Use case

LLM API for SaaS Products

Ship AI-powered features to your SaaS users without managing multiple provider accounts, building failover logic, or worrying about surprise bills.

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You only pay credits per request. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

First success in 60 seconds
Step 01Sign up in 10 secondsGet 40 free creditsStep 02Open your dashboardCreate API keyStep 03Send first requestRun a sample
Why teams start here first
No monthly subscription
Pay-as-you-go credits
Start with trial credits, then buy only what you consume.
Failover safety
Production-ready routing
Auto fallback across providers when latency, quality, or reliability changes.
Data control
Your policy, your choice
BYOK and zero-retention mode keep training and storage scope explicit.
Single API experience
One key, multi-provider access
Use Chat/Compare/Blend/Judge/Failover from one dashboard.
Common problem
Integrating multiple LLM providers requires separate SDKs, API keys, billing accounts, and error-handling logic, which slows feature development and increases maintenance burden.
Common problem
A single provider outage can take your AI features offline, frustrating users and eroding trust in your product's reliability.
Common problem
LLM costs are unpredictable and hard to allocate across features or customers, making it difficult to price AI features profitably.

How LLMWise helps

✓One API key gives you access to nine models across five providers with OpenAI-style messages (role + content), so you integrate once and ship AI features faster.
✓Mesh failover with circuit breakers keeps your AI features online even when individual providers go down, delivering the uptime SaaS customers expect.
✓Credit-based pricing with per-feature budgets lets you allocate AI spend precisely, making it straightforward to price AI features in your own plans.
✓Optimization policies analyze your real usage data and recommend the best model for each feature, reducing cost while maintaining quality as your product scales.
Evidence snapshot

LLM API for SaaS Products implementation evidence

Use-case readiness across problem fit, expected outcomes, and integration workload.

Problems mapped
3
pain points addressed
Benefits
4
outcome claims surfaced
Integration steps
4
path to first deployment
Decision FAQs
5
adoption blockers handled

Integration path

  1. Sign up for LLMWise and get your API key. You receive 40 free trial credits immediately, enough to prototype and test your first AI feature end to end.
  2. Install the LLMWise SDK (Python/TypeScript) or call POST https://llmwise.ai/api/v1/chat directly. If your app already uses role/content messages, you can reuse your payloads and prompts with minimal changes. Send your first request using Chat mode to verify the integration.
  3. Configure model routing for each feature: use Auto mode for intelligent routing, or specify exact models per endpoint. Set up Mesh mode on critical paths for automatic failover.
  4. Connect LLMWise to your billing system by tracking credit usage per customer or feature. Use the Usage API to pull consumption data for your own dashboards and invoicing.
Example API call
POST /api/v1/chat
{
  "model": "auto",
  "messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "..."}
  ],
  "stream": true
}
Example workflow

A typical SaaS integration starts with a classification request using Claude Haiku 4.5 to determine the complexity of the user's input. Simple queries like FAQ lookups route to Gemini 3 Flash for a fast, cost-efficient response. Complex queries that require deep reasoning route to GPT-5.2 or Claude Sonnet 4.5. If the primary model is unavailable, Mesh failover automatically redirects to the next model in the chain within 300 milliseconds. Throughout this flow, LLMWise tracks per-request cost and latency, feeding data back into the optimization policy that continuously tunes the routing thresholds.

Why LLMWise for this use case

LLMWise is purpose-built for SaaS teams that need to ship AI features without building a model orchestration layer from scratch. A single API with OpenAI-style messages (role + content) eliminates multi-provider integration complexity, credit-based pricing maps cleanly to per-customer billing, and optimization policies automatically right-size your model selection as usage patterns evolve — so your AI spend scales with your revenue, not ahead of it.

Common questions

Can I use LLMWise alongside my existing direct provider integration?
Yes. Many SaaS teams adopt LLMWise incrementally. Start by routing one feature through LLMWise while keeping others on direct integrations. Because the message format is familiar and the integration is just HTTP/JSON (or the SDK), you can migrate feature by feature without a rewrite.
How does credit-based pricing map to my own SaaS pricing?
Each LLMWise operation has a fixed credit cost: Chat costs 1 credit, Compare costs 3, Blend costs 4, and Judge costs 5. You can map these to your own usage tiers or per-seat plans by tracking credits consumed per customer via the Usage API.
What happens if I exceed my credit balance?
LLMWise returns a 402 status code when credits are exhausted, so your application can handle it gracefully with a user-facing message or automatic top-up. You can add paid credits at any time with no subscription, and paid credits do not expire.
What is the best LLM API for SaaS products?
The best LLM API for SaaS depends on your requirements for reliability, cost control, and model flexibility. LLMWise is designed specifically for SaaS integration: it provides one API key that accesses nine models across five providers using OpenAI-style messages, includes automatic failover so your AI features never go down due to a single provider outage, and offers credit-based billing that maps directly to your own pricing tiers. Unlike direct provider APIs, you get multi-model orchestration without managing multiple SDKs or accounts.
How do I add AI features to my SaaS product without vendor lock-in?
Use an abstraction layer like LLMWise that provides a provider-agnostic API. LLMWise uses OpenAI-style messages (role + content), so your prompts stay portable across models, and you can switch from GPT-5.2 to Claude Sonnet 4.5 or Gemini 3 Pro by changing a single model parameter. If you ever want to migrate away from LLMWise itself, your message format and prompts remain standard JSON over HTTP, so the change is usually swapping your client and endpoint rather than rewriting your product logic.

One wallet, enterprise AI controls built in

You only pay credits per request. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

Chat, Compare, Blend, Judge, MeshPolicy routing + replay labFailover without extra subscriptions
Start free with 40 creditsSee pricing examples
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