The problem I wanted to solve
Customer support can become surprisingly repetitive when the same customer returns with the same unresolved problem. A new conversation may look like a fresh ticket, even when the important facts already exist in previous interactions: what failed, what was tried, and whether the attempted fix actually worked.
When I built ResolveIQ, I focused on customer history and avoiding repeated troubleshooting. The goal was not to make another chat interface. I wanted the support workflow to recover useful history at the moment a new issue arrives and turn that history into a concrete next action.
What ResolveIQ does
ResolveIQ is a Streamlit-based support application connected to Hindsight persistent memory. A support agent enters a customer identifier and the current issue. The application asks Hindsight for relevant previous support history and then evaluates that context for recurring issues, previous verification or troubleshooting, and signs of frustration.
The important part is the sequence:
Current issue → Memory retrieval → Historical context → Escalation guidance
That gives the support interaction a memory layer instead of treating every request as isolated.
Why persistent memory mattered
I found that the useful information in a recurring support case is rarely a single sentence. It is the relationship between several events. For example, a payment failure matters differently when the customer has already experienced it, completed bank verification, and returned with the same failure.
Hindsight gives ResolveIQ a place to retain those interactions and retrieve semantically relevant memories later. I used Hindsight's retain and recall capabilities so that the system can store customer interactions and retrieve the history that matters to a new support request.
A simplified memory flow
Customer interaction
↓
Hindsight retain
↓
Persistent customer memory
↓
Hindsight recall
↓
ResolveIQ escalation logic
A concrete customer case
The core example is customer C102. The customer has a recurring payment failure. In the previous case, support asked the customer to complete bank verification. Verification was completed, but the problem did not permanently disappear. The customer then returned with the same payment failure and expressed frustration.
When ResolveIQ recalls the history, the application can surface facts such as the recurring payment failure, completed bank verification, unresolved status, and frustration. That changes the support decision.
Before memory
Customer: Payment failed again.
Agent: Let's start with bank verification.
After memory
Customer: Payment failed again.
ResolveIQ: Previous verification was already completed.
Recommendation: Review the previous case and escalate.
The difference is not that the system magically solves the payment problem. The difference is that the agent receives relevant history before repeating a step that has already been attempted.
The Hindsight integration
The application uses the Hindsight Python client to communicate with the memory service. A recall request is built around the customer identifier and the current issue so the returned memories are relevant to the support decision.
python
result = await client.arecall(
bank_id="resolveiq",
query=query
)
Top comments (0)