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TypeSafe Jev 1.13: a model for application decisions

Short answer

Jev from TypeSafe AI is a model built for tasks where software needs a structured decision, for example assigning a message to the complaints or logistics department, instead of a paragraph of text. It is available on OpenRouter, and a correct answer format has to be told apart from a correct decision.

How we workDetails ↓

  1. 01Call30 minutes with an engineer, free
  2. 02PrototypeA working system on your process and data, free
  3. 03ImplementationTarget and fixed price in the contract; 50% at signing
  4. 04Acceptance50% once the agreed target is met
model on your server or in the cloud in the EU
quoted after the review
same work in application with EU cloud model
from €3,000
task, data and equipment analysis
€0

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Author: Syntalith · 4 min read

Example: the morning request inbox
Agent · ready

Statistics

Decision models: statistics 2026

1.5 mo.

payback of €3,000 at 5,000 decisions a month: €2,908 of work today, €872 with checking and the model. Scenario.

Figures checked: 22 October 2026

A decision from Jev in an application
  1. 01Inputthe text and the list of allowed results
  2. 02Questiona choice, a score or an extraction
  3. 03Answera structured decision
  4. 04Checkthe decision compared with the expected one

What goes in and what comes out

You give a description of the situation and questions about the allowed results. You get typed answers with probabilities. The vendor presents Jev as a model that gives up generating free text in favour of such an interface.

A sample task could be choosing a department, deciding whether urgent escalation is needed and judging whether a request is complete. These are different questions about the same case. The application uses the answers in the process rules, for example it sends an ambiguous request to an operator.

This describes a proposed use. It is no result of a Jev test at Syntalith, and no proof that the model will handle a specific company queue correctly.

Three kinds of question and access through the API

choice picks from the given categories, noul returns the probability of a yes answer, and score places a case on a defined scale. For a request, these could be the department, whether it asks for a refund and the level of urgency. The model takes text, also inside a JSON object; it does not analyse images or recordings directly. It also gives no reasoning for its decision.

According to OpenRouter's documentation, an OpenRouter key is enough, with no separate TypeSafe account. Requests go to the Decisions API at POST /api/alpha/decisions or, compatible with the TypeSafe SDK, POST /api/v1/systemone. The key stays on the application server. Several independent questions about the same state can be sent together; the answers do not see each other.

In a pilot, we record the version identifier the API returns. An alias that points to the newest model can change the result, so after a version change we check the thresholds again on labelled data.

Why speed attracts interest

Many applications need no long statement. They have to recognise an intent quickly, check a condition or choose the next path. Jev fits this need with a different way of getting structured results.

TypeSafe publishes its own speed and cost comparisons. The authors describe the set of tasks used, the conditions and the limits of the comparison. We treat these results as the vendor's measurements that justify a trial. We do not translate their percentages into savings for a specific company.

In an application, the network path, the input size, validation and the time other services take also count. Shorter model computation will not always shorten the whole process by the same amount.

A correct format and a correct decision

Keep two kinds of error apart. The model can return an invalid structure that the application cannot read. It can also return one of the allowed categories, but the wrong one.

TypeSafe's claims of no type errors concern the structure of the answer. The category „logistics” can be a valid data type and a wrong choice for a payment complaint. Likewise, a high confidence level needs checking on company examples. That is why the project covers evaluation, a threshold for passing a case to a person and handling of missing data.

Can Jev run locally?

OpenRouter provides a hosted TypeSafe service. In the materials we checked, we found no Jev 1.13 weights to download and run yourself. In a project that needs private processing, we check the vendor's terms, location and availability. We do not assume that the Jev name means offline work.

There are separate local projects inspired by this idea, including Kev and TinyJev. They have their own weights, training and limits. We describe them in the comparison of local alternatives.

How Syntalith can help

We choose a decision in the process that can be judged clearly. We compare rules, a small model and a chosen general model; we include Jev where its availability and terms fit the requirements. We measure accuracy, the escalation rate and the cost of an accepted decision.

If you have a queue of requests or documents to classify, describe it to Syntalith. We can prepare a test, choose how to host it and tune a local model to the categories your company uses.

What it costs

Scenario: 5,000 decisions a month
Today
5,000 decisions × 1 min = 83.3 h (€2,908)
With the system, a person checks the result in 30% of the time
€872
Jev calls
not counted in the scenario
Cost of one case
€0.58 today, €0.17 with the system
Saving
€2,036 a month

Payback of €3,000

1.5 months

The volume, the time and the checking share are the scenario's assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat.

The cost of Jev calls depends on the OpenRouter price list, so the scenario does not count it. What remains is the time to check decisions and the cost of the application.

What we measure in the trial
  • The time from receiving a case to the result, before and after the change
  • Cases the application passed to a person
  • Corrections by the person checking
  • The cost of the model and maintenance at the target volume

Where to start

In the free review we choose one process and count the volume and the team's working time, and within 2 working days you receive a written summary with a price. We run the build as part of AI apps, and price maintenance separately.

Worked example · Scenario

How we count the payback: decisions in an application

We run the same count for your team in the free review.

€5,817

a month for answering 2,000 customer emails

Payback: 0.6 mo.

5 minutes to read an email and write a reply and checking in 15% of the old time are our assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat, for companies with 10 or more employees. Model cost: Claude Sonnet 5.5, about 3,000 + 600 tokens per message with a draft reply, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

See the full calculation →

This is how we implement it in companies

All case studies →

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗

A model on your server or in the cloud in the EU, proven on your tasks.Book a free process review (30 min) →

How we build automation and agents

From a conversation to a working system in four steps.

  1. 01 · 30 min

    Free process review

    €0

    You're talking to an engineer. You receive the written plan within 2 business days.

  2. 02 · 5 days

    Free prototype

    €0

    The system works on 20-100 cases that your team has already handled. You see every result.

  3. 03 · 2–16 weeks

    Build

    50%

    Fixed price and goal written in the contract. First installment upon signing.

  4. 04 · after reaching the goal

    Reception

    50%

    You pay the second installment when the system reaches its target on your cases.

How a free prototype is created

Mon.

We set a goal

What result do you consider good?

Tue–Wed

The system is working

It goes through your affairs, one by one.

Thu

We compare

We check every difference with the team's work.

Fri

Result and price

List of errors and fixed implementation price.

You choose the matters. We anonymize them upon request, they stay in the EU and we delete them after the test.

On the market, such a test usually costs from PLN 3,000 to PLN 8,000.

Book a free process review (30 min)

We establish a prototype during a free analysis.

Data checked on October 25, 2026.

„Is my data safe?”

Yes. You choose where they go: from your company account to the model on your server.

  1. 00Employee's private account

    Customer and company data ends up in an account that the company cannot see or control. There is no data processing agreement, so it is a violation of the GDPR. When an employee leaves, the chat history goes with them.

  2. 01ChatGPT or Claude corporate account

    The provider does not use your data to train models. A copy of the queries remains in his logs for up to 30 days.

  3. 02API with zero retention (ZDR)

    The provider processes the request and does not save anything. It requires his consent, we prepare the application together.

  4. 03Processing in the EU

    Queries are counted and stored in Europe: OpenAI in the EU region, Claude via clouds with the EU region.

  5. 04Model at your place

    The open model runs on your server or in your cloud in the EU. The data does not go outside the company.

What we do with every implementation

  • Confidentiality agreement and data processing agreement before we receive any data.
  • You choose the cases for the prototype and we anonymize them upon request.
  • The data stays in the EU and we delete it after the test.
  • Corporate accounts with an administrator on your side.

When data cannot leave the company

The open model runs on your server or in your cloud in the EU. To choose from:

White-tailed eagle
Polish model, SpeakLeash and ACK Cyfronet AGH
PLLUM
Polish model, HIVE consortium commissioned by the Ministry of Digitization
Qwen
Alibaba
GLM
Zhipu AI
DeepSeek
DeepSeek

We select a model for the task and check it on your cases. We run it, tune it and maintain it.

Source: Bielik and PLLuM, ACK Cyfronet AGH ↗ · PLLuM, Ministry of Digitization ↗

Do you have a lot of your own data? We will fine-tune the small model.

  1. 1 Your examples
  2. 2 tuning
  3. 3 test on new cases
  4. 4 model at your place

When you have thousands of similar emails, documents or reports, we teach a small open model based on your examples. It works for you, responds quickly and costs less to maintain than a large model. We measure quality on issues that the model has not seen while learning.

Przemysław and Piotr did it in large programming and consulting companies. Artem did it before and does it today at Syntalith. It's about models on your own infrastructure, tuning and quality measurement.

You choose the protection level during the interview. We sign the data processing agreement before we see any data.Schedule a free analysis →

Private AI models

A model on your server or in the cloud in the EU, proven on your tasks.

We select the model and equipment for the task, run it and measure the quality using your examples before you buy anything. The data stays in the company or in the cloud in the EU. We price implementation, hardware or hosting and support separately after analysis.

View private AI models →
model on your server or in the cloud in the EU
quoted after the review
same work in application with EU cloud model
from €3,000
task, data and equipment analysis
€0

Questions

  • What is Jev from TypeSafe AI?

    A decision model that returns a structured answer, for example a chosen category, instead of free text. It is available through an API on OpenRouter.

  • Does a correct format mean a correct decision?

    No. The model can return valid JSON with the wrong category, so decisions are checked on your own examples with an expected result.

  • How much does it cost?

    At Syntalith, AI apps, automations and agents start from €3,000 net. At 5,000 decisions a month and 1 minute each, the payback is 1.5 months.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
When we roll out ChatGPT, Claude or Copilot, you buy the licences directly from OpenAI, Anthropic or Microsoft and they invoice you. We add nothing to the licence.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.