ResonanceEngine — Score how well two texts resonate (semantic, intent, emotion, brand)

#ai #api #llm #testing

Stop shipping AI features blind. ResonanceEngine tells you exactly how well two texts resonate — whether that's a model output vs. expected answer, a chatbot reply vs. brand voice, or a generated email vs. the user's intent.

Why developers use it

LLMs are non-deterministic. You need a fast, calibrated way to measure "did the output actually match what we wanted?" — without hand-grading every response.

ResonanceEngine gives you a 0–100 score plus aligned/misaligned signals, in four modes:

🧠 Semantic — do the texts mean the same thing?
🎯 Intent — does the response fulfill the user's actual goal?
❤️ Emotional — does the tone match (warm, urgent, calm)?
🎨 Brand — does it sound like your brand voice?

Use cases

QA on AI responses — flag low-scoring outputs before they ship
Prompt evaluation — A/B test prompts with objective scoring
Content guardrails — block off-brand or off-intent generations
Chatbot evals — measure response quality at scale
RAG validation — does the answer actually match the retrieved context?

Quick start

curl -X POST 'https://resonance-engine.p.rapidapi.com/resonance-engine-evaluate' \
  -H 'x-rapidapi-key: YOUR_KEY' \
  -H 'x-rapidapi-host: resonance-engine.p.rapidapi.com' \
  -H 'Content-Type: application/json' \
  -d '{
    "source": "I need help fast, my server is down",
    "target": "Sure! Here is a 12-step guide to server architecture",
    "mode": "intent"
  }'