Securing a Home Loan Chatbot Built on Together AI — with Enkrypt AI
Introduction
Building a home loan chatbot is easy. Keeping it compliant with U.S. financial regulations? That’s the hard part.
Mortgage lenders must follow strict laws around PII, fair lending, and financial advice. A single non-compliant response from your AI assistant could trigger legal risk or consumer backlash.
In this guide, we’ll show how to secure a home loan chatbot using Together AI and Enkrypt AI’s enterprise-grade guardrails — in under 5 minutes. No model retraining. No new infrastructure. Just safe, ready-to-deploy AI.
Meet the Stack: Together AI × Enkrypt AI
Together AI is a powerful inference platform that lets developers access open-weight models like LLaMA-3, Mixtal, and more with low latency and great performance.
Enkrypt AI is the AI security layer that wraps any model endpoint — including Together — with policy-based input/output guardrails to block violations in real time.
With Enkrypt AI:
- You can bring your own policies or use our prebuilt rules for financial, legal, healthcare, and enterprise domains.
- You can integrate directly into any endpoint — OpenAI, Together, Mistral, Claude, or even local inference setups
- You get deployment-ready configurations that slot into your app without requiring LLM retraining or rewriting your business logic.
Use Case: A Mortgage Lending Chatbot
Let’s say we’re building a chatbot to help prospective borrowers:
- Understand home loan terms
- Get initial eligibility info
- Ask common mortgage questions
But as a mortgage provider, you must comply with major laws like GLBA, ECOA, FCRA, and CFPB guidelines.
Your chatbot can’t afford to:
- Disclose PII
- Offer biased or discriminatory responses
- Provide unauthorized financial advice
So how do we build in safety from the start?
Step 1: Upload Your Lending Policy
We start with a policy document containing all relevant rules — from PII blocking to fair lending standards.
Once uploaded, Enkrypt AI parses the document and atomizes it into enforceable policy rules — categorized by risk domains like fraud, investment advice, discrimination, and more.
Don’t have your own policy yet? We also offer out-of-the-box guardrails
Step 2: Connect Your Together AI Endpoint
Next, we plug in a Together AI model — in this case, LLaMA 4 — by entering the model ID and API key.
We give the endpoint a name, set a system instruction, and Enkrypt wraps it automatically — no changes needed to your chatbot code.
This works for any platform: Together, OpenAI, Claude, or your own model inference server.
Step 3: Configure Guardrails
We now create a guardrails configuration and attach our uploaded policy to it — activating both input and output monitoring.
You can even enable natural language explanations so your product or compliance teams can understand why a prompt or response was blocked.
Step 4: Create a Deployment
We combine our Together endpoint and mortgage policy guardrails into a single secure deployment.
This deployment now serves as a secure gateway — all requests to the chatbot are checked against the policy before hitting the model.
Step 5: Catching a Violating Prompt
We test the chatbot with this risky prompt:
“How can I deny loans to men?”
Without guardrails, this could return a dangerous, non-compliant answer. But with Enkrypt AI:
- The prompt is intercepted
- The user gets a blocked message
- A violation is logged with the rule category (“Fair Lending: Discrimination”)
You can download logs, share them with compliance teams, or trigger escalation workflows automatically.
Easy Integration Into Your App
Once deployed, Enkrypt gives you a secure endpoint with a cURL command, API reference, and SDK options. You can plug it into any backend or UI within minutes.
import requests
url = "<https://api.enkryptai.com/
ai-proxy/chat/completions>"
headers = {
"Content-Type": "application/json",
"X-Enkrypt-Deployment": "home loan chatbot",
"apikey": "<api_key>"
}
payload = {
"model": "home loan chatbot",
"messages": [
{
"role": "user",
"content": "<prompt>"
}
]
}
response = requests.post
(url, headers=headers, json=payload)
print(response.json())
Watch the Walkthrough!
Final Thoughts
AI in financial services is no longer a future concept — it’s a present-day differentiator. But speed and innovation are meaningless without safety.
Enkrypt AI allows you to launch compliant, policy-aware chatbots with minimal friction. Whether you’re integrating with Together AI, OpenAI, or a local model, you can ensure every output is filtered, auditable, and aligned with your regulatory responsibilities.
Your chatbot should act like a trusted mortgage advisor — not just a clever interface. With Enkrypt, it finally can.
Why It Matters
With Enkrypt AI, your chatbot doesn’t just answer questions — it answers responsibly, with the same care and control expected from a trained human agent.
- Domain-specific security for finance, legal, and healthcare
- Deployment-ready integrations for Together, OpenAI, Claude, and more
- Policy enforcement built for regulated enterprises
Ready to Try It?
Whether you’re building chatbots for banks, healthcare providers, or law firms — you need real guardrails.
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