horoz.aiLLM integration and software development
We integrate large language models into your existing products and build the web app and backend from scratch when needed. The goal is a system that works reliably in production, not only in a demo.
What it covers
- Choosing a suitable model and architecture for your product, weighing cost, speed and data privacy with you
- Integrating language models into your existing application and backend
- Building the web app and backend from scratch when needed
- Setting up tests and evaluations to measure the quality of model output
- Launching and monitoring the system and documenting it so your team can take it over
When it is the right starting point
- You want to add an AI feature to your product
- You have a working prototype and need to take it to production
- You are looking for a team to build a new product from idea to launch
How we work
Discovery and architecture
We get to know your product’s goal, your users and your existing infrastructure. Together we assess which model and architecture fit, weighing the balance between cost, speed and data privacy, and we share the reasoning behind each decision openly.
Data and security design
We clarify which data the model will access, where that data is processed and who can see which information. We design how user input and model output are checked, and we access only the data the project needs.
Prototyping
We test the approach early on real data with a small, working prototype. That way we see the quality of the model output, the speed to expect and possible problems before committing to a larger build.
Development and evaluation
We develop in short cycles and show a working version at the end of each one. We set up tests and evaluations to measure model output and use them to check whether a change really improves quality.
Launch, monitoring and handover
We take the system live and monitor errors, latency and running costs. We document the code and the architecture so your team can take them over, and we keep developing the system as your needs change.
What it can look like in practice
Example scenario: Picture a company with its own web app that wants its users to find what they need in long documents more easily. The team has put together a quick demo with a language model, but on some questions the demo produces information that is not in the source, and it is unclear how consistently it would work in production. In a case like this we would build a setup that makes the model answer only from the relevant parts of the documents, add tests that measure answer quality, and integrate the system into the existing app with monitoring in place. The team could then see concretely which questions the system handles well and where it needs improvement. This is a hypothetical example that does not describe a specific client.
Frequently asked questions
What is LLM integration?
It means connecting large language models, AI models that can understand and produce text, to an existing product or business process. The work covers designing which data the model uses, how it talks to your application, how its output is checked and how the system is monitored in production. The aim is to run the language model as a reliable part of your product, not as a standalone demo.
How do you decide which language model to use?
There is no single right model for every product. We weigh with you the quality the task requires, response speed, running cost and any constraints on where your data can be processed. We share the choice along with the reasons and set up the architecture so that switching models later stays as easy as possible.
Can you take our existing prototype to production?
Yes. We first review the prototype and the approach behind it and identify what could cause problems in production. Then we add tests and evaluations, rework the architecture if needed and launch the system in a way that can be monitored. We take care to keep what works in the prototype and change only what truly needs to change.
Is our data shared with model providers?
That depends on the chosen model and how it is used, which is why we address data privacy at the very start of the architecture decisions. Together with you we decide which data is sent to the model, where it is processed and how it is stored, and we access only the data the project needs.
Do you also build applications from scratch?
Yes, when needed we build the web app and backend from scratch. If you want to take a new product from idea to launch, we work in a transparent process where you know what is being done at every step, from discovery and prototype to development and launch.
Who runs the system after launch?
We document the system so your team can understand it and take it over. You can maintain it with your own team or keep working with us on monitoring and development; as your needs change, we develop the system further together. During handover we go through how the code, the infrastructure and the evaluations work with your team.
Other services to consider
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Custom AI assistants and agents
If you need an assistant that answers from your own information sources and performs defined tasks, start with its scope and tool connections.
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Let us talk about what you need
Describe your situation in a few sentences and we will work out the right next step together.