Why we're building Howzer
Customer service teams drown in messages. We think structured AI analysis, not chatbots, is the answer.
By Howzer Team, Founders
Every day, customer service teams process hundreds or thousands of messages. Each message carries intent, emotion, urgency, and sometimes real risk. But most of that signal is lost because there is no time to read carefully, and no tooling to surface what matters.
The problem is not that companies don't care. It's that the volume makes it impossible to care consistently.
The problem we saw
We spent time with customer service leads at mid-size and enterprise companies across Germany. The pattern was the same everywhere: teams were fast but blind. They responded quickly, but had no structured understanding of tone, root cause, or risk. Escalations happened too late. Patterns went undetected for weeks.
Existing tools either offered keyword-based tagging (too shallow) or full chatbot automation (too risky for regulated industries). Nobody was building a system that analyzes every message in depth and gives the human agent a clear picture before they respond.
What Howzer does differently
Howzer is not a chatbot. It does not talk to customers. Instead, it reads every incoming message and produces a structured analysis: What is the sentiment? What emotion is present? What is the root cause? How high is the risk? All before a human ever opens the ticket.
- Analysis, not automation: every message is scored, not auto-replied.
- Privacy first: PII is redacted before any model sees the data.
- Self-hosted: the entire pipeline runs in your infrastructure.
- Human-in-the-loop: agents decide, Howzer informs.
Where we're starting
We're building for the German market first. German customer feedback has specific linguistic challenges, including compound words, formal/informal register, and indirect complaints, that generic English-first models handle poorly. Our first pipeline version is German-native. English follows.
The initial deployment model is self-hosted: the pipeline runs inside your cloud tenant with zero internet egress. For regulated industries, this is a non-negotiable starting point. A managed SaaS option will follow once we've proven the pipeline under real production load.