🚀 Limited Early Access Available

Agents That Learn
in Production

Turn every failure into a lesson. Patch and improve agents in minutes, not weeks.

Join 500+ developers already on the waitlist • No spam, ever

+40%
Accuracy
Adapts instantly
–80%
Token Costs
Leaner agents
10×
Faster Learning
Live improvements

The Problem with Current AI Agents

Traditional development cycles leave agents failing in production for weeks

Eval suites can't predict real users.

Your carefully crafted test cases miss the edge cases that real users hit every day.

Deploys happen every 1–2 weeks.

Traditional ML cycles are too slow for the fast-moving pace of production issues.

That leaves your agents failing silently in production.

Users experience poor performance while you wait weeks to identify and fix issues.

The Traditional Cycle

Deploy
Ship to prod
📊
Eval
Looks good
⚠️
OOD Use Case
Reality hits
💥
2 Weeks of Fails
Users suffer
🔄
Next Deploy
Finally fix it

Revolutionary Agent Architecture

🧠

Persistent Memory Architecture

Our memory system maintains context across executions, enabling agents to build upon previous interactions and develop deeper understanding over time.

Vector Storage
Semantic search & retrieval
Hierarchical Org
Short & long-term memory
Context Preservation
Relationship mapping
Auto Pruning
Optimized performance
📊

Token Efficiency

Smart memory indexing reduces token usage by up to 80%

80%
Reduction in costs
🎯

Reality as Classroom

By using real-world interactions as the training environment, agents develop practical intelligence that translates directly to improved performance.

Learning Pipeline
InteractionFeedbackMemoryImprovement

Real-time Learning

Continuous improvement through reality-based RL

Continuous adaptation
Error correction
🔄

Seamless Integration

Easy integration with existing LLM frameworks and tools

OpenAIClaudeLlamaCustom
📈

Performance Metrics

Track and optimize agent effectiveness with detailed analytics

Accuracy+40%
Speed10x
Cost-80%

Who It's For

Built for teams deploying vertical AI agents in production who need their agents to improve continuously

🏢

SaaS Companies

Building AI copilots and assistants that need to understand domain-specific context and improve with each customer interaction

🏥

Healthcare & Legal Tech

Deploying specialized agents that learn from real cases and adapt to regulatory requirements over time

💼

Enterprise Teams

Running production agents for customer support, sales, or operations that need to learn from every interaction

🚀

AI-First Startups

Building vertical AI products where agent performance directly impacts customer value and retention

🔧

DevTools & Infrastructure

Creating coding assistants and DevOps agents that learn from your codebase and deployment patterns

📊

Data & Analytics Teams

Operating agents that process complex queries and learn to provide better insights with each analysis

Your Agents Learn Between Deployments

InferenceIndex enables automatic learning between deployments. Your agents analyze production interactions and improve continuously without manual retraining cycles - just deploy and watch them get smarter.

Learns between deployments
No manual retraining
Automatic improvement

Simple, Transparent Pricing

Scale with your usage. No surprise bills.

Developer

Free

Perfect for testing and small projects

  • Up to 100 patched sessions/mo
  • Core memory architecture
  • Community support
POPULAR

Professional

$500
/month

For small teams getting started

  • $0.01 per patched session
  • Advanced analytics
  • Priority support
  • Custom integrations

Enterprise

$20k+
/month

Scale with volume, predictable costs

  • Capped at $30k/mo maximum
  • Volume-based pricing
  • Dedicated support
  • Custom deployment

Be Among the First to Experience the Future

Join our exclusive waitlist and get early access to revolutionary AI agent technology.

500+ developers already on the waitlist

No credit card required • Early bird pricing available