AI built into your product, not bolted on after.

Three ways we apply AI to your product.

We do not build AI for the sake of it. We look at your product, identify where AI creates real value, and build exactly that.

⚙️

Process automation

Repetitive tasks slow teams down. We identify the workflows in your product that can be automated and build the tooling to handle them — so your team focuses on work that actually needs a human.

🤖

Generative AI & copilots

Chatbots, smart assistants and AI copilots built directly into your product. Trained on your data, designed for your users, integrated into your existing workflows rather than bolted on as a separate tool.

🔌

AI integrations

You do not always need to rebuild from scratch. We connect existing AI capabilities from Claude, Azure AI and others to your current software stack — extending what you already have without starting over.

When AI makes sense. And when it doesn't.

A lot of companies add AI to their pitch decks. We only add it where it genuinely saves time, reduces manual work, or makes the user experience measurably better. We will tell you honestly if your use case is not ready for it.

✓AI works well when

There is a high volume of repetitive decisions or classifications
Users regularly interact with large amounts of unstructured text or data
The task has a clear output that can be validated or corrected
Speed matters more than perfection on every individual result
You have enough data to train or fine-tune a model meaningfully
You need to break down complex documents so users can ask questions and get quick, useful answers

!Think carefully when

The problem could be solved more reliably with a well-designed form or rule
The output has serious consequences if it is wrong
You have very little existing data to work from
The user cannot easily detect or correct an AI mistake
The main benefit is the word "AI" in a product description

AI we have already built.

Not hypothetical. Here is how we have applied AI in products we built for real clients.

From feedback to action, automatically

A B2B SaaS platform for collecting and analyzing employee and customer feedback at scale. AI turns raw responses into concrete recommendations — in seconds, not hours.

B2B SaaSCloudAI integrationSubscription billing

AI data extraction from tender documents

We built AI-powered data extraction into Tender.app, automatically pulling structured information from complex tender documents. Less manual input, fewer errors, faster processing.

Document AIData extractionLLM

Frequently asked questions

The questions clients ask most before adding AI to a product.

Not always. For integrations using foundation models like ChatGPT or Claude, you can get started with very little proprietary data. For fine-tuning or training custom models, we will tell you what volume you need before the results are reliable.

We work with OpenAI (ChatGPT, Embeddings), Anthropic (Claude), Azure AI, and open-source models depending on your requirements for cost, privacy, and performance. We are model-agnostic — we pick what is right for your use case, not what is newest or most hyped.

We design AI features with privacy by default. For sensitive data we can use on-premise or private cloud deployments, avoid sending personal data to third-party APIs, and build audit trails so you always know what the AI did and why.

We always build with fallbacks. AI outputs are never shown to users without a confidence threshold or a human review step where the stakes are high. We also build monitoring so you can see error rates over time and know when retraining is needed.

Yes, and that is often the fastest path. We start with a technical review of your current stack and identify the integration points. In most cases we can deliver a working AI feature into an existing product in 2–6 weeks.

Three ways we apply AI to your product.

When AI makes sense. And when it doesn't.

AI we have already built.

Frequently asked questions

Ready to build something that lasts?