We map delivery into stages with quality gates, scope boundaries, and clear ownership.
You get a fixed, accountable plan with deliverables, milestones, and a pricing model that makes sense.

Explicit payment states, verified webhooks, safe retries, and reconciliation reporting so operations can resolve exceptions without ad-hoc database work.
Immutable histories, controlled mutation paths, and traceable actors so the system can answer who changed what, when, and why.
Data minimization, secret hygiene, and least-privilege controls paired with observability and runbooks for calmer incident response.
Decision tools, patterns, and delivery governance for teams planning a service investment.
An experimental public Codex profile for teams that need more verification, broader code reading, and clearer risk boundaries on medium and large codebases.
ReadA practical guide, grounded in a ViaRah case study, to shipping portals, workflow apps, and dashboards quickly with Django + Vue, plus a gut-check on when Vue is worth it and a build checklist.
ReadAI pilots look promising until handoffs, ownership, and approvals get messy. This guide shows leaders how to make AI automation safe to run at scale.
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