Collect and analyze all of your LLM usage, in one spot , and build better products.
Everything you need to understand, debug, and improve your LLM applications with precision and confidence
Track every request, response, and performance metric across all your language model interactions with millisecond precision.
Identify and analyze potential hallucinations in your LLM outputs with advanced pattern recognition and AI-powered validation.
Powerful search and filtering capabilities to quickly find specific interactions, errors, or patterns in your massive datasets.
Comprehensive API documentation with examples, guides, and everything you need to integrate Siloam AI
package main
import (
"bytes"
"encoding/json"
"fmt"
"net/http"
"os"
)
func main() {
// Log an AI interaction
payload := map[string]interface{
"model": "gpt-4",
"input": "What is machine learning?",
"output": "Machine learning is a subset of AI...",
"sessionId": "session-123",
"tokens": 150,
"cost": 0.003,
}
data, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", "https://demo.siloam.ai/api/log", bytes.NewBuffer(data))
req.Header.Set("Authorization", "Bearer "+os.Getenv("SILOAM_API_TOKEN"))
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, _ := client.Do(req)
defer resp.Body.Close()
var result map[string]string
json.NewDecoder(resp.Body).Decode(&result)
fmt.Println("Log ID:", result["id"])
}Start free and scale as you grow. No hidden fees, no surprises.