AI Prototype to Production Services for Scalable Product Launches

Every line of code goes through peer review. We enforce automated testing (minimum 70% coverage), run security scans in CI/CD, and use tools like SonarQube to monitor code complexity. For critical features, we require two reviewers before merging.

For fixed-scope projects (MVP Sprints), we absorb overruns up to 20% of estimated hours. Beyond that, we discuss options: reducing scope, extending the timeline, or adding resources. For dedicated pods, you're billed monthly regardless of feature completion, similar to an in-house team.

You own all code, documentation, and intellectual property from day one. Our contracts explicitly state this. We do not retain any rights to your codebase or product.

Yes, we offer a conversion program. After 6 months of engagement, you can hire an AI engineer on your pod with a 2-month recruitment fee (equal to 2 months of their billing rate). This ensures smooth transitions without disrupting your project.

Yes, we sign NDAs before any technical discussions. We also have standard BAAs (Business Associate Agreements) for HIPAA-covered entities.

We replace underperforming engineers within 2 weeks at no additional cost. This happens rarely (less than 5% of placements), but when it does, we act quickly.

We implement security best practices by default: encryption at rest and in transit, secure authentication, input validation, and OWASP Top 10 protection. For regulated industries (healthcare, finance), we have experience with HIPAA, SOC 2, PCI-DSS, and GDPR compliance.

99% of our projects deploy to production. The 1% that do not are typically due to business pivots, not technical failures. Our average client Net Promoter Score is 72 (considered excellent in B2B services).