Generative AI and agents
Fewer hours reading documents and copying data: AI does it and your team reviews the doubtful cases.
Sound familiar?
- Your team spends hours reading invoices, delivery notes and emails to copy data.
- Finding something in the internal documentation takes longer than doing the work.
- Market or tender reports are done by hand and arrive late.
What you get out of it
- Your documents answer for you
- Data reaches your system on its own
- Reports write themselves
- Your team decides what matters
Assistants and agents that work with your knowledge.
We create AI systems that detect, analyse and score market information automatically, and assistants that answer accurately from your company's own documentation.
Chatbots over your documents
They answer questions about manuals, contracts or regulations citing the source, without your data leaving your environment.
Agents that work for you
They read emails, invoices or delivery notes, extract the data and leave it ready in your system.
Automatic reports
Periodic summaries and analysis of the market, tenders or business indicators.
Human review
Doubtful cases go to a review queue: the AI proposes and your team decides.
How it is integrated and validated
It connects to your email, ERP or document manager, or is used from an internal website. It is validated with real cases from your company, and doubtful ones go to a manual review queue.
We choose the documents and systems it works with.
We define what the agent can and cannot do.
We measure it on real cases and count the errors.
We put it into production and improve it with use.
How we do it
What you get
- 01Assistant or agent flow in production
- 02Manual review queue for doubtful cases
- 03Log of what it does and how confident it is
- 04Training for the team that uses it
Where it runs
We decide with you where the system lives, depending on how sensitive your data is.
On your servers
We install it on your infrastructure or in your cloud. Your data never leaves your environment; in exchange, someone on your side has to maintain those servers.
On Vidra's servers
We host it on servers inside the European Union and you access it via web or API. We take care of maintenance, and access is restricted to your team.
With external AI APIs
For language models we use the OpenAI, Anthropic, Google or OpenRouter APIs. It is the most capable option and the fastest to set up. The text fragments needed are sent to that provider, and we tell you which one is used and what data it receives.
With local models
If your data cannot leave your environment, we use models that run entirely on your servers or ours, without sending anything to third parties. They are somewhat less capable than the large API models and need more hardware.
From pilot to production
We start with a scoped pilot: one specific case, with your real data and measurable goals agreed up front. If they are met, we integrate it into your tools and it goes into production. If not, we explain why and what it would take.
After delivery
When the system goes into production, a feedback stage begins: your team uses it day to day and, if something fails or does not fit, we fix it. After that you can hire maintenance: incident handling, updates and, for models, retraining with new data.
What you hire and what we build it with
What you hire
An assistant or agent flow in production. It starts with a pilot with measurable goals, and doubtful cases always go through someone on your team.
Under the hood
Assistants over your documents and automatic analysis systems, with language models via API or run locally.
- Claude
- OpenAI
- Gemini
- pgvector
- FastAPI
- Pydantic
We choose the tools for your case; you do not need to know them.
