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Custom AI apps

We build a custom AI app around a defined process when off-the-shelf software does not fit or company data must stay in place. It can search documents, extract data, or classify cases. Prices start at €6 000 net and production launch takes 4–10 weeks. We check quality on client examples, uncertain answers go to a person, and the code, system instructions, and test examples stay yours.

Book a free process scan (30 min)

In short

Price and time
from €6 000 net · 4–10 weeksprice follows integrations, data sources, and quality requirements; fixed quote before the contract
How we guard quality
Accuracy measured on your dataaccuracy checked on your documents before launch; uncertain cases go to a reviewer
What stays yours
The code, system instructions, and test examplesno lock-in to a single provider
For whom
When off-the-shelf SaaS does not fitfor internal tools when data must remain in an approved environment
Book a free process scan (30 min)

Problem

Your team spends hours hunting for knowledge scattered across documents and pulls data from PDFs and scans by hand, because off-the-shelf SaaS doesn't fit the process or can't be given your data. A quick API call bolted onto an app looks great in a demo and breaks in production. One made-up answer delivered with confidence is enough for the team to stop trusting any of them. Those hours have an hourly rate; the status quo is not free.

Outcome

In 4–10 weeks you get an application where the LLM performs a specific, repeatable task: answering from cited documents, classifying cases or extracting invoice data. We measure accuracy on your data and route uncertain answers to a reviewer. You commit to the full build after the pilot meets the accuracy target.

How we control risk

Each risk has its own control in a running system.

The control sits where an error could harm the user, a document, or the company.

  • Legal research · answer integrity

    Case-law research

    The system creates an answer after finding an exact source passage. Questions that require legal advice go to a lawyer.

    Open the deployment

  • Internal knowledge · access control

    Permission-aware memory

    Permissions are checked before a document is retrieved. A user sees material available to their role, and every denied request is recorded.

    Open the deployment

  • Confidential documents · on premises

    A document flow with no internet egress

    Documents and answers remain on company infrastructure. The system blocks external connections, while an administrator controls data sources and updates.

    Open the deployment

For each project, the controls and quality threshold are set on data from the client's process.

  • Artem Lisovtsov

    Founder, Full-Stack & AI/ML Architect

  • Serhii Ivanchatenko

    Head of Backend & AI Integrations

This is how one sourced answer is built.

From a question or a document to a checkable answer. The confidence gate marks where a person takes over.

  1. 01

    A query arrives

    a user question or a document enters the app

  2. 02

    Source search

    the app retrieves and reranks the right passages in your data

  3. 03

    Answer with a source

    the model answers, pointing to the passage it uses

Confidence threshold

confident answers go to the user, doubtful ones wait

Answer with the source cited

a confident case reaches the user with its source and decision history

Uncertain answer to a human

a doubtful case the app does not serve on its own

We set the confidence threshold where a human takes over on your data during scoping. Operations with production impact can require approval.

The difference shows when the model is wrong.

Bolted-on API

  • Quality

    “Works on my examples”

  • Hallucinations

    Reach the user

  • Boundaries

    The model does as it pleases

  • Trace

    No idea where the answer came from

  • Ownership

    Locked in someone else's SaaS

  • Cost and time

    Lower entry, a subscription you switch on today

An app built around the process

  • Quality

    A fixed example set and measured accuracy on your data

  • Hallucinations

    Safety rules, source checks, and a handoff to a person

  • Boundaries

    Content from documents is data rather than commands; actions under conditions and minimum permissions

  • Trace

    A log of input, sources and decision

  • Ownership

    Code, system instructions, and test examples are yours

  • Cost and time

    Higher upfront cost, then no permanent subscription to another company's software

A build costs more upfront and takes longer than switching on an off-the-shelf SaaS. It is worth it when the process or the data is too specific for ready-made tools, or when the data can't leave the company. If a ready tool is enough, we'll say so. You get a fixed quote in the proposal after the free process scan.

An app built around the process

Answer with a source

a confident case reaches the user with its source and decision history

Sources

  1. Passage from your knowledge baseRAG
  2. Record from your systemRAG

Answer and rule checks

  • Safety rules, source checks, and a handoff to a person
  • Content from documents is data rather than commands; actions under conditions and minimum permissions
  • A log of input, sources and decision

Code, system instructions, and test examples belong to you

A named package in this line

Company AI knowledge base

An assistant that answers from your own documents and shows where the answer came from.

A packaged build inside the AI Apps line. The assistant reads your procedures, contracts, offers and system notes, answers in full sentences and names the document it relied on. With no basis in the corpus it says "I don't know" and points to the person who owns the topic.

How it behaves at work

  • 01

    Answers from company documents

    The corpus is your procedures, contracts, offers and system knowledge. Each answer is composed from retrieved passages, with no filling of gaps from the model's training memory.

  • 02

    Cites the source

    Every answer carries the document name and the passage it rests on, so an employee can verify it in seconds.

  • 03

    Says "I don't know"

    When retrieval finds no basis, the assistant declines to answer and routes the question to the person who owns the topic.

  • 04

    Inherits permissions

    Each person sees only the documents they can already open in the source system. Permissions are resolved in the retrieval layer, before a document reaches the model.

When a separate search layer is worth it

500

pages of documents

Below the threshold
Below roughly 500 pages, a simpler assistant over one file set is usually enough. We say so during the scan, before a build starts.
Above the threshold
Above that threshold, we combine semantic and keyword search and order results by relevance. This preserves quality as the collection grows and document versions change.

The threshold is indicative. The decision depends on corpus volume, update frequency and permission requirements; we assess it on your files.

Price inside the AI Apps line

Entry
from €6 000 net
Typical implementations
€6 000–35 000 net
Maintenance
priced individually

The range follows the number of sources, required permissions, and scope of testing. You get a fixed quote in the proposal after the free scan, before any contract.

Book a free process scan (30 min)

In 30 minutes we determine which questions your documents can answer and which search architecture fits the corpus.

Read further

What the build includes.

  • Internal assistants and panels working on your data
  • Answers from your documents with the source cited
  • Extracting data from invoices, contracts and scans into an agreed format
  • Classification of cases and documents according to your rules
  • A fixed set of client examples with measured accuracy
  • Safety rules and a human handoff for uncertain answers
  • Integration with your systems over APIs, on minimum permissions and with a log
  • Code, system instructions, and test examples belong to you

Data & compliance

Production cloud (AWS, Google Cloud, Azure) or your own infrastructure, minimum permissions and a decision log, uncertain answers through a human. We provide technical input to EU AI Act documentation (accuracy, transparency, oversight), but not legal advice. If the app talks to users or generates content, the Art. 50 transparency duty (disclosing it is AI) applies from 2 August 2026.

Not for

  • Marketing websites and landing pages
  • Web development with no AI component
  • A chat widget pasted onto a site
  • A process an off-the-shelf SaaS handles cheaper and faster: we'll recommend the SaaS

Entry price

from €6 000

Delivery window · 4–10 weeks

Price follows the integrations, data sources, and quality requirements.

You get a fixed quote in the proposal after the free scan. You know the full cost before signing, with no hidden items.

Book a free process scan (30 min)

What drives the price

  • The number of integrations and data sources
  • Quality requirements and the scope of testing
  • Security, consent, and action history

Cost over time

  1. Implementation buildfrom €6 0004–10 weeks
  2. Maintenance and oversightpriced individuallymonthly

Free process scan

Start with a free process scan.

  • A 30-minute call with the engineer who would lead the work.
  • A review of the processes that cost you the most time and money.
  • A written summary of what to automate first and the likely cost range.

The scan is free and creates no obligation. If automation is unlikely to pay off, the written recommendation will say so.

€0

30 minutes · written takeaway within 2 business days

Book a free process scan (30 min)

Times are shown in your own time zone. We work with clients across time zones.

Describe the process in the form

AI app questions

  • What if an off-the-shelf SaaS is enough?

    The scan recommendation will identify it. We recommend existing software when it handles the process at lower cost. A custom build makes sense when the process or data is too specific for ready-made tools.

  • How do you keep the model from making things up?

    We check the app on a fixed set of examples from your process, verify each answer against its source, and define the handoff to a person. Accuracy is measured before launch, and answers below the agreed threshold go to a reviewer.

  • What if the model gets it wrong in production?

    For each answer, we record the question, sources, and decision, so a mistake can be traced and fixed at its source. Safety rules hold doubtful cases back from the user, while maintenance improves the rules and test examples after launch.

  • Where does our data live, and does it leave the company?

    We deploy to an agreed cloud or your infrastructure, with minimum permissions and encryption. The app accesses the required data, while the code, system instructions, and test examples stay on your side. For personal data, we sign a GDPR data processing agreement and limit engineer access. The AI provider works under terms that exclude training on your data, or the system runs locally.

  • What about security and the EU AI Act?

    We work on minimum permissions and with a decision log, and uncertain answers go through a human. We also provide technical input to the operator documentation the EU AI Act expects (accuracy, transparency, oversight), but we don't give legal advice or classify the system.

  • What if the app doesn't work in our process?

    We set the quality threshold on your data before the build. If the scan or test shows that accuracy is too low for your process, we tell you before paid development begins.

  • Who maintains the app after launch?

    The same engineer who built it. After launch, maintenance covers monitoring, fixes, and updates to the safety rules and test examples as data and the process change. Scope and response time are set in the contract.

  • How much does an AI app cost?

    Implementations start at €6 000 net. Price follows the integrations, data sources, and quality requirements. The proposal gives you a fixed quote before signing.

  • Is the pilot included in the price?

    Yes. A pilot on your data is the first implementation stage inside the fixed price. If it does not reach the written accuracy threshold, we improve it within the same price, and the decision on full deployment stays with you.

  • When does a company knowledge base not need RAG?

    For fewer than roughly 500 document pages, a simpler assistant over one file set is often enough. For larger collections, we combine semantic and keyword search and check permissions before releasing a document. The free scan identifies the suitable approach.

The scan ends with a written recommendation.

  • A 30-minute call with the engineer who would lead the work.
  • A review of the processes that cost you the most time and money.
  • A written summary of what to automate first and the likely cost range.
€030 minutes · written takeaway within 2 business days
Book a free process scan (30 min)

Times are shown in your own time zone. We work with clients across time zones.

The scan is free and creates no obligation. If automation is unlikely to pay off, the written recommendation will say so.

Full pricing