Stop Wasting Money onDuplicate LLM Calls
Set budget limits. Cache intelligently. Debug agents step-by-step.Integration = 2 lines of code. No SDK. No code rewrite.
10k requests/mo free · No credit card
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
+ baseURL: "https://proxy.watchllm.dev/v1",
+ defaultHeaders: { "X-WatchLLM-Key": process.env.WATCHLLM_KEY }
});
// That's it. Same code, same SDK.
// Automatic caching, tracing, cost controls, agent debugging.Works with every major LLM provider. Your keys, your billing, zero markup.
What Makes WatchLLM Different
Features your current tool doesn't have
Not another generic observability dashboard. These are production-grade capabilities that no other LLM proxy offers.
Prevent Runaway Agent Costs
Set a $5 budget per agent run. When the limit is hit, WatchLLM automatically terminates the run. No more waking up to $500 overnight surprises from infinite loops.
- Real-time cost tracking per agent run
- Automatic termination on budget breach
- Configurable alert thresholds
- Prevent $500 overnight surprises
// Set budget limits per agent run
const run = await watchllm.startAgentRun("research-agent", {
input: userQuery,
maxCost: 5.00, // Hard stop at $5
alertAt: 3.50, // Warn at $3.50
});
// Agent runs normally until budget reached
// → Automatic termination on limit breach
// → Real-time cost tracking in dashboardCustomer Billing Pass-Through
B2B EssentialTrack LLM costs per end-user or customer automatically. Export usage data for invoicing. Know exactly which customer costs how much.
Streaming Cache with Timing
Technical InnovationMost caching tools break streaming. WatchLLM replays SSE chunks with realistic timing preservation. Users can't tell it's cached.
Agent Debugger with Per-Step Costs
Developer FavoriteStep-by-step timeline of every agent action. Per-step cost attribution, cache hit/miss visibility, and infinite loop detection.
Integration
2 lines. That's the whole integration.
No SDK to install. No code to rewrite. Change your baseURL and add a header. Your existing OpenAI/Anthropic/Groq code works as-is.
1import OpenAI from "openai";23const openai = new OpenAI({4 apiKey: process.env.OPENAI_API_KEY,5});67const response = await openai.chat.completions.create({8 model: "gpt-4o",9 messages: [{ role: "user", content: "Explain React hooks" }],10 stream: true,11});1213// No caching. No cost tracking. No debugging.14// Every duplicate call = full price.1import OpenAI from "openai";23const openai = new OpenAI({4 apiKey: process.env.OPENAI_API_KEY,5 baseURL: "https://proxy.watchllm.dev/v1",6 defaultHeaders: { "X-WatchLLM-Key": process.env.WATCHLLM_KEY },7});89const response = await openai.chat.completions.create({10 model: "gpt-4o",11 messages: [{ role: "user", content: "Explain React hooks" }],12 stream: true,13});1415// Automatic: Caching, tracing, cost controls, agent debugging.16// Duplicates served from cache in <50ms at $0.00.Semantic Caching
Similar prompts return cached responses in <50ms. 95% accuracy.
Request Tracing
Latency, tokens, cost, and cache status for every call.
Cost Attribution
Per-endpoint, per-model, per-customer cost breakdown.
Agent Debugging
Step-by-step execution timeline with per-step costs.
Budget Limits
Set hard cost caps per run. Auto-terminate on breach.
Multi-Provider
OpenAI, Anthropic, Groq, OpenRouter. One base URL.
Platform Capabilities
Everything else you need in production
Beyond the unique features, WatchLLM covers the full production stack: tracing, security, compliance, and multi-provider routing.
Request-Level Tracing
Every LLM call is traced with latency breakdown, token count, cost attribution, and cache status. Stream data to your dashboard or export to your observability stack.
Verified Pricing (0% Variance)
21+ model pricing verified to the cent. Know exactly where every dollar goes. Per-endpoint, per-model, per-customer cost attribution.
Multi-Provider Routing
OpenAI, Anthropic, Groq, and OpenRouter through a single endpoint. Switch providers with a header change. Your keys, your billing, zero markup.
Semantic Deduplication
Vector-based similarity matching catches duplicate prompts even when worded differently. "What is France's capital?" matches "What's the capital of France?"
AES-256-GCM Encryption
All cached data encrypted with AES-256-GCM using PBKDF2-derived keys. Zero prompt storage on disk. API key leak prevention built in.
GDPR & Audit Compliance
Full audit trail for every request. GDPR-compliant data handling with configurable retention. Anomaly detection and alerting included.
ROI Calculator
See how much you'd save
Most teams see 40-70% cache hit rates within the first week.
Your usage
Cache hit rates depend on prompt repetition patterns. Customer support bots typically see 50-70%. Research agents see 30-40%.
Your savings
Why Trust WatchLLM
The product sells itself.
Read the docs and see.
Built by an engineer, for engineers
WatchLLM was built by a 16-year-old developer who got frustrated paying full price for duplicate LLM calls. Every feature solves a real problem from production use.
Self-hostable from day one
No vendor lock-in. Deploy WatchLLM in your own VPC with Docker. Same features as cloud. Your data never leaves your infrastructure.
Open documentation, transparent roadmap
Every feature is documented with real code examples. The changelog shows exactly what shipped and when. No marketing pages without substance.
Production architecture, not a weekend project
ClickHouse for analytics, Qdrant for vector search, edge-deployed proxy. Built to handle millions of requests with sub-50ms cache responses.
Built on proven infrastructure
Don't take our word for it. The technical documentation speaks for itself.
Security You Can Trust
Bank-level security for your API keys and sensitive data
SOC 2 Type II
Enterprise security controls
In ProgressAES-256-GCM
Military-grade encryption
ActiveGDPR Compliant
EU data protection
ActiveISO 27001
Information security
Planned Q2Security Features
Need a security review?
Request our security whitepaper or schedule a call with our team
Pricing
Transparent, usage-based pricing
Start free. Scale as you grow. No markup on provider API costs.
Estimate your ROI
See how much caching saves based on your current LLM spend.
Monthly savings from caching
$250
Recommended plan
Pro
Net savings after fee
$151
Break-even time
12 days
Annual savings
$1,812
Assumes an average of $0.002 per request to estimate volume. Adjust after signup.
Start building for free →Free
For side projects
- •10,000 requests/month
- •10 requests/minute
- •Basic semantic caching
- •7-day usage history
- •1 project
Exceeded your limit? No problem:
Cache-only mode after 10k requests (no additional charges)
Starter
For growing applications
- •100,000 requests/month
- •50 requests/minute
- •Advanced semantic caching
- •30-day usage history
- •Email support
Exceeded your limit? No problem:
$0.50 per 1,000 additional requests (up to 200k total)
Pro
For production workloads
- •250,000 requests/month
- •Unlimited requests/minute
- •Priority semantic caching
- •90-day usage history
- •Priority support
Exceeded your limit? No problem:
$0.40 per 1,000 additional requests (up to 750k total)
Agency
For high volume
- •10M+ requests/month
- •Custom rate limits
- •Dedicated infrastructure
- •Custom retention
- •SLA
Exceeded your limit? No problem:
Custom overage rates negotiated
FAQ
Frequently asked questions
Everything you need to know about WatchLLM.
Your LLM calls are costing
more than they should.
Add 2 lines of code. Get semantic caching, cost controls, agent debugging, and per-customer billing. Free up to 10,000 requests/month.