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AI agents for branch reporting follow-ups

Short answer

For a monthly report, an AI agent links head office's questions with the branches' replies, checks that each comment concerns the right indicator and month, and writes the coordinator a follow-up when a reply describes a state in place of a cause. The agent costs from €3,000 net at Syntalith and, with 150 questions to branches a month at 15 minutes each, pays back in 3.3 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
net per agent for one process, build paid once
from €3,000
from signing the contract to acceptance
6–16 weeks
free prototype on your cases
€0

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

Reporting and AI: statistics 2026

3.3 mo.

payback of a €3,000 agent with 150 questions to branches a month: €1,309 of work today, €397 with checking and the model. Scenario.

Figures checked: 22 October 2026

Head office asks for the cause, the branch gives the state

The monthly report shows a rise in backlog cases at one branch. The analyst asks the manager what caused the rise in the reported month. The manager replies: „We currently have 48 overdue cases”. That is the number from the table. Another branch describes the previous month. The head of operations hears that every branch has replied, and there is still nothing to build a discussion of causes from.

The agent shows the coordinator the reply next to the question and the month, and proposes a follow-up: what affected the rise in backlog in this period? When a comment describes the previous month, the agent points this out and proposes a request about the current period. The explanation comes from the branch, because the agent cannot tell from the numbers alone what happened on site. The analyst judges whether the reply explains the change.

From the report to a discussion of causes
  1. 01Questionthe indicator, the month and the responsible person at the branch
  2. 02Replythe manager's comment on the question
  3. 03Checkwhether it concerns the right month and gives a cause
  4. 04Follow-upa draft of the next question for the coordinator
  5. 05Discussionthe analyst assesses the explanations and prepares the conversation

What it costs and when it pays back

Scenario: 150 questions to branches a month
Today
150 questions to branches × 15 min = 37.5 h (€1,309)
With the system, a person checks the output in 30% of the time
€393
Model, 2 calls per case, Claude Sonnet 5.5
€4
Cost of one case
€8.73 today, €2.65 with the system
Saving
€912 a month

Payback of €3,000

3.3 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: 5,000 input 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 things on. What remains is the time to check the output, 30% of today's work in the scenario. Before the quote we measure both times on 20 to 100 cases the team has already handled, in a €0 test that takes 5 working days.

The count leaves out what happens at the results review. When head office has the explanations before the meeting, the conversation with managers is about corrective action. Without them, the meeting starts with the question of what happened and ends by booking another one.

First check the comments on the report

If branches work in Power BI, start with the conversation in the report. Microsoft describes comments on reports and visuals, with notifications through mentions. When the team holds the conversation on the right report, agreeing how questions are asked is enough. An agent makes sense when replies arrive by email and messenger, and the coordinator checks by hand whether they concern the right period. If head office first fixes columns in exports, the article on taking in data from franchisees is the closer fit.

What to choose for which report
  • Branches comment in the Power BI report

    comments and mentions in the report

    licence

  • A few branches

    the coordinator collects replies by hand

    no build

  • Dozens of branches, replies in emails and messenger

    an agent that links comments with the report

    from €3,000

Where to start

The first scope covers one recurring report and the team that collects the comments. On last month's materials we check with the person running the report whether the view shows whom they still need to talk to. We build this as part of AI agents. For the free process review, a description of one case from recent weeks and the tools it ran 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: reporting automation

We run the same count for your report in the free process review.

€1,815

a month for 12 h a week of report preparation

Payback: 1.9 mo.

The hours for each firm size 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. We measured the model cost in our report system: a commentary with a check of the figures costs about €0.0002, converted at the NBP rate of 21 October 2026 and 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 ↗

See the agent on your own cases before you commit.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 agents

See the agent on your own cases before you commit.

The agent takes the case through the next steps in your systems, and the actions take effect until the consent of the indicated person is obtained. A prototype for 20-100 cases that your team has already handled costs €0. We write down the purpose and test set in the contract.

See AI agents →
net per agent for one process, build paid once
from €3,000
from signing the contract to acceptance
6–16 weeks
free prototype on your cases
€0

Questions

  • How does an AI agent help collect explanations from branches?

    It links head office's questions with the branches' replies, checks that each comment concerns the right indicator and month, and proposes a follow-up when the cause is missing.

  • Does the agent establish the causes of the results?

    No. The explanation comes from the branch, and the analyst judges whether it explains the change. The agent cannot tell from the numbers alone what happened on site.

  • How much does such an agent cost?

    At Syntalith from €3,000 net. With 150 questions to branches a month at 15 minutes each, the payback is 3.3 months. We agree integrations and maintenance before the quote, and the model costs €4 a month.

  • When are comments in Power BI enough?

    When branches hold the conversation in the report. An agent makes sense when replies arrive by email and messenger.

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.