Hire AI
Developers

SDLC Corp starts with a short kickoff to understand your product goals, tech stack, and timelines. We then align on access, environments, and delivery milestones, and assign an AI developer who can work with your team’s workflow (Jira, Git, Slack/Teams) from day one.

Yes—most work is integration, not replacement. We can connect models to your current backend, databases, and APIs, and ship AI features as services or modules that fit your current architecture.

We pick the simplest option that meets accuracy, cost, latency, and privacy needs. If an off-the-shelf model works, we optimize prompts, retrieval (RAG), and evaluation; if not, we move to fine-tuning or custom training.

We share clear weekly updates, measurable checkpoints (accuracy, latency, cost), and a documented backlog. SDLC Corp also follows review practices like code reviews, test coverage where relevant, and staged releases—so you can see real progress without surprises near launch.

It means testing, monitoring, and repeatability: clear evaluation metrics, error handling, model/version tracking, and performance checks after launch. If your model drifts over time, we set up a plan for retraining and ongoing quality control.

Yes. We diagnose where the issue lives data quality, evaluation method, retrieval, prompting, model choice, or infrastructure then improve accuracy and stability while also reducing latency and inference cost where possible.

After release, SDLC Corp can handle monitoring, bug fixes, and performance tuning (speed + inference cost). If results change over time due to data shifts, we also help with evaluation refresh, dataset improvement, and iterative upgrades so the AI stays reliable in production.

You can choose hourly support, a dedicated monthly resource, or a fixed milestone plan. For uncertain projects, a short paid “trial sprint” is often best to validate feasibility before committing long-term.