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Harshad Jadav
Harshad Jadav

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Stop Using 2,000ms LLMs for Simple Choices: Introducing Laya (<35ms Free AI Decision API)

Every day, developers wire up massive generative Large Language Models (like GPT-4o, Claude 3.5, or Gemini) to make simple classification decisions:

  • "Is this support ticket about billing, technical issues, or account management?"
  • "Is this incoming user prompt an injection or jailbreak attack?"
  • "Is this customer message spam or legitimate?"

The Problem with Generative LLMs in Workflows

Generative models generate text token-by-token. For simple structured tasks, this introduces:

  1. Unnecessary Latency: 1,500ms to 3,500ms spent waiting for completion.
  2. Formatting Drift & Hallucinations: Even with structured output prompts, generative models can fail to conform strictly to enums or output unwanted conversational filler.
  3. Compounding Costs: High per-token pricing rapidly accumulates in automated queues (n8n, Make, Kafka, or backend microservices).

The Solution: System 1 Non-Generative AI

To solve this, I built Laya AI Decision Gateway.

Inspired by cognitive "System 1" thinking (fast, automatic, and deterministic), Laya uses a non-autoregressive 322M parameter multilingual bidirectional encoder (mmBERT).

Instead of generating text, it maps inputs into high-dimensional vector spaces and computes calibrated categorical probabilities in a single mathematical forward pass in RAM (< 35 milliseconds).


⏱️ Latency Benchmarks: Model vs. Public Gateway

Transparency in AI latency is essential. Here are our measured numbers:

Layer Measured Latency Technical Explanation
Foundational Model Core < 35 ms Pure tensor mathematical execution of the 322M mmBERT encoder in RAM.
Direct Edge Microservice ~40 ms – 70 ms Direct TLS 1.3 container edge transit.
RapidAPI Marketplace Gateway ~750 ms – 1,200 ms Real-world round-trip over RapidAPI public proxy (includes key validation, daily quota accounting, and international routing).

🛠️ 6 Ready-to-Use Endpoints

Laya provides 6 dedicated decision endpoints:

  1. POST /v1/triage — Support Ticket Triage: Categorizes inquiries into departments (billing, technical, account), grades urgency (0–2), and flags churn risks.
  2. POST /v1/guard — Prompt Injection Firewall: A sub-30ms security perimeter that detects jailbreaks and system prompt overrides before hitting expensive LLMs.
  3. POST /v1/filter/spam — Spam & Phishing Filter: High-precision binary classifier distinguishing real inquiries from commercial junk.
  4. POST /v1/sentiment — Sentiment & Frustration: Evaluates tone alongside a customer anger intensity score.
  5. POST /v1/moderate — Content Moderation Gate: Zero-shot multi-label safety filter for toxic and harmful content.
  6. POST /v1/decide — Universal Decision Engine: Evaluates arbitrary custom choices, scores, or boolean questions on any payload.

Quick cURL Example (/v1/triage):

curl --request POST \
  --url https://laya-ai-api-gateway-lightning-decision-engine-api.p.rapidapi.com/v1/triage \
  --header 'x-rapidapi-host: laya-ai-api-gateway-lightning-decision-engine-api.p.rapidapi.com' \
  --header 'x-rapidapi-key: YOUR_RAPIDAPI_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "subject": "Billing dispute regarding invoice #4081",
    "body": "I was double charged this morning for my enterprise plan. Please refund immediately or cancel my account."
  }'
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Response (< 35ms model pass):

{
  "department": "billing",
  "urgency_level": "critical",
  "is_churn_risk": true,
  "recommended_priority": "critical",
  "latency_ms": 28.4
}
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🔒 Zero Data Retention

Privacy is first-class:

  • Ephemeral RAM Only: Payloads are loaded into memory strictly for inference calculation and discarded immediately upon response dispatch.
  • Zero Logging: We never log, store, or train on your customer text.
  • In-Transit Security: Full TLS 1.3 encryption across all communication routes.

🎁 Free Tier for Developers

I've set up a generous free tier on RapidAPI offering 16,666 free requests per day (~500,000 requests/month) with zero cost so developers can integrate it into automation workflows:

I would love to get your thoughts! What endpoints or workflow integrations (e.g. native n8n community nodes) would you like to see next?

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