One AI API for developers, applications and bots

AI API architecture for web and mobile products

The browser or mobile app should call your backend, not the model gateway directly. Your backend authenticates the user, checks tenant permissions, limits payload size and chooses an allowed model before calling CLODEX. This keeps the main API key out of distributed client code.

Create separate keys for each environment and major product function. Usage logs then show whether support chat, document extraction or an internal coding tool generated the spend, and one key can be revoked without stopping unrelated features.

Common AI API use cases

Each use case needs its own quality tests and budget. A single generic prompt is not a production evaluation. Build a representative dataset, define acceptable failures and measure cost per completed business task.

• Customer support assistants with retrieval and human escalation.
• Document classification, extraction and summarization.
• Telegram and community bots with server-side authorization.
• Coding assistants, code review and test generation.
• Content workflows with structured output and approval steps.

Multi-tenant security and tool permissions

Model authentication proves that your backend may call the API; it does not authorize an end user to read a document, send an email or update a customer record. Recheck ownership and role after every tool request. Treat model-generated arguments as untrusted input.

Use an allowlist of tools, JSON Schema validation and idempotency keys. Destructive or financial operations should require an additional confirmation step. Log safe metadata while avoiding raw secrets and sensitive prompts unless retention is explicitly required.

Cost, latency and reliability controls

Track input, cached input, output, model, request count, error rate and terminal status by product feature. This supports unit-economics decisions and detects a runaway loop before it consumes the shared balance.

Set timeouts and bounded retries, but distinguish connect failures from partially completed streams. If output or a tool action already occurred, a blind retry can duplicate work. Preserve request IDs and failure phases for operational review.

Review data-retention and regional privacy requirements before sending customer content to any model. Minimize prompts, remove unnecessary personal data and document which application features may transmit files or conversation history through the gateway.

• Set per-tenant and per-feature budgets.
• Limit concurrency for expensive long-context tasks.
• Use explicit, tested fallbacks.
• Alert on error rate and unusual spend growth.