Stigg is a usage runtime for AI products. It meters usage, manages entitlements, and monetizes AI features in real time, without building billing infrastructure. It provides a single enforcement layer for credits, entitlements, metering, and governance. Stigg is trusted by engineering teams operating at scale and complexity.
Best AI API Tools (2026)
Compare AI APIs and model gateways for adding LLMs, image generation, speech, and embeddings to your app — from single-provider endpoints to unified multi-model platforms.
Humalike provides behavioral infrastructure for humanlike AI agents, offering APIs, models, and benchmarks. It includes seven behavioral components—turn-taking, norms, persona, theory of mind, social observability, social memory, and social signals—that are model, use-case, and stack agnostic. These components are designed for both 1:1 and group interactions, enabling agents to feel human in various scenarios such as gaming, coworking, therapy, companionship, education, humanoids, and communities. Humalike emphasizes trust with SOC 2 Type II and ISO 27001 compliance in progress, and offers a free tier with $20 in credits for new accounts.
Related categories
What is an AI API?
An AI API is an HTTP endpoint you send a request to — a prompt, image, or audio — and get back a model's output, so you can add AI features without training or hosting models yourself. You authenticate with an API key and pay per token or per request. Some are single-provider (OpenAI, Anthropic, Google); others are gateways that route one request across many models.
What AI APIs offer
- REST and streaming endpoints for chat, image, and audio
- One API key routing across many model providers
- Token-based, pay-as-you-go pricing with usage dashboards
- Official SDKs for Python, JavaScript, and more
- Function calling, structured output, and tool use
- Rate limits, fallbacks, and OpenAI-compatible schemas
Who uses AI APIs
App developers
Add chat, summarization, or vision to a product without running your own model infrastructure.
Teams comparing models
Test GPT, Claude, Gemini, and open models behind one gateway to pick the best fit per task.
Cost and reliability optimizers
Route requests to cheaper or faster models and fail over automatically when a provider goes down.
Agent and automation builders
Wire function calling and tool use into agents, workflows, and backend jobs.
How AI APIs work
Your app sends an HTTPS request with an API key and a JSON payload — the prompt plus parameters like model and temperature — to the provider's endpoint. The model runs inference on their servers and returns the result, either all at once or streamed token by token. Gateways sit in front of several providers, translating one request format (often OpenAI-compatible) to whichever model you target and metering usage for billing.

