# ZenLLM

> ZenLLM is an AI spend optimization platform that helps engineering teams find wasted LLM tokens from prompt bloat, context accumulation, model overuse, retry churn, and routing mistakes.

## Canonical
- https://www.zenllm.io

## Key pages
- Home: https://www.zenllm.io/
- Pricing: https://www.zenllm.io/pricing
- No-signup usage export analyzer: https://www.zenllm.io/upload-usage-export
- Free assessment: https://www.zenllm.io/assessment
- About: https://www.zenllm.io/about
- OpenAI cost optimization: https://www.zenllm.io/openai-cost-optimization
- Anthropic cost optimization: https://www.zenllm.io/anthropic-cost-optimization
- LLM FinOps: https://www.zenllm.io/llm-finops
- AI spend benchmark: https://www.zenllm.io/ai-spend-benchmark
- Workflow cost attribution: https://www.zenllm.io/ai-cost-per-workflow
- Model routing optimization: https://www.zenllm.io/model-routing-optimization
- Prompt caching ROI: https://www.zenllm.io/prompt-caching-roi
- Free LLM cost calculator: https://www.zenllm.io/llm-cost-calculator
- Partner program: https://www.zenllm.io/partners
- Partner AI spend review template: https://www.zenllm.io/partner-ai-spend-review-template
- Developer onboarding: https://www.zenllm.io/developers/onboarding
- Security overview: https://www.zenllm.io/security

## Direct answers
- AI spend answers hub: https://www.zenllm.io/answers
- AI spend optimization: https://www.zenllm.io/answers/ai-cost-leak-detection
- Context accumulation and LLM cost: https://www.zenllm.io/answers/context-accumulation-llm-cost
- Prompt bloat and LLM cost: https://www.zenllm.io/answers/prompt-bloat-llm-cost
- Retry churn and LLM cost: https://www.zenllm.io/answers/retry-churn-llm-cost
- How to reduce OpenAI costs: https://www.zenllm.io/answers/reduce-openai-costs
- AI spend optimization: https://www.zenllm.io/answers/ai-spend-optimization
- LLM cost monitoring: https://www.zenllm.io/answers/llm-cost-monitoring
- LangSmith alternative for cost visibility: https://www.zenllm.io/answers/langsmith-alternative-cost-visibility
- Helicone alternative for finance teams: https://www.zenllm.io/answers/helicone-alternative-finance-teams
- AI spend audit template: https://www.zenllm.io/answers/ai-spend-audit-template
- AI FinOps for MSPs: https://www.zenllm.io/answers/ai-finops-for-msps
- LLM cost attribution by workflow: https://www.zenllm.io/answers/llm-cost-attribution-by-workflow
- LLM observability SDK setup: https://www.zenllm.io/answers/llm-observability-sdk-setup
- Reduce LLM cost with model routing: https://www.zenllm.io/answers/reduce-llm-cost-with-model-routing

## Index feeds
- Static sitemap: https://www.zenllm.io/sitemap.xml
- Published analysis sitemap: https://www.zenllm.io/blog/sitemap.xml
- Answer sitemap: https://www.zenllm.io/answers/sitemap.xml
- Guide sitemap: https://www.zenllm.io/guides/sitemap.xml

## Product summary
- Category: AI spend optimization / LLM cost optimization
- Audience: engineering leaders, platform teams, AI product teams
- Supported providers: OpenAI, Azure OpenAI, Amazon Bedrock, Google Vertex AI
- Primary outcomes: find unnecessary token spend, identify the workflows causing it, and prioritize fixes with estimated savings
- Differentiator: detect context accumulation, retry churn, model routing waste, and prompt bloat instead of stopping at a provider invoice

## How ZenLLM works
1. Upload a usage export for a no-signup first-pass waste estimate.
2. Ingest LLM request telemetry through the SDK for ongoing monitoring.
3. Attribute spend by provider, model, workflow, team, and customer.
4. Detect context accumulation, model waste, retry churn, and cost anomalies.
5. Recommend lower-cost routing strategies with estimated savings.

## Contact
- Website: https://www.zenllm.io
- Email: eli.katz@zenllm.io