UNIFIED LLM GATEWAY

Unified API.
Predictive Intelligence.

Don't just routeโ€”predict. Metis Prism analyzes prompt complexity and forecasts costs before execution, giving you the control to optimize latency and budget across every provider.

15+
LLM Providers
40%
Cost Reduction
99.99%
Uptime via Failover
<50ms
Routing Overhead
๐Ÿ”ฎ

Predictive Routing

Route based on Forecasted Metrics.

Most gateways route blindly. Our Foresight Engine inspects request complexity in real-time to predict the tokens required.

It automatically directs simpler queries to faster, cost-effective models while reserving frontier models for complex reasoning tasksโ€”optimizing your total cost of ownership (TCO) without sacrificing quality.

Semantic
Task Classification
Real-time
Cost Optimization
Prompt Complexity:Simple (Translation)
Routed to:Claude 3 Haiku
Cost Savings:92% vs Claude Opus
Quality:98% equivalent
Monthly Savings Example
$12,400
on 1M requests/month with semantic routing
# ๐Ÿš€ Drop-in Compatible with OpenAI SDK
import openai

client = openai.OpenAI(
    base_url="https://api.metisprism.ai/v1",
    api_key="sk-metis-..."
)

# Works exactly like OpenAI, but routes intelligently
response = client.chat.completions.create(
    model="router-pro", # Automatically routes to GPT-4/Claude/Gemini
    messages=[{"role": "user", "content": "Analyze this dataset..."}]
)
๐Ÿ”Œ

Zero-Code Intelligence

Upgrade Without Rewriting.

Avoid vendor lock-in without the refactoring headaches. Our gateway provides a drop-in OpenAI-compatible endpoint, so you can inject Foresight intelligence into your existing applications instantly.

  • โœ“OpenAI Compatible: Drop-in replacement for existing OpenAI SDK calls.
  • โœ“Streaming Support: Full SSE streaming across all providers.
  • โœ“Function Calling: Unified tool use interface for all models.
๐Ÿ›ก๏ธ
Failover Sequence
โœ—OpenAI API503 Service Unavailable
โ†’Failover to AnthropicAttempting...
โœ“Claude 3.5 Sonnet200 OK (142ms)
User experienced zero downtime
๐Ÿ”„

Automatic Failover

99.99% Uptime. Zero Code Changes.

Provider outages happen. Rate limits hit. Our gateway automatically fails over to equivalent models from other providers. Your users never notice.

  • โœ“Health Monitoring: Real-time provider health checks with latency tracking.
  • โœ“Smart Retry: Exponential backoff with circuit breaker for chronic failures.
  • โœ“Model Mapping: Automatic mapping to equivalent capability models.
๐Ÿ›ก๏ธ

Aegis Governance

Enterprise-grade controls for LLM usage. Budget limits, content policies, and full audit trails.

๐Ÿ’ฐ

Budget Controls

Set spending limits per team, project, or API key. Real-time alerts before you hit limits. Never get surprised by a bill again.

๐Ÿ”’

Content Policies

Block PII, detect prompt injection, filter sensitive topics. Policies propagate to all providers automatically.

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Full Audit Trail

Every request logged with user, cost, latency, and provider. SOC2-compliant retention and export.

All Your LLMs. One Place.

First-class support for frontier models and open-source. Bring your own API keys or use ours.

Anthropic

  • Claude 3.5 Sonnet
  • Claude 3 Opus
  • Claude 3 Haiku

OpenAI

  • GPT-4o
  • GPT-4 Turbo
  • o1-preview

Google

  • Gemini 1.5 Pro
  • Gemini 1.5 Flash

AWS Bedrock

  • Claude
  • Llama 3
  • Titan

Meta

  • Llama 3.1 70B
  • Llama 3.1 8B

Mistral

  • Mistral Large
  • Mistral Medium
  • Mixtral

Cohere

  • Command R+
  • Command R

Self-Hosted

  • vLLM
  • Ollama
  • TGI

Built for Developers

OpenAI-compatible endpoint means zero learning curve. SDKs for Python, TypeScript, and Go.

# Python SDK
from metisprism import LLMGateway

# Initialize with your org's gateway
gateway = LLMGateway(api_key="pk_...")

# Simple completion - routes automatically
response = gateway.complete(
    model="auto",  # Let gateway choose optimal model
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain quantum computing."}
    ],
    routing={
        "strategy": "cost_quality_balanced",
        "max_cost_per_request": 0.05,
        "min_quality_score": 0.9,
    }
)

print(f"Model used: {response.model}")  # e.g., "claude-3-5-sonnet"
print(f"Cost: ${response.usage.cost_usd:.4f}")
                        print(f"Content: {response.choices[0].message.content}")

Ready to Unify Your LLMs?

Stop juggling API keys. Start routing intelligently. One gateway for all your LLM needs.