Guide · made with Zapier
How do you route customer email automatically? A five-step build with Jev and Zapier
A keyword filter flags a furniture ad and misses the client who is locked out. Jev is a model that never writes text — it reads a message and returns a decision with a confidence score. Here is the five-step build.
The short answer
Use a model that decides instead of one that writes. A keyword filter searching for the word “urgent” will flag an ad for forty percent off office chairs and miss the customer whose whole team is locked out two hours before a client presentation, because the filter is matching a word rather than reading what the message means. Jev, from a company called TypeSafe, is built for exactly that gap: it reads a message and returns a decision — yes or no, one option out of a set, or a rating on a scale you define — along with a confidence score for each answer. It never writes text back. Zapier has added a native Jev integration, so the whole thing is one “Ask Questions” step with Paths branching on the answers, and no code. The five steps are: pick the job and write down what you expect before you build, decide which questions Jev should answer, connect those answers to actions, set a minimum confidence so low-confidence messages go to a person instead of the wrong department, and then work out what it saves you in both staff time and model charges.
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Step by step
Choose the job, and write down what you expect first ▶1:17
Jev is built for sorting customer requests, rating sales leads and deciding which department should handle a problem. Pick one. Then, before you build anything, take a few real messages your business actually received and write down what you want Jev to do with each. Include a hard case with too little context, like “it happened again, please fix it.” That written list is what you will test against later.
Tell Jev what to look for ▶2:23
Jev takes three kinds of question. Yes or no: does this message describe a problem that needs action today to prevent a business interruption? Pick one: which team should handle this, billing or tech support or sales or something else? Or a scale: how frustrated is this customer, from calm to furious. You define the questions and the possible answers. Jev returns its choices with a confidence score for each.
Connect the answers to actions ▶4:09
In the Zap editor, search for TypeSafe Jev, connect your account and select “Ask Questions.” Then use Zapier's Paths to send the work in different directions based on what Jev decided: an urgent technical problem opens a priority task for support, a billing question goes to accounts, a new lead goes to sales. No code, and no custom connection between the apps.
Give Jev a way to ask for help ▶5:01
“It happened again, please fix it” could be a duplicate charge or a login problem, and there is no way to tell from the message alone. In the Zapier integration you set a minimum confidence level; below it, the answer comes back as unsure. Then you either stop the workflow or branch to a person who can check the customer's history and route it properly. Without this, a low-confidence guess gets sent somewhere wrong.
Calculate what it saves you ▶6:17
Do it on both axes. Staff time first, then the model charge — which is the point where a decision-only model separates from a writing model, because you are not paying for output tokens you never wanted.
“A filter looking for the word urgent flags the chairs, and it misses your message from the client who's still locked out.”
Nick Standlea, in the video
Key moments
- ▶0:00An AI that doesn't write text
- ▶0:27Two emails arrive at your business
- ▶0:49The filter flags the chairs and misses the emergency
- ▶1:17Step one: choose the job
- ▶1:38Write down what you expect before you build
- ▶2:23Step two: tell Jev what to look for
- ▶2:31Yes or no, pick one, or a scale
- ▶3:33Why “is this important?” is a bad instruction
- ▶4:09Step three: connect the answers to actions
- ▶4:25Branching the work with Zapier Paths
- ▶5:01Step four: give Jev a way to ask for help
- ▶5:28Minimum confidence, and the “unsure” path
- ▶6:17Step five: calculate what it saves
- ▶6:52220 hours a month, 165 hours back
- ▶7:06$8,250 a month, $99,000 a year in time
- ▶7:40Four cents per million input tokens, no output charge
- ▶8:12$8.40 for 200 million tokens
Questions people ask
what is jev
Jev is a model from a company called TypeSafe that does not write text at all. It reads something — an email, a ticket, a form entry — and returns a decision: yes or no, one option from a set you define, or a rating on a scale. Every answer comes back with a confidence score.
how is jev different from chatgpt or claude
Those models generate text. Jev only decides. It will not draft your emails or write your essays, and it produces no output tokens at all, which is why it is cheap to run at volume. The tradeoff is that it only does the one job, so you use it where you want a decision rather than a document.
why do keyword filters miss urgent emails
Because they match words, not meaning. An ad reading “URGENT: forty percent off office chairs” contains the word a filter is looking for. An email reading “our whole team is locked out, we have a client presentation in two hours” does not. The filter flags the ad and drops the emergency, which is exactly backwards.
what kinds of questions can jev answer
Three. Yes or no, which is deterministic if-then logic. Pick one from a list of options you supply, such as billing, tech support, sales or other. Or a scale, such as how frustrated a customer sounds, from calm to furious. You set the questions and the allowed answers to fit your own workflow.
how do i write a good instruction for an ai classifier
Be specific about what you actually care about. “Does this message describe a problem that needs action today to prevent a business interruption?” works. “Is this email important?” leaves far too much to interpretation, and you will get inconsistent answers because you asked an ambiguous question.
how do i test an ai routing workflow
Write down the answers you expect before you build anything, using real messages your business received. Then feed those messages through and compare Jev's answers against your list. That is a real test. Reading the output and deciding it looks reasonable is not — it is an eyeball test, and it will let bad routing through.
what happens when the ai is not confident
You set a minimum confidence level in the Zapier integration, and anything below it comes back as unsure. From there you can stop the workflow or branch to a separate path where a person reviews the message, checks the customer's history and routes it properly. This is the step that keeps a low-confidence guess from landing in the wrong department.
how do i connect jev to my other apps
Zapier has a native TypeSafe Jev integration. Search for it in the Zap editor, connect your account, and select “Ask Questions.” Then Paths branches the workflow on whatever Jev decided. There is no code and no custom connection to build between the apps.
how much does jev cost to run
At the price TypeSafe published as of recording, just over four cents per million input tokens, with no output-token charge at all because it never writes text. On an example of roughly 200 million input tokens a month — in the region of 100,000 emails — that works out to about $8.40. Check the current published price before you plan around it.
how much time can automated email routing save
Worked through as an example: twenty people spending half an hour a day sorting messages, across twenty-two working days, is 220 hours a month. If the workflow removes three quarters of that, the team gets 165 hours back, which at $50 an hour in staff costs is $8,250 a month, or $99,000 a year in time. Payroll does not shrink — what changes is that those hours go to customers and leads instead of sorting.
do i need to write code to build this
No. The Jev integration is a single step in the Zap editor, and Paths handles the branching. That is the appeal of a deterministic workflow: once it is set up properly, it just runs.
Zapier sponsored this video. Nick chose what to build and what to say.