Customer Support Agent
Let customers describe a problem in plain English — and have it genuinely resolved in seconds. No FAQ dead-ends, no repeating themselves. It uses real account data and hands off to a human only when it should.
The problem
Support deflection isn't resolution
FAQ bots point customers at articles; they don't fix anything. So tickets pile up, wait times grow, and your team burns its day on the same repetitive issues over and over.
Building an agent that actually resolves issues — with real account data and a clean human handover — usually means a six-figure build and months of engineering. Most teams stall before they start.
The solution
An agent that resolves, then escalates
A Support Agent connects to your helpdesk and knowledge base through MCP. It uses real account data to resolve issues end to end — and hands off to a human with full context when it should.
You set the boundaries once in SentientOne. It runs 24/7, keeps conversation history, and your customer data never leaves your environment.
Out of the box
Real questions, real answers.
However your customers phrase it.
The agent understands natural language and acts on live account data — so it resolves the issue instead of linking to an article.
“I can't log into my account.”
Checks the account and sends a reset, end to end.
“Where's my refund?”
Looks up the case and gives a real status, not an article.
“How do I change my plan?”
Walks them through it using their live account data.
“My order arrived damaged.”
Logs it, offers a fix, and escalates with full context.
“Can you cancel my subscription?”
Handles it within the boundaries you set.
“I need to speak to someone.”
Hands off to a human with the whole conversation attached.
How it works
Four steps in SentientOne.
Live in days, not months.
Create the agent
In Agents, add a new agent, pick a model (e.g. OpenAI · gpt-4o), and write a short system prompt that defines its job.
Name
Provider
Model
Temperature
System Prompt
Connect your Helpdesk API
On the agent's MCP tab, add your Helpdesk API as an MCP server. SentientOne discovers the resolve_ticket tool — your credentials stay in your environment.
Name
Transport
URL
Auth Type
Test it in the Playground
Ask real questions in the Playground. The agent calls your API, reads the live response, and replies in plain language. Tweak the prompt until it's right.
Go live with one request
Grab your API key and send a single POST from your app. No AI SDK — anything that can make an HTTP request works.
Platform API key
API endpoint
POST /v1/chat
X-Api-Key: sk-live-•••
X-Agent-Id: customer-support-automation
{ "message": "I can't log into my account." }Why SentientOne
Why teams ship this with us.
Not a 6-month engineering project.
No AI team required
Skip the ML hires, the prompt infrastructure, and the model plumbing. Configure the agent in the dashboard and you're done — we'll even set up the MCP server for you at no extra cost.
Your data stays yours
The MCP server runs on your infrastructure. SentientOne only receives the tool response — never your raw database, credentials, or records. Self-host the whole platform if you need to.
Works with your stack
Connect any REST or gRPC API through MCP. One HTTP endpoint plugs into React, Flutter, Python, .NET, Go — anything that can make a request. No SDK lock-in.
Switch models, never rebuild
Run GPT-4o today, Claude tomorrow — change it from a dropdown. When your API changes, you update one tool definition. No retraining, no redeploys.
“It doesn't deflect — it resolves. Customers get their issue fixed in seconds, and the tickets that do reach us arrive with a full summary. Our queue has never been shorter.”
The outcome
What you get
60–70%
of repetitive tickets resolved automatically
Days
to deploy — no AI engineers required
Private
your customer data stays in your environment
Questions
Common questions
How long does it take to go live?
Most teams are answering real questions within a few days. There's no model training and no AI pipeline to build — just connect your API and configure the agent.
Do I need AI engineers?
No. The agent is configured in the dashboard, and we'll set up the MCP server that wraps your Helpdesk API for you at no extra cost.
Is my data safe?
Yes. The MCP server runs in your environment and only returns the specific tool response. Your database, credentials, and raw records never reach SentientOne.
What happens for questions it can't answer?
You define the boundaries. Anything outside the issues you allow is handed off cleanly to your team with full context.
Which models can I use?
GPT-4o, Claude, Gemini, Groq and more. Pick one from a dropdown and switch any time — your setup and integration stay exactly the same.
How does it reach my users?
One HTTP endpoint. Drop it into your existing chat widget, app, or site — React, Flutter, Python, .NET, Go, anything that makes a request.
Free white papers
Go deeper on this
Improve Your Customer Support with AI Agents
Support queues grow faster than headcount, and every minute a customer waits chips away at trust. Most teams paper over the gap with canned macros and after-hours auto-replies that never actually resolve the issue. This guide shows how AI agents handle the repetitive tickets end to end, escalate the ones that need a human with full context, and give your team back the hours they spend on copy-paste answers.
Improve Your Knowledge Base with AI Agents & RAG
Your team's knowledge is scattered across docs, wikis, and tickets — and answers stay locked away until someone goes digging. This guide shows how Retrieval-Augmented Generation turns that knowledge base into an AI agent that answers in plain language, cites its sources, and stays current, so your team finds what they need in seconds instead of hours.
More patterns
Explore other use cases
Order Status Agent via MCP
Let customers ask about their orders in plain English.
Business Intelligence Reporting Agent
Turn your database into a conversation.
Personalised Recommendations Agent
Send insights in, get smart recommendations out.
Product Discovery & Catalogue Agent
Let users search your catalogue by describing what they want.
Get started