Map the source set
Organize pages, docs, policies, FAQs, catalog data, and approval rules into material the agent can use.
AI support agents that feel human
Answer more repeat questions, guide customers to the right next step 24/7, and stay inside your voice, rules, handoff paths, and your store's content.
FlexChat guide
readyCustomer
Can I return this if I opened it?
AI guide
Yes, our return policy allows opened returns within 30 days. Here’s the return page and what to expect.
Built for support teams across
Retail
SaaS
Clinics
Agencies
Education
Local services
FlexChat platform
One operating layer for safer AI support.
FlexChat sits behind each deployment: collecting the right material, setting the rules, routing exceptions, and keeping the system reviewable once it is live.
Configure the workflow
Set tone, routing, handoff logic, and operating boundaries so the agent follows your rules.
Escalate when needed
Route off-script cases to a person with the thread, intent, and relevant policy context preserved.
Tighten over time
Use live questions, missed handoffs, and review logs to update the source set and behavior.
Handoff and review
Escalates when it should.
The agent routes to a person when a question is outside scope, defers on pricing and policy edges, and preserves the thread so your team sees what was asked and why it escalated.
Escalation preview
The handoff is structured before the agent stops.
Customer intentRefund exception after 30 days
ConfidenceLow because warranty language is missing
Recommended routeSenior support queue
Context attachedCustomer-provided order ID, policy excerpt, conversation summary
Source graph
Returns policy
Shipping FAQ
Warranty rules
Product catalog
Order-status FAQ
Escalation paths
Gap flagged
Customers are asking about international exchanges. Add the policy before expanding scope.
Control
Control built in.
Answers come from your store's own content — your pages, policies, FAQs, and product data. Scope is explicit: what it can answer, what it should defer, and when a person needs to take over.
Operating model
Launched with review. Improved by FlexChat.
Live questions and missed handoffs show what needs adjustment. We use that feedback to update the source set, rules, and behavior.
Custom
built around your workflow
48h
first working demo
24/7
available on your site
Review logs
Add source for warranty exceptionsqueued
Tighten refund escalation thresholdqueued
Promote shipping-delay answer to signed-off languagequeued
What to measure first
Prove control before you expand coverage.
The first launch should show where the agent is useful, where it should stop, and what your team needs to adjust before expanding.
Scope
Track which questions the agent can answer, what it should defer, and when a person needs to take over.
Handoffs
Watch off-script cases, policy edges, and repeated escalations so routes stay clear.
Review logs
Keep conversations visible so drift, gaps, and repeated misses are easy to spot.
Updates
Use live questions to tighten the source set, rules, and behavior over time.
Every deployment starts with scoped sources, clear rules, and a review loop your team can understand.
How it works
From intake to live operation.
We start by collecting the materials the system needs to work correctly, then configure the rules, launch, monitor, and tighten over time.
Source set mapped48h demo
Customer asks about an exception
The agent answers from policy, defers, or hands off based on scope.
Route exceptions
Thread and reason preserved.
Review logs
Gaps and drift stay visible.
Ready for the next channel
01
Map the source
Organize your site, docs, catalog, policies, and FAQs into a usable source set, then flag gaps and deferral points.
02
Configure the workflow
Set tone, routing, handoff logic, and approval boundaries so responses follow your operating rules.
03
Launch and run
Deploy the system, monitor usage, fix issues, and manage updates without making your team support it internally.
04
Tighten over time
Use live questions and missed handoffs to adjust the source set, rules, and behavior.
FAQ
Questions teams ask before launch.
What is FlexChat?
FlexChat is a managed AI support agent that lives on your website. It answers customer questions from your store's own content, follows your rules, and hands off to your team when a request leaves scope. We build, host, and maintain it for you.
How is this different from a chatbot?
Most tools hand you a chatbot to set up and manage yourself. We build a bespoke agent on your store's content, install it with one line, and run it for you — it answers in your voice and hands off when an answer isn't there, with nothing for your team to maintain.
How do you keep answers under control?
The agent answers only from your store's content and hands off instead of guessing when something falls outside it. Every build is tested against real customer questions before it goes live, and every conversation is logged so gaps and drift stay visible.
What does launch include?
We capture your store's content, build and configure the agent, and stand up a working demo within 48 hours of kickoff. After launch we host, monitor, and maintain it — so your team doesn't have to run or support it.
Get a demo
Make customer service your competitive edge.
Use FlexChat to launch an AI support experience that feels accurate, governed, and unmistakably yours.