The Problem
Your prompts deserve an operations layer.
Prompt Management
Version-controlled prompts with full history. Branch, diff, and merge like code. Every prompt in your multi-agent system lives in one place with instant rollback and team collaboration built in.
promptops.register({
name: "support-agent-v2",
model: "claude-sonnet",
prompt: systemPrompt,
tags: ["support", "production"]
});
// Branch for experimentation
const branch = await prompt.branch(
"experiment/tone-shift"
);Self-Optimization
Define your objective. PromptOps iteratively rewrites, tests, and scores your prompts using execution feedback. Every optimization cycle makes your prompts measurably better.
const result = await promptops.optimize({
prompt: "support-agent-v2",
dataset: "customer-tickets-q4",
objective: "accuracy",
iterations: 50
});
// Result: accuracy 0.73 → 0.91
console.log(result.improvement); // +24.6%LLM Benchmarking
Run your prompts against every major LLM using your own datasets. Get accuracy, latency, and cost metrics side by side. Make data-driven decisions about which model to deploy.
const results = await promptops.benchmark({
prompt: "support-agent-v2",
models: [
"gpt-4o", "claude-sonnet",
"gemini-pro", "llama-3.1-70b"
],
dataset: "customer-tickets-q4",
metrics: ["accuracy", "latency", "cost"]
});Production Deploy
Deploy the winning prompt-model combination to production. Canary rollouts, real-time monitoring, and instant rollback. Your prompts go live with confidence.
await promptops.deploy({
prompt: "support-agent-v2",
model: results.best.model,
strategy: "canary",
monitoring: {
latency: { max: "2s" },
accuracy: { min: 0.85 },
},
rollback: "automatic"
});See the transformation.
You are a helpful customer support agent. Answer questions about our product. Be nice and professional. If you don't know something, say so.
You are a concise product specialist for {{product_name}}.
RULES:
- Answer in ≤3 sentences
- Cite documentation links when available
- Escalate billing issues to human agents
- Never speculate about unreleased features
CONTEXT: {{relevant_docs}}
USER TIER: {{user_tier}}| Model | Accuracy | Latency | Cost/req |
|---|---|---|---|
| ▸Claude Sonnet | 0.91 | 1.2s | $0.003 |
| GPT-4o | 0.82 | 1.8s | $0.005 |
| Gemini Pro | 0.78 | 0.9s | $0.002 |
| Llama 3.1 70B | 0.74 | 0.7s | $0.001 |
0%
Avg. accuracy improvement
0+
LLMs supported
0x
Faster than manual tuning
0%
API uptime