Unified management forenterprise AI API access
Kite Layer gives reviewed business customers a unified AI API gateway for model routing, usage controls, access management, and billing operations. Standardized interfaces, routing policies, usage analytics, and cost visibility help teams optimize model spend, improve access performance, and reduce multi-provider integration, operations, and finance complexity.
Built on top of every major model provider
Preview the request flow in your browser
Type any prompt to experience the streaming interface. This uses canned responses for the demo; real model calls require an API key from the console.
Where Kite Layer fits
"Consolidating providers behind one unified API entry point makes keys, quotas, and usage logs easier to manage."
"When model, cost, or reliability needs change, routing can move in the console while application code stays stable."
Get started in three steps, five minutes
Keep your application code stable while moving model access, routing, and controls into one gateway.
Request access and configure a key
After business account review, configure a Workspace and issue separate sk- keys for each project and environment.
# 1. Sign in & create a key
export KITELAYER_API_KEY="sk-..."Swap the base URL
Reuse the official OpenAI / Anthropic SDK. Just point base_url at Kite Layer — no code changes.
# 2. Point base_url at the gateway
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["KITELAYER_API_KEY"],
base_url="https://api.kitelayer.com/v1",
)Switch models freely
Use the model field and console policies to manage routing, fallback, quota, and team access.
# 3. Switch models with one field
client.chat.completions.create(
model="claude-opus-4-6",
messages=[...]
)Drop-in for the tools you already use
From CLI coding agents to desktop chat clients — copy, paste, and you're live without writing a line of code.
- 1
Install
npm install -g @anthropic-ai/claude-code - 2
Set env vars
Add to ~/.zshrc or ~/.bashrc and restart your shell
export ANTHROPIC_BASE_URL="https://api.kitelayer.com/v1" export ANTHROPIC_AUTH_TOKEN="$KITELAYER_API_KEY" - 3
Run
cd your-project claude - !
Tip
To switch between endpoints (official / Kite Layer / others), pair this with CCSwitch below.
Your existing SDK, zero changes
Designed for mainstream SDK workflows. Drop into curl, Python, Node, or model-specific SDKs by swapping the base URL.
curl https://api.kitelayer.com/v1/chat/completions \
-H "Authorization: Bearer $KITELAYER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-opus-4-6",
"messages": [{ "role": "user", "content": "Hello!" }]
}'Move AI API management out of application code
Unified model routing
Manage models and upstream channels in the console while applications keep a stable SDK-friendly interface.
Quota and access control
Separate keys by team, project, and environment, with quota, rate-limit, and disable controls.
Usage and cost visibility
Track usage by key, model, and user to support internal allocation and customer reconciliation.
Low-friction integration
Keep OpenAI-style SDK calls and migrate by changing the base URL and API key.
Why teams add an AI API control layer
For enterprise buying and operations, the difference is not just model count. It is integration effort, access governance, usage allocation, and billing operations.
Kite LayerPICK | Direct vendorsModel provider APIs | Self-hosted gatewayInternal code / OSS framework | |
|---|---|---|---|
Provider access Manage multiple upstreams and model capabilities | 40+multiple | 1single | requires setup |
Access governance Separate keys by team, project, environment, and customer | account-level | build needed | |
Integration effort Reduce SDK, account, and request-format differences | low | medium | high |
Routing and failover Choose models and backups by policy | policy-based | build needed | |
Usage allocation Allocate usage by key, model, project, and customer | scattered | build needed | |
Billing operations | quota/billing | vendor panels | build needed |
Organize model access by business workload
Manage routing across generation, reasoning, multimodal, retrieval, and private-route workloads. Final model availability and quota depend on console configuration.
General chat and content
For support assistants, knowledge Q&A, content generation, and product chat.
- Management
- Default route
- Routing
- Route by quality, latency, and cost with fallback models.
Reasoning and code
For complex reasoning, code generation, agent tasks, and multi-step workflows.
- Management
- High-value requests
- Routing
- Reserve stronger models for high-value requests and route routine work economically.
Multimodal understanding
Handle image understanding, document parsing, transcription, and video summaries.
- Management
- By input type
- Routing
- Choose model families by input type, request scale, and latency target.
Embeddings and rerank
Support RAG, semantic search, similarity matching, and knowledge retrieval.
- Management
- RAG pipeline
- Routing
- Manage retrieval, rerank, and generation separately for clearer allocation.
Local and regional providers
Connect regional providers and backup routes by customer, workload, or data boundary.
- Management
- Customer/region split
- Routing
- Separate keys, quota, and model policies by project and environment.
Open and private models
For self-hosted, private-provider, or dedicated model routes.
- Management
- Dedicated routes
- Routing
- Use one API layer for hosted and private models to reduce migration effort.
Estimate usage and model spend
Choose a reference model and projected token volume to plan budgets, quotas, and customer pricing. Final billing depends on console records, upstream prices, and customer agreements.
- Input
- $350.0
- Output
- $350.0
This estimate is for budget planning only. Actual costs may vary by routing policy, cache hits, provider pricing, and commercial terms.
- Plan quota by team, project, and customer.
- Compare cost impact across routing strategies.
- Final invoices follow console usage and agreed pricing.
Ready to onboard your business account?
Contact us to review your use case, service scope, and test environment before production use.