Platform
Build together.
Run together.
Create a named AI bot for every customer care professional. Observe real work, turn it into reusable skills and manage people, bots and shared cases on one multiplayer platform.
Explore the demo ↗Personal bots, shared skills and team context
Connected workflows with human control
One platform / five connected modules
From how work happens.
To how agents improve.
Observe real work, teach the right skills, build together and improve from reviewed outcomes.
01ObserveSee how work gets done.↗02LearnTurn expertise into agent skills.↗03BuildBuild agents. Together.↗04RunPut your agents to work.↗05OptimizeMake every version better.↗
↳ Outcomes and approved corrections feed back into Observe and Learn.
From human know-how to work done
One case.
The whole journey.
Follow a damaged-order refund from the way a person handles it to a team of agents carrying the work through.
01 / Observe
It starts with your team’s know-how.
A customer request. A policy check. A decision. Observe how your people handle a real task, across conversations and back-office tools.
Illustrative product journey · synthetic customer case
Human know-how. In its natural habitat.
Zendesk · ticket received“My order arrived damaged.”
✓Shopify · order foundOrder and delivery matched
✓Policy · next actionCheck eligibility. Issue refund.
✓02 / Learn
Turn real work into shared skills.
Connect observed steps to their context. Your team reviews the knowledge, rules and exceptions before an agent uses them.
Illustrative product journey · synthetic customer case
KNOWLEDGE / PROPOSED SKILL
Damaged-order refund
01 / EVIDENCEOrder, delivery and damage report
02 / PROCEDUREVerify eligibility against the refund policy
03 / EXCEPTIONAsk a person when the case falls outside policy
Team review → test → approve
03 / Build
Shape the agents together.
Support defines the mission. Operations adds the procedure. Quality tests the edge cases. Give each specialist a clear role.
Illustrative product journey · synthetic customer case
SHARED PROJECT / RETURNS TEAM
One mission. Complementary agents.
CARE AGENTUnderstand the request and reply
ORDER SPECIALISTRetrieve the order and verify delivery
REFUND SPECIALISTPrepare the permitted refund action
Support + Operations + Quality · version review
04 / Run
Humans and agents. One resolution.
The care agent receives the request. Specialists carry out the checks. People guide exceptions and approve actions when required.
Illustrative product journey · synthetic customer case
NEW REQUEST / SHARED CASE
“My order arrived damaged.”
ZendeskTicket received
01“My order arrived damaged.”
ShopifyOrder retrieved
02Purchase and delivery matched.
AI policyEligibility checked
03Within the approved refund policy.
Human + AIRefund issued
04Approved refund completed.
NotificationCustomer informed
05Confirmation sent to the customer.
ResolutionResolved
06Ticket closed. Outcome recorded.
One case history. Clear ownership.
05 / Optimize
Improve from confirmed outcomes.
Review what happened, propose a change and test it together. Approved improvements feed back into the next learning cycle.
Illustrative product journey · synthetic customer case
IMPROVEMENT / TEAM REVIEW
Make the next resolution better.
OBSERVED ISSUEA delivery check was repeated unnecessarily
PROPOSED CHANGEReuse verified order context between specialists
BEFORE RELEASETest against the shared case set and approve
Approved improvement → next version
Across the conversation
Different channels.
One way to work together.
Design around the customer journey. Keep context attached to the case as the conversation moves between supported channels.
01 /
Voice ↗
A conversation. An action. A resolution.
02 /Chat & Messaging ↗
Keep the conversation moving.
03 /Email ↗
Longer threads. Shared context.
04 /Agent-to-Agent ↗
Ready for customers. And their agents.
Channel connections and supported actions are agreed during setup. Agent-to-agent is a product direction under development.
Build with Supraway
Explore the demo ↗Your team. Your first agent.
See how customer context, business rules and authorized actions come together in an interactive return workflow.