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About
Not Diamond is a continuous learning infrastructure platform designed for AI developer teams operating at the frontier. It provides three core capabilities: intelligent routing, prompt optimization, and agent optimization — all working together to maximize the performance and efficiency of AI-powered workflows. Intelligent Routing uses ultra low-latency runtime prediction to select the best model for each individual query, dynamically balancing accuracy, cost, and latency across all leading language models. Prompt Optimization automatically refines static prompt templates across any model and provider, outperforming days of manual engineering in minutes of background processing. Agent Optimization applies self-improving algorithms to multi-step agentic workflows, compounding accuracy gains across long-running agent trajectories. Not Diamond integrates seamlessly into existing stacks — it is stack-agnostic and supports existing orchestration gateways, models, and evaluation pipelines via a secure API or private environment deployment. The platform is SOC-2 and ISO 27001 compliant, with zero data retention (ZDR) policies, VPC deployments, and 24/7 enterprise support. Trusted by companies like OpenRouter, Rootly, and Replicated, Not Diamond has demonstrated up to 50%+ accuracy gains, 40x faster dev cycles, and 100x cost savings in production workloads.
Key Features
- Intelligent Model Routing: Ultra low-latency runtime prediction that selects the optimal AI model for each query, balancing accuracy, cost, and latency across all leading LLMs.
- Automatic Prompt Optimization: Automatically optimizes static prompt templates across any model and provider in minutes, replacing days of manual prompt engineering.
- Agent Optimization: Self-improving algorithms that continuously improve multi-step agentic workflows, boosting success rates across long-running agent trajectories.
- Stack-Agnostic Integration: Plugs into existing orchestration gateways, model providers, and evaluation pipelines via a secure API or private environment deployment.
- Enterprise-Grade Security & Compliance: SOC-2 and ISO 27001 compliant with ZDR policies, VPC deployments, and 24/7 support for the most demanding AI teams.
Use Cases
- Routing LLM queries dynamically across multiple model providers to maximize accuracy while minimizing API costs in production applications.
- Automatically optimizing prompt templates for customer-facing AI features without manual iteration by ML or prompt engineering teams.
- Improving the reliability and success rate of multi-step AI agents in incident management, DevOps automation, or enterprise workflow tools.
- Accelerating AI product development cycles by automating performance tuning that would otherwise require days of experimentation.
- Deploying AI infrastructure in regulated industries that require SOC-2/ISO 27001 compliance and private VPC environments.
Pros
- Dramatic Performance Gains: Proven results in production — 50%+ accuracy improvements, 40x faster dev cycles, and up to 100x cost savings reported by enterprise customers.
- Minimal Integration Overhead: Stack-agnostic design means it slots into existing workflows without requiring major architectural changes.
- Enterprise Security: SOC-2 and ISO 27001 compliance with flexible deployment options (VPC, ZDR) makes it suitable for regulated industries and sensitive workloads.
- Continuous Self-Improvement: The platform learns and adapts over time, meaning AI systems improve automatically without constant manual tuning.
Cons
- Enterprise-Focused Pricing: Primarily targeting large or well-funded AI teams; pricing and access may not be accessible to individual developers or small projects.
- Demo-Gated Onboarding: Full access appears to require booking a demo, which slows down self-serve experimentation for new users.
- Dependency on External Models: Value is contingent on the breadth and quality of the underlying model ecosystem; teams locked to a single model may see limited routing benefit.
Frequently Asked Questions
What is Not Diamond and what problem does it solve?
Not Diamond is a continuous learning infrastructure layer that automatically routes AI queries to the best model, optimizes prompts, and improves agentic workflows. It solves the problem of manually managing performance and cost tradeoffs across a rapidly evolving multi-model AI landscape.
How does intelligent routing work?
Not Diamond's routing engine uses ultra low-latency runtime prediction to evaluate each incoming query and select the model most likely to produce the best result, factoring in configurable tradeoffs between accuracy, latency, and cost.
Do I need to change my existing AI stack to use Not Diamond?
No. Not Diamond is designed to be stack-agnostic and integrates with your existing orchestration gateways, model providers, and evaluation pipelines via a secure API or a private environment deployment.
Is Not Diamond secure and compliant?
Yes. Not Diamond is SOC-2 and ISO 27001 certified and offers zero data retention (ZDR) policies and VPC deployments for teams with strict security requirements.
What kind of results can teams expect?
Production customers have reported accuracy gains of 50%+, development cycles accelerating by 40x, and cost savings of up to 100x, depending on the complexity and volume of their AI workloads.
