What this category covers (in plain English)
Think of this as your “AI product toolkit.” It includes the software that helps you go from first prompt to a feature that’s safe, measurable, and fast enough for real users.
- Model access: SDKs and gateways that make calling multiple LLMs simple.
- Workflow tools: Orchestration frameworks for multi-step tasks and agents.
- Knowledge & retrieval: Tools that pull in your docs, database, or files.
- Quality checks: Evaluation suites to compare prompts and catch regressions.
- Monitoring: Visibility into latency, cost, and real-user outcomes.
How to pick the right tools
Start with the outcome you need. If you’re exploring an idea, choose tools that let you iterate quickly. If you’re shipping to customers, choose tools that help you test and monitor quality.
- Compatibility: Works with the models you already use.
- Cost control: Clear usage tracking and simple ways to limit spend.
- Evaluation: Built-in testing so you can compare versions before launch.
- Team readiness: Collaboration, access controls, and audit trails when you need them.
A simple “ship it” workflow
- Draft the prompt and user flow in a sandbox.
- Connect the right data sources (docs, DB, or APIs).
- Test output quality with real examples before launch.
- Release behind a feature flag and monitor feedback.