Artificial intelligence applied to your processes
We integrate language models where they save measurable time: assistants that know your business, document extraction, real-time agents and automations. With guardrails, cost control and your data under European law.
What we build with AI
Four families of use cases we have already shipped, for clients and inside Brymio.
Assistants with your knowledge
Chat and voice assistants that answer from your documentation, catalogue or procedures, with sources and without making things up.
- Retrieval over your documents (RAG) with citations
- Web, app, WhatsApp or Telegram front ends
- Access rules per user and audit of every answer
Document extraction and review
Invoices, contracts, forms and reports read, structured and checked automatically, with a human in the loop where it matters.
- Extraction of fields and tables into your database
- Classification, summaries and plain-language explanations
- Validation rules and confidence thresholds
Real-time avatar agents
Agents that talk to your users in real time, with a custom system prompt, retrieval over company knowledge and voice. Already built for a client.
- Voice and video avatars with low latency
- Custom persona, tone and escalation rules
- Conversation analytics and hand-off to humans
LLM automations
The manual step in a process replaced by a model: triage, drafting, routing, enrichment. Integrated into the tools you already use.
- Email and ticket triage and drafting
- Product and catalogue enrichment
- Integrations with your CRM, ERP or store
How we approach an AI project
The same four steps as any other project, with two extra questions: is it worth it, and can we measure it.
- 1
Use-case discovery
We look at the process, the volume and the cost of the manual work today. If AI will not pay for itself, we say so.
- 2
Data and guardrails
What the model can see, where it lives, what it must never do. Access rules, retention and GDPR settled before a line of code.
- 3
Prototype with real data
A working version on your actual documents or conversations within weeks, evaluated against a test set you agree with us.
- 4
Production and monitoring
Cost per request, quality over time, fallbacks when the model fails. AI in production is a system, not a demo.
Proof, not promises
We use AI in our own products and have shipped it for clients.
AI inside Brymio
Receipt OCR for expenses, catalogue enrichment, plain-language explanations and audit recommendations run in production for Brymio's customers every day.
Real-time avatar agents for a client
Custom system prompt, retrieval over the company's knowledge, voice and latency engineering. We do not name the client; we can walk you through the architecture.
Questions about AI projects
Which models do you use?
Whichever fits the case: OpenAI, Anthropic and Google models, and open models when data has to stay in a specific place. We benchmark on your data before choosing.
Does our data end up training someone's model?
No. We use business APIs with no-training terms, or self-hosted models, and we document exactly what each provider sees and for how long.
How do you keep the assistant from making things up?
Retrieval over your documents with citations, a constrained system prompt, validation rules and a test set we run on every change. And a clear 'I don't know' when the answer is not in the sources.
What does an AI project cost?
A focused assistant or extraction pipeline starts in the low five figures in euros; real-time agents and multi-step automations cost more. Running costs are usually cents per request, and we report them from day one.
Have a process AI could take off your hands?
Tell us about it. We will tell you whether it is a good candidate, what it would take and what it would cost.