AI integration into business software and processes
We bring artificial intelligence where it is useful: inside the software and processes your company already uses. We do not train proprietary models: we integrate AI models available through APIs, connect them to your data with the necessary controls and measure whether they really help.
What we build
- Assistants that answer from the company knowledge base and documents
- Contextual chatbots for customers and operators, also inside existing platforms
- Recognition and reading of documents and images
- Automatic classification and routing of requests
- Workflow automation connected to the systems in use (CRM, ERP, WhatsApp)
- API integration of language models into your applications
Typical applications
- A live chat that suggests answers to operators from the knowledge base
- Searching company documents by asking questions in natural language
- Extracting data from documents received by email or uploaded to a portal
- Sorting incoming requests by topic and priority
How we work
From the problem to the product
- 01
Assessment
We start from the problem: processes, users, the systems already in place and measurable goals.
- 02
Requirements and roadmap
Together we define what to build, in which order and with which priorities, timing and budget.
- 03
UX and architecture
We design interfaces and technical structure, integrations included, before writing code.
- 04
Iterative delivery
Incremental releases you can verify: you watch the product grow and can correct the course.
- 05
Testing, launch and evolution
Testing and go-live, then maintenance and new features guided by how the product is actually used.
What to expect
A working integration, measured on real cases. Some distinctions matter: a rule-based chatbot is not an assistant built on a language model; keyword search is not the same as retrieving passages to ground an answer; integrating a model through APIs does not mean having a proprietary model; deterministic automation is not an autonomous agent. We tell you which one fits your case. Language models can make mistakes: we do not guarantee the accuracy of answers, we define how to measure it and where a person must check.
Technologies
- LLM APIs
- REST APIs
- .NET / C#
- Angular
- Flutter
Related project
Knowledge base and AI live chat for an insurance company (Insurance).
Selected projectsFAQ
Frequently asked questions
Can I integrate AI into the software I already use?
Often yes, if the software exposes APIs or allows extensions. During the assessment we check the access points and what data the AI would need.
Do our documents stay confidential?
We define with you which documents are used, who can see what and which provider processes the data, under which contractual terms. Access rules of the source systems must also be respected by the assistant.
How do you check the quality and cost of answers?
With a set of real questions and expected answers to test before and after each change, and by monitoring usage: every request to a model has a cost that can be estimated and capped.
Can we start with a proof of concept?
Yes, it is the approach we recommend: a limited case, real data and a clear success criterion, before extending the solution.
Related services
Tell us about your project
Let’s talkWrite to us describing what you need: we will reply to arrange a first free 30-minute call.
Write to usThe data you send us is handled as described in our Privacy policy.