Product Discovery Agent
Let shoppers search your catalogue the way they actually talk — and find the right product in seconds. No keyword guessing, no “no results”. It reasons over your catalogue and asks smart follow-ups.
The problem
Keyword search hides your catalogue
Customers describe what they want in plain language; your search bar matches keywords. The gap shows up as “no results”, abandoned sessions, and products people never find — even when you stock exactly what they need.
Building natural-language search in-house means expensive NLP infrastructure and a team to maintain it. For most catalogues, that never gets approved.
The solution
Search the way customers talk
A Product Discovery Agent reasons over your catalogue through MCP. Shoppers ask in their own words, and it returns the right products — asking follow-ups and comparing options like a sales assistant would.
Configure it once and drop it into your search bar or chat. No NLP pipeline to build, and your catalogue data stays in your environment.
Out of the box
Real questions, real answers.
However your shoppers phrase it.
The agent interprets intent and reasons over your catalogue — so shoppers find the right product even when keywords would fail.
“Waterproof jacket under $150?”
Returns in-stock matches that fit the budget and need.
“Something for a beginner.”
Interprets intent and narrows to the right options.
“Compare these two for me.”
Lays out the differences like a sales assistant.
“What's good for cold weather?”
Reasons over specs to surface genuine fits.
“Do you have this in blue?”
Checks live variants and stock before answering.
“I don't know what I need.”
Asks smart follow-ups to guide them to a choice.
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 Catalogue API
On the agent's MCP tab, add your Catalogue API as an MCP server. SentientOne discovers the search_catalogue 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: product-discovery-agent
{ "message": "Waterproof jacket under $150?" }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.
“Customers describe what they want and the agent finds it — even things they'd never have searched for. Our 'no results' page basically disappeared.”
The outcome
What you get
Fewer
dead-end “no results” searches
Days
to deploy — no NLP pipeline to build
Private
your catalogue 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 Catalogue 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 product search 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 Search with Agentic AI
Most businesses still run a keyword search bar over a catalogue that customers describe in plain language. The gap between the two is lost revenue — every day. This guide shows how to move from keyword matching to natural-language search, and how to deploy a production-grade Product Search Agent in days, not months.
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.
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