Sainapse classifies 32 million customer emails a year into Salesforce

A global logistics leader receives 32 million customer emails a year.

They land in inboxes across country teams around the world, written in the language of the local market, and each one has to become a Salesforce case before an agent can act on it. The taxonomy is not uniform. Different country teams use different sub-types for the same underlying issue, and routing rules depend on getting the classification right the first time.

Response quality tracked the agent, not the question. Two agents in two regions could answer the same shipment query with different SOPs, different phrasings, and different escalation paths. The intranet held the SOPs, FAQs, and how-to guides that covered the answers, but no agent could search them while a customer waited. The knowledge existed. Nobody could find it in time.

Any system taking on that workload had to absorb the country-by-country taxonomy rather than flatten it, and it had to ground every suggested reply in the SOPs the company already trusted. It also had to work inside Salesforce, where the agents already were, not in one more tool for them to open.

Sainapse started by reading the mail. Before writing a single classifier, it clustered the inbound email to find the intents that drive the volume and the ones that take the most work to close.

That gave a global logistics leader a ranked map of where automation would pay back first, drawn from what customers actually wrote rather than from a standard ticket taxonomy.

Three things now run in production on top of that map. Sainapse routes each email into the correct Salesforce Type and Sub-Type for the country team that owns it.

It drafts the reply from the matching SOPs, FAQs, and how-to guides, so an agent reviews a draft instead of writing from scratch. And every correction an expert makes goes back into the model, so Sainapse keeps up with changing policies and new shipment scenarios as the team works, not in a separate project.

Sainapse runs a second deployment at the same customer. It reads the same email and case data for early signs of churn and scores every account, so the team sees the risk while there is still time to act.

Read the companion story on proactive churn detection.