One Intelligent Gateway for Every AI Interaction
A single control plane that routes every query between local models, public LLMs, and MCP servers — optimizing for cost, latency, and compliance automatically. Less than 2ms overhead.
A single control plane that routes every query between local models, public LLMs, and MCP servers — optimizing for cost, latency, and compliance automatically. Less than 2ms overhead.
Sound Familiar?
If your teams are using AI without a central gateway, you're likely facing these problems today.
Teams default to expensive frontier models for simple tasks. Nobody knows what each department spends, and there's no way to enforce cost-efficient routing.
Every team manages its own provider relationships, API keys, and billing. IT has no inventory, no central access control, and no way to revoke credentials at scale.
When a provider goes down, your AI-powered workflows go down with it. There's no automatic fallback, no retry logic, and no routing around outages.
There's no routing logic to keep confidential queries on-premises. Customer data, proprietary code, and financial records flow to cloud LLMs by default.
You can't see which models are being called, how many tokens are consumed, or what the per-query cost is. When something breaks, there's no trace to debug.
No audit trail for AI interactions means no way to prove compliance. Regulated industries need a record of every query, every model decision, and every response.
Architecture
If your teams are using AI without a central gateway, you're likely facing these problems today
Capabilities
Each component works together to give you cost control, performance, access governance, and data sovereignty — out of the box.
Automatically directs queries to the optimal model or MCP server based on task complexity, cost, and latency targets. No manual selection required.
✓ Complexity-aware model matching
✓ Routes across LLMs, local models, and MCP servers
✓ Automatic failover across providers
✓ Custom routing rules per department
Prompt compression, model weight arbitrage, local LLM offloading, and real-time per-department billing visibility — reducing spend by an average of 60%.
✓ Prompt compression & token optimization
✓ Model output arbitrage across providers
✓ Per-department billing & cost dashboards
✓ Local LLM offloading for simple tasks
Role-based permissions restrict which teams can access which models, with full audit logging for every single request flowing through the gateway.
✓ Role-based model access permissions
✓ Department-level usage quotas
✓ Full audit trail for every interaction
✓ SSO / SAML integration
Route data through the gateway to train local LLMs, ensuring sensitive information never leaves your infrastructure while improving model performance.
✓ On-premises model hosting & training
✓ Data residency controls by geography
✓ Sensitive data auto-routed to local models
✓ Air-gapped deployment support
Integration
The Gateway is fully compatible with the OpenAI API format. Switch your base URL, and all existing code works instantly — no SDK changes, no refactoring. You gain routing, optimization, and governance with one line.
🔴🟡🟢 gateway-example.com
from openai import OpenAI
client = OpenAI( base_url="https://gateway.optscale.ai/v1", api_key="kf-your-api-key" )
response = client.chat.completions.create(
model="auto", # Gateway picks the best model
messages=[{ "role": "user", "content": "Summarize Q3 revenue trends" }],
max_tokens=1000)
print(response.choices[0].message.content)
# Model used: llama-3-8b (routed by gateway)
# Cost: $0.0003 (vs $0.012 with GPT-4)
# Latency: 340ms
Explore the Platform
Ready to Centralize Your AI?
Start free with up to 5 seats. Deploy the gateway in hours, see cost savings within weeks.
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