ChatInfer

Use Cases

Use Cases for AI Teams

Explore how teams use ChatInfer to build reliable AI applications — from customer support to enterprise deployment.

Use case 1

AI Customer Support

The problem

Support teams spend hours answering the same questions. Customers expect instant, accurate responses — but building AI support from scratch is complex and time-consuming.

How ChatInfer helps

ChatInfer lets you deploy an AI support assistant that answers customer questions from your docs, help center, and product knowledge. The assistant handles common inquiries, escalates complex issues, and reduces repetitive tickets.

Example workflow

1

Connect your documentation and knowledge base

2

Configure the chatbot for your support workflow

3

Deploy the assistant on your website or app

4

Monitor conversations and improve responses over time

Use case 2

Internal Knowledge Assistant

The problem

Employees waste time searching across documents, policies, and tools for information. Knowledge is scattered and hard to access.

How ChatInfer helps

ChatInfer helps teams build an internal AI assistant that searches policies, documentation, and company knowledge through a secure conversational interface. Answers include source references for verification.

Example workflow

1

Upload internal documents and knowledge articles

2

Configure access controls for sensitive content

3

Deploy the assistant for your team

4

Update knowledge bases as your content evolves

Use case 3

Developer AI API

The problem

Engineering teams managing multiple LLM providers deal with different SDKs, authentication, and rate limits. Switching models requires rewriting integration code.

How ChatInfer helps

ChatInfer provides a unified API for chat completions across multiple providers. Use one request format, one authentication method, and one dashboard for monitoring usage and cost.

Example workflow

1

Get your API key through early access

2

Send chat completion requests with a single API call

3

Monitor usage, latency, and cost from the dashboard

4

Route traffic across models without changing code

Use case 4

Model Routing and Cost Optimization

The problem

Different AI use cases need different models. Using expensive models for simple tasks wastes budget. Teams lack visibility into cost and performance across providers.

How ChatInfer helps

ChatInfer's model gateway lets you route requests to the best model for each use case. Configure routing rules based on cost, latency, or capability. Monitor usage patterns and optimize spending.

Example workflow

1

Connect multiple model providers to ChatInfer

2

Configure routing rules for your use cases

3

Monitor cost and latency from the dashboard

4

Adjust routing to balance performance and budget

Use case 5

Enterprise AI Deployment

The problem

Enterprises need secure, compliant, and scalable AI infrastructure. Evaluating vendors, managing access controls, and planning deployment takes months.

How ChatInfer helps

ChatInfer provides enterprise-grade AI infrastructure with SSO/SAML, data retention controls, security reviews, and dedicated support. Early access users get deployment consultation and private beta discussion.

Example workflow

1

Schedule a deployment consultation

2

Review security and compliance requirements

3

Plan your AI workflow architecture

4

Onboard your team with dedicated support

Not sure which use case fits your team?

Book a demo and we'll help you find the right approach.