AI Builder Support
Turn Your AI Prototype Into Trusted Software
Your team built software to solve the problems that they know better than anyone. We're here to fill the gaps and make sure it's ready for production.
Supporting the AI builders you use:
👋 Talk to an AI engineer.
Supporting the AI builders you use:
Trusted and top rated tech team
Your team built it fast with AI. Now it has to hold up in production.
Tools like Claude Code, Replit, and Lovable have empowered small non-technical teams to build bespoke software. Your team has product instincts and a prototype already working. The harder problem is what sits underneath: data models that won’t scale, security gaps no one has reviewed, a lack of version control, and no test suite. We bring the engineering depth to audit what’s there, fix the gaps, and put guardrails in place so the team can keep moving.
Our capabilities include:
- Code audits and architecture reviews
- Security and compliance assessments
- Data model and infrastructure redesign
- Engineering guardrails for AI-built applications
- Application rebuilds and production deployment
- Team coaching for AI-assisted development
Who we support
Companies come to us from three different starting points: the business side built something with AI tools, the tech team shipped code that needs hardening, or a new leader inherited an application nobody can explain. The work differs. The need is the same.
Business Teams Building With AI Tools
The operations lead used Lovable to build a portal, the marketing team shipped a tool with Bolt, or someone vibe-coded a customer-facing app with Claude Code. The product works. What's missing is the engineering layer underneath: security review, a clean data model, and a path to production.
Lean Engineering Teams Using AI
The in-house dev team is lean, but the roadmap is large, and Claude Code or Cursor closed the gap. The code shipped, but no one wrote tests, set up CI/CD, or reviewed the dependency tree. The team needs senior engineering review and guardrails before the next release goes live.
Leaders Inheriting AI-Built Apps
You walked into a role and found internal applications nobody can fully explain. A previous team built them with Replit or v0, the documentation is thin, and the original people who built it are not there. We start with an audit so you know what you have, then work with you on what comes next.
Ways to engage
We offer a wide range of engagement models to meet our clients’ needs. From hourly consultation to fully managed solutions, our engagement models are designed to be flexible and customizable.
Staff Augmentation
Get access to on-demand product and engineering team talent that gives your company the flexibility to scale up and down as business needs ebb and flow.
Retainer Services
Retainers are perfect for companies that have a fully built product in maintenance mode. We'll give you peace of mind by keeping your software running, secure, and up to date.
Project Engagement
Project-based contracts that can range from small-scale audit and strategy sessions to more intricate replatforming or build from scratch initiatives.
We'll spec out a custom engagement model for you
Invested in creating success and defining new standards
At Curotec, we do more than deliver cutting-edge solutions — we build lasting partnerships. It’s the trust and collaboration we foster with our clients that make CEOs, CTOs, and CMOs consistently choose Curotec as their go-to partner.
Why choose Curotec for AI Builder Support?
You’ve got a new superpower for building software. Curotec works alongside your team to make sure that superpower doesn’t become a liability with security leaks, data loss, or system downtime. We put the guardrails in place to let you keep building.
1
Extraordinary people, exceptional outcomes
Our outstanding team represents our greatest asset. With business acumen, we translate objectives into solutions. Intellectual agility drives efficient software development problem-solving. Superior communication ensures seamless teamwork integration.
2
Deep technical expertise
We don’t claim to be experts in every framework and language. Instead, we focus on the tech ecosystems in which we excel, selecting engagements that align with our competencies for optimal results. Moreover, we offer pre-developed components and scaffolding to save you time and money.
3
Balancing innovation with practicality
We stay ahead of industry trends and innovations, avoiding the hype of every new technology fad. Focusing on innovations with real commercial potential, we guide you through the ever-changing tech landscape, helping you embrace proven technologies and cutting-edge advancements.
4
Flexibility in our approach
We offer a range of flexible working arrangements to meet your specific needs. Whether you prefer our end-to-end project delivery, embedding our experts within your teams, or consulting and retainer options, we have a solution designed to suit you.
Our Approach
We start with an expert review. Your vibe-coded application goes through a structured process that gives your team full clarity on the current state and a clear view of the gaps related to security and stability.
1. Audit & Discovery
2 weeks
- Identify technical debt
- Security audit
- Data model review
- Validate requirements against the codebase
2. Blueprint
Produced during discovery
- Document requirements
- Technical architecture plan
- Vibe coding guardrails
- User journey maps
- Risk assessment
3. Backlog Creation
Collaborative with your team
- Phased project roadmap
- Detailed task creation
- Parallel work stream plans
- Training for your team
4. Build & Deploy
Phased rollout
- Production infrastructure
- Development oversight
- Test suites, CI/CD
- Deployment strategy
- Ongoing support
AI Builder Support for every type of application
Internal Operations Tools
Customer Portals and Self-Service Apps
AI Agents and Workflow Automation
Data Dashboards and Reporting Apps
Custom Business Logic Applications
Marketing and Lead Generation Tools
The modern stack we bring to AI-built applications
AI Coding Guardrails and Standards
Curotec installs the configuration layer that turns AI coding tools into a reviewable, controllable part of the workflow.
- CLAUDE.md — Our engineers write project-level configuration that defines coding standards, architecture decisions, and review expectations for every Claude Code session.
- Cursor rules — We configure
.cursor/rules/*.mdcfiles so the team’s AI suggestions follow the patterns we’ve put in place, not the ones the AI defaults to. - AGENTS.md — Curotec maintains shared rules across Claude Code, Cursor, and other agents so teams using multiple tools stay consistent.
- Claude Code hooks — Pre-commit and post-action hooks that enforce linting, testing, and security checks before AI-generated code ever lands in a branch.
- MCP servers — We configure Model Context Protocol servers that give AI tools controlled access to internal systems, with the right boundaries.
- Prompt and pattern libraries — Curated examples and standards documents that keep AI output aligned with how the application is actually built.
Code Quality and Architecture
We rebuild the structural layer that AI tools skip: data models, business logic boundaries, and the static analysis to keep both honest.
- SonarQube — Our engineers run static analysis across the full codebase to surface code smells, complexity, and duplication that vibe-coded apps tend to accumulate.
- ESLint and Prettier — We standardize formatting and linting rules so AI-generated code follows the same conventions as everything else in the repository.
- Ruff and Black — Curotec applies modern Python tooling for fast linting and formatting, replacing the inconsistent style that emerges from prompt-driven development.
- Data model refactoring — We rearchitect the database layer to fix the relational issues and denormalization that show up almost universally in AI-built apps.
- Domain-driven design — Our engineers separate the duplicated business logic into clear boundaries so the application reflects how the business actually operates.
- Architecture decision records — We document the technical choices so the team and any future AI agent knows what was decided and why.
Testing and Quality Assurance
Our team builds the test coverage that should have been there from the start, then automates it so regressions get caught before they ship.
- Vitest and Jest — Our engineers write unit tests for the business logic AI tools usually leave untested, with coverage targets that mean something.
- Playwright — We build end-to-end test suites that exercise the real user flows, including the edge cases AI-generated code rarely accounts for.
- Pest and PHPUnit — Curotec writes integration tests for PHP and Laravel applications, validating logic against real data, not placeholder responses.
- pytest — Our engineers cover Python applications with fixtures, parametrized tests, and the kinds of assertions that catch subtle business logic errors.
- Contract testing — We validate the boundaries between services and APIs so changes in one place don’t quietly break another.
- Test data and fixtures — Curotec replaces the placeholder data that hid problems during development with realistic fixtures that surface actual edge cases.
Version Control and CI/CD
Curotec installs the source control, automation, and deployment pipeline that should exist before a single line of code ships.
- Git workflows — Our engineers set up branching strategies, code review processes, and merge protections that match how the team actually works.
- GitHub Actions — We build CI/CD pipelines that run tests, security scans, and quality gates on every pull request before code can be merged.
- Husky and lint-staged — Curotec configures pre-commit hooks so formatting, linting, and basic checks run automatically on every commit.
- Gitleaks — We add pre-commit and CI-level secrets scanning to catch the API keys and credentials that AI tools sometimes paste into the codebase.
- Conventional commits — Our engineers standardize commit messages so the release process, changelog, and code history stay readable as the team scales.
- Dependabot — We automate dependency updates with the right review gates so security patches land quickly without breaking the build.
Security and Dependency Management
We bring the security review and supply chain controls that AI-assisted development tends to skip entirely.
- Snyk Open Source — Our engineers run continuous dependency scanning to surface known vulnerabilities in the package tree, with automated pull requests for fixes.
- Semgrep — We write custom static analysis rules that catch the specific vulnerability patterns AI tools introduce, including authentication and authorization gaps.
- Trivy — Curotec scans containers, infrastructure-as-code, and filesystems for CVEs and misconfigurations across the deployment surface.
- SBOM generation — We produce software bills of materials with CycloneDX so the team knows exactly what’s running in production at any given time.
- Secrets management — Our engineers move credentials out of the codebase into proper secret stores like AWS Secrets Manager or HashiCorp Vault.
- Authentication and authorization review — We audit auth flows, session handling, and access controls, the areas where vibe-coded apps fail most consistently.
Infrastructure and Observability
Our engineers move your applications from prototype to production-ready infrastructure, giving you full visibility and monitoring.
- AWS — Curotec deploys applications on AWS with the networking, security, and scaling configuration that real workloads require.
- Terraform — Our engineers manage infrastructure as code so environments are reproducible, reviewable, and consistent across staging and live deployments.
- Docker — We containerize applications for predictable deployments and isolation between services, environments, and dependencies.
- Sentry — Curotec configures error monitoring with release tracking, source maps, and alerting so issues surface the moment they happen.
- Datadog — We set up application performance monitoring across the stack so the team can see latency, throughput, and resource usage in real time.
- Langfuse — Our engineers add LLM observability for the AI features inside the application, tracking prompts, costs, and output quality once it’s live.
FAQs about our AI Builder Support services
What does an engagement actually look like?
Discovery first, then a phased plan. Audit and discovery, blueprint deliverables, roadmap and prioritization, then build and deploy. You see what we found and what we recommend before committing to scope or cost.
How long does an audit take?
Two to four weeks per application, depending on complexity. The first week is codebase deep-dive and business logic mapping. By week two, our engineers have a clear picture of what’s working, what’s broken, and what needs to change.
Do you rewrite the app or just fix it?
Both, depending on what the audit finds. Sometimes the right move is targeted refactoring and guardrails. Sometimes the data model is broken badly enough that a rebuild is faster than the patches. We tell you which after discovery, not before.
What if we already shipped the app to customers?
That’s most of what we see. We audit live applications and prioritize the fixes by risk and impact, with a phased rollout plan that keeps the application running while we work. No big-bang rewrite, no production downtime.
Can our team keep using Claude Code or Replit?
Yes. The goal is not to remove AI tools from your workflow. It’s to install the conventions, review processes, and engineering standards that make those tools safe to use on live code. Your team gets faster, not slower.
Do you stay involved after the audit?
If you want us to. Some clients use Curotec for the audit and setup only, then run on their own. Others keep us embedded for ongoing engineering support. The model fits what you need, not the other way around.
Ready to have a conversation?
We’re here to discuss how we can partner, sharing our knowledge and experience for your product development needs. Get started driving your business forward.