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Tender review with sources: how the workflow works

Short answer

A tender document can contain an instruction aimed at the model that reads it. A document reader with no network and no tools passes on only a closed set of fields, so a foreign instruction never reaches the part that plans actions. At Syntalith an agent costs from €3,000 net, and with 300 tender notices a month at 10 minutes each it pays back in 2.3 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
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

Public procurement: statistics 2026

2.3 mo.

payback of a €3,000 agent at 300 tender notices a month: €1,745 of work today, €445 with checking and the model. Scenario.

Figures checked: 22 October 2026

There is a notice. Is there material for a decision

An analyst collects notices from several registers. The description of a procedure is not enough for a decision: you need the source, the deadline and a note of which documents are still missing. In our demonstrator the view orders 67 saved records from BZP, the Polish public procurement bulletin, and TED, the EU's tender journal, from a controlled snapshot. It lets you narrow the register and the region and go to the original notice. A missing tender specification (SWZ) stays visible instead of vanishing under a summary.

The document reader and the planning part have different permissions. The reader has none of the planner's tools and no access to its database, and passes on a closed data contract. That limits the path by which unverified content can reach the next stage. OWASP describes prompt injection as the first risk on its list for applications built on language models.

Tender monitoring in the Syntalith demonstrator
The rebuilt local app, 25 September 2026. Archived data from 2 August 2026.
A tender document in two zones
  1. 01Readerno network, none of the planner's tools, no database access
  2. 02Contracta closed set of fields: deadline, bid bond, criteria, gaps
  3. 03Quarantinesuspicious content flagged and stopped
  4. 04Plannerworks only on the fields in the contract
  5. 05Analystthe decision to bid, with the source and a list of gaps
The scope of the evidence
  • A snapshot of 67 notices from 2 August 2026, without continuous monitoring or full pagination
  • 14 controlled artefacts with hostile instructions, from outside these tenders
  • Keeping 670 fields intact measures data transport, and reading quality needs its own measurement
  • No evidence of market completeness or of the quality of bid decisions

What a protected tender agent costs and when it pays back

Scenario: 300 tender notices a month
Today
300 notices × 10 min = 50 h × €34.90 = €1,745
With the system, a person checks the output in 25% of the time
€436
Model, 2 calls per case, Claude Sonnet 5.5
€9
Cost of one case
€5.82 today, €1.48 with the system
Saving
€1,300 a month

Payback of €3,000

2.3 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: 6,000 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, 25% 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.

According to the Polish Public Procurement Office (2026), 53.6% of Polish tenders above the EU thresholds received only one bid. Reaching the right notices faster has value, but only when the analyst trusts the fields they read.

Reader security and the quality of tender monitoring

Testing the security boundary and the quality of market monitoring are two separate tasks. Controlled trials do not prove that all notices were collected, and keeping fields intact does not say whether the company should bid. So the first business scope sets the sources and categories the team really follows, and the deadline is always checked at the source. Anthropic, in Building effective agents, advises adding complexity only when a simpler solution is not enough. A reader with no tools is such a simpler solution.

How to start with tenders
  • A few registers, a manual review is enough

    register alerts and a list of followed categories

    no build

  • Many notices, document analysis

    monitoring with an isolated reader and a closed set of fields

    from €3,000

  • A bid decision against the company's criteria

    an agent that prepares an assessment for the analyst

    priced after the review

Where to start

First we compare the notices found with manual monitoring and keep source completeness apart from the assessment of fit. To prepare: a profile of the procedures you look for, the registers and the owner of the bid decision. The current process is described in tender monitoring with AI. We build this kind of rollout as part of AI agents. 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: tender monitoring

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

€1,047

a month for reviewing 600 tender notices by hand

Payback: 3.4 mo.

3 minutes to review a notice 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 6,000 + 800 tokens per notice with its assessment, at the ECB rate of 1.1205 USD per euro on 22 October 2026. Reading a notice in our system alone costs about €0.0002. The tender margin is a scenario: we assume that 1 in 5,000 notices spotted in time ends in a winning bid with a margin of €4,590. In the review we count it on your tenders.

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 is prompt injection in a tender document?

    An instruction hidden in the text of a document and aimed at the model, for example a command to skip a criterion or to send data. A model reading the document may treat it as an order.

  • How do you protect an agent from a hostile document?

    Separate the document reader from the planning part. The reader has no network and no tools and passes on only a closed set of fields, and suspicious content goes to quarantine.

  • How much does such an agent cost?

    At Syntalith from €3,000 net. With 300 tender notices a month at 10 minutes each, the payback is 2.3 months. We agree integrations and maintenance before the quote, and the model costs €9 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.