Our AI products
OCS operates four focused products, giving our team direct experience with the engineering work that continues after the first useful prototype.
View details →Production engineering for working prototypes
You built the prototype. We make it production ready.
Production engineering for software prototypes that already prove the idea but still need secure architecture, reliable data, testing, observability, deployment, and an operating handoff.
Discuss this serviceThe engagement
Solve the workflow, not just the technology.
A working prototype is valuable evidence. It proves the workflow, helps users react to something real, and exposes what should be built next. It does not need to be discarded simply because it was created quickly or accelerated with tools such as Claude Code, Codex, Cursor, Lovable, or Replit.
Production introduces a different set of responsibilities. We inherit the existing codebase, understand what is sound, identify the risks that matter, and harden the system without turning the engagement into an unnecessary rewrite. That includes the application, data, integrations, AI behavior, deployment path, and the team that will own it after launch.
Where it fits
Where we can help
- Hardening an AI-assisted SaaS prototype before the first production customers
- Taking over a codebase that works but needs architecture and security review
- Adding authorization, tenant isolation, data-integrity rules, and safe migrations
- Making APIs, background jobs, billing, and webhooks idempotent and recoverable
- Building model evaluations, application tests, logging, alerts, and cost controls
- Establishing environments, CI/CD, backup, rollback, runbooks, and a maintainable handoff
What you receive
Practical deliverables
- Codebase, architecture, data, security, and deployment assessment
- Risk-ranked production-readiness plan that separates launch blockers from later improvements
- Targeted remediation across identity, authorization, tenant boundaries, secrets, and data integrity
- Reliable integrations, migrations, jobs, webhooks, and failure recovery
- Application tests, AI evaluations, observability, alerts, and release automation
- Production launch plan, rollback and recovery procedures, runbooks, and ownership handoff
Delivery approach
A controlled path to a useful result
- 01
Inspect
Run the application, trace its critical workflows, review the code and data model, and document how it is currently deployed and operated.
- 02
Prioritize
Rank findings by user impact, security exposure, data risk, reliability, and launch dependency so the team knows what must change first.
- 03
Harden
Remediate the highest-value risks while preserving the parts of the prototype that already work and adding evidence through tests and evaluations.
- 04
Launch and transfer
Validate production behavior, recovery, monitoring, and ownership, then leave the team with a supportable release process and prioritized backlog.
Safety and operations
Built for real operations.
Reliability, governance, and human responsibility are treated as engineering requirements. The controls are connected to how the system will actually be used, supported, and changed.
- No automatic rewrite: existing code is evaluated before replacement is recommended
- Authentication is separated from authorization, tenant boundaries, and data-access policy
- Critical integrations are designed for retries, duplicate events, partial failure, and recovery
- Launch criteria cover security, data integrity, reliability, observability, cost, and operational ownership
Relevant work
Delivery experience behind the service
EduTrack
A client platform delivered as a role-aware production application with consolidated workflows, data, deployment, and operational visibility.
View details →Keep exploring
Related guidance
Bring us the hard problem.
Show us the prototype, the current codebase, and the launch concerns. We will help separate what is ready, what must change, and the shortest responsible path to production.
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