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Use cases / AI-powered apps

Build AI-native apps that solve real problems.

Ship AI-powered experiences on a backend that gives you data control, model freedom, and production-grade guardrails. Use AI to generate content, route work, surface insights, and make better decisions - powered by your live data.

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Powered by your live data your live data any model, your key guardrails Xano AI-native backend generate content route work surface insights decide
AI-powered apps

AI features on your live data, with guardrails and review

Xano keeps data governed and observable while letting you use the full power of modern AI models inside your app, so you can move fast and scale safely.

  1. 01 · Models

    LLM integration made simple

    Drop AI into existing flows with minimal code and maximum flexibility. Bring your own keys, standardize calls across models, and tune cost/latency per feature as you grow.

    • Bring-your-own-key for any provider (no lock-in)
    • Standardized request/response shapes across models
    • Tool calling for retrieval, actions, and structured outputs
    • Cost/latency controls per endpoint or environment
    Bring your own key provider A provider B provider C LLM call standard shape tool calling structured output cost / latency
  2. 02 · Context

    Structured context and memory

    Give models the right information at the right time - securely. Retrieve and filter live data, templatize prompts, and manage memory while protecting PII.

    • Retrieve from your DB or external stores with filters and guards
    • Prompt templates with variables and system instructions
    • Short- and long-term memory patterns you can tune
    • PII redaction and allow-lists for safe context
    Context and memory Retrieve from your DB, with filters Template variables, system instructions Remember short- and long-term memory Safe context PII redaction allow-lists guarded retrieval
  3. 03 · Workflows

    Readable workflows with AI inside

    Compose AI steps alongside business logic so features ship faster. Validate outputs against schemas, add human checkpoints where risk is higher, and A/B test safely.

    • Chain prompts, functions, and evaluators in one place
    • Validate outputs against schemas before they propagate
    • Human-in-the-loop checkpoints for risky operations
    • A/B test prompts and models without code forks
    AI inside the workflow Prompt Function Evaluator Schema check Human checkpoint Ship safely outputs validated A/B test prompts A/B test models
  4. 04 · Review

    Human + AI collaboration

    Let people review, override, or approve AI outcomes where it matters most. Built-in queues, diffs, and feedback loops raise quality and make compliance straightforward.

    • Assignment, escalation, and SLAs for review queues
    • Inline diffs and rationales to speed decisions
    • Feedback loops that improve prompts and rules
    • Event logs for compliance and post-mortems
    Review queue item AI outcome status refund request approve + rationale approved contract clause flagged, inline diff escalate support reply edited by reviewer override feedback prompt rule updated logged
  5. 05 · Production

    Production-ready from day one

    Operate AI features with the same standards as the rest of your stack. Observe every call, enforce guardrails, and manage policy and costs centrally.

    • Observability: traces, logs, metrics per call/model
    • Guardrails: conditional logic, agent triggers, and agent history
    • Policy: role-based access and consent tracking
    • Routing: direct traffic to the right model for the task
    Production standards Same rules as the rest of your stack Observability traces, logs, metrics per call Guardrails agent triggers and history Policy role-based access, consent Routing the right model for the task

AI builds software. Xano makes it trustworthy.

Build your backend in TypeScript with AI. Your coding agent writes it with the Xano SDK, you run it on the Xano Engine on your machine, then deploy it to Xano.

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