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Field-work documentation: how the workflow works

Short answer

When a photo, a voice note and a job card from one call-out give different data, the AI system keeps each file separately, shows the conflicting values side by side and blocks closing the case until a coordinator decides. A convenient summary must not erase the difference between sources. At Syntalith the app costs from €3,000 net, and with 300 field call-outs a month at 15 minutes each it pays back in 1.6 months.

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
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Author: Syntalith · 3 min read

Example: the morning request inbox
Agent · ready

Statistics

Field documentation: statistics 2026

1.6 mo.

payback of a €3,000 app at 300 field call-outs a month: €2,618 of work today, €796 with checking and the model. Scenario.

Figures checked: 22 October 2026

Three sources, two machine numbers

A coordinator receives a photo, a voice message and a job card in PDF from the site. The card gives one machine number, and the technician says another in the recording. The photo shows the machine and liquid beneath it, and the nameplate is not visible. An ordinary summary would pick one number and hide a conflict that may matter for safety.

In our demonstrator each file enters the case file separately and keeps its source, time and author. The system compares the shared fields and shows the differing values side by side. An open conflict blocks closing the case file. The coordinator chooses a value present in the evidence, picks the basis from a closed list and signs the reasoning. The system does not identify the machine or the source of the liquid, and it does not release the machine for work.

The evidence package for one call-out
  1. 01Photothe original with time and author, the description as a suggestion
  2. 02Voice notethe original for listening, the transcript as a suggestion
  3. 03Job carda PDF with fields to compare
  4. 04Comparisonshared fields, conflicting values side by side
  5. 05Decisionthe coordinator chooses the value and the basis, and signs
The scope of evidence in the demonstrator
  • One fictional case file and three test files
  • A synthesised voice note, without site noise
  • 10 readings of the photo for $0.047340 in total
  • No measurement on different phones, languages and machine types

What a field evidence app costs and when it pays back

Scenario: 300 field call-outs a month
Today
300 field call-outs × 15 min = 75 h × €34.90 = €2,618
With the system, a person checks the output in 30% of the time
€785
Model, 3 calls per case, Claude Sonnet 5.5
€11
Cost of one case
€8.73 today, €2.65 with the system
Saving
€1,822 a month

Payback of €3,000

1.6 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. Model: 4,000 input tokens and 500 output tokens per call at Anthropic's rates, converted at the ECB rate of 1.1205 USD per euro on 22 October 2026.

The count covers the work around a case: searching, reading, writing and passing it on. What stays is the time to check the output, 30% of today's work in the scenario. Before we quote, we measure both times on 20 to 100 cases your team has already handled, in a €0 test that takes 5 working days.

We leave 30% of today's work in the count because every conflict goes to the coordinator. According to the European Commission (2026), 90% of companies using AI say people take the decisions, and 2% of decisions are fully automated. In field cases this split follows from safety.

Why the transcript stays a suggestion

Ten transcription samples of the same recording returned two texts that differed in punctuation. That is why the case file keeps the audio and the original file, and the text is an aid for the coordinator. No reading of the photo settles the machine number when the nameplate is not in the picture. We write such limits down before the pilot, together with the rule that a model's suggestion never starts a machine and never replaces an inspection. Anthropic's guide to evaluating agents recommends running the same task many times, because a model's output changes between trials.

How to start with field evidence
  • One source per call-out, no conflicts

    a form in a mobile app

    no AI

  • A photo, a recording and a card from one case

    an evidence package with field comparison

    from €3,000

  • Cases with a safety decision

    a package with a closing block and a role signature

    priced after the review

Where to start

The pilot covers a few types of event with an agreed result, a decision owner with acceptance criteria and material from real phones. To prepare: rules for storage and access. We build this kind of rollout as part of AI apps. For the free process review, a description of one case from recent weeks and the tools it went through is enough. You do not need to send confidential documents, and you get a written plan within 2 working days.

Worked example · Scenario

How we count the payback: cases from the field

We run the same count for your call-outs in the free process review.

€3,490

a month for writing the reports for 400 jobs

Payback: 1 mo.

15 minutes to write a work report 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: reading a photo at €0.0042 (0.004734 USD), measured in our field documentation system, plus the description (Claude Sonnet 5.5, about 2,000 + 400 tokens), 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 ↗

Start with the process that takes the most time each week.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 →

AI implementation

Start with the process that takes the most time each week.

The engineer chooses one process with you and calculates how much it costs today. Then we build a free prototype on 20-100 cases that your team has already handled. We write down the goal and the fixed price in the contract.

See AI implementation →
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

Questions

  • What should you do when a photo and a note from the field contradict each other?

    Keep both sources separately, show the conflicting values side by side and leave the decision to the coordinator. The case does not close until a person chooses the value and records the reason.

  • Is a transcript of a voice note reliable?

    It is an aid. In our demonstrator 10 transcripts of the same recording gave 2 different texts, so the original recording stays in the case file for listening.

  • How much does such an app cost?

    At Syntalith from €3,000 net. With 300 field call-outs a month at 15 minutes each, the payback is 1.6 months. We agree integrations and maintenance before the quote, and the model costs €11 a month.

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.