Secure AI Platform
We design and deploy a complete, secure AI platform for internal use — local LLMs, specialised models like Jev, voice and video, MCP connectors to your systems, and an agentic layer that actually gets work done.
New · Secure AI Platform
Local LLMs, specialised models, MCP connectors and an agentic system — deployed on your own infrastructure. Scroll to take it apart — from the perimeter down to the foundations.
01 Perimeter
Everything runs inside your own infrastructure — on-premise, in your private cloud, or fully air-gapped. Prompts, documents and outputs never leave your network, and no third party trains on your data.
02 MCP connectors
Model Context Protocol servers give AI governed access to your ERP, CRM, documents, databases, e-mail and ticketing — with per-tool permissions, so each assistant sees only what it should.
03 Agentic system
On top we build an internal agent platform: role-based agents that plan, call tools, hand work to each other and report back — with a human approving what matters. We run our own company this way.
04 Local LLMs
We select, benchmark and serve open-weight language models sized to your hardware and your tasks — quantised, load-balanced and exposed through one private, OpenAI-compatible endpoint.
05 Specialised models
General chat is only the start. We add specialised models alongside the LLM: Jev-class typed-decision models, speech-to-text and voice, video and vision understanding, embeddings and rerankers for search.
06 Governance
The foundation: audit trails of every prompt and tool call, evaluation suites, usage and cost monitoring, and policies aligned with GDPR and the EU AI Act — plus training so your team can own it.
Delivered end-to-end
From hardware sizing to agents in production — designed, deployed and handed over with training for your team.
What is in the package0
bytes of your prompts, documents or outputs sent to third-party AI providers
1
private endpoint for every team, model and agent — one place to secure, audit and pay for
100%
yours — infrastructure, models, connectors and know-how handed over to your team
Take the full stack, or start with the layer you need most — every layer is built to plug into the next.
01
Open-weight language models selected and benchmarked on your own tasks, then served on your GPUs through one private, OpenAI-compatible endpoint.
02
The right model for each job, running next to the LLM — not every problem is a chat problem.
03
Model Context Protocol servers give AI governed access to the systems you already run — one standard instead of a pile of custom integrations.
04
An internal agent platform: role-based agents that plan, use tools, delegate to each other and report back — with people approving what matters.
05
Your data never leaves your control. We deploy on-premise, in your private cloud, or fully air-gapped.
06
Measured, auditable and owned by your team — not a black box left behind by a vendor.
Answers from your wikis, contracts and tickets — with sources, and only what each user may see.
Invoices, orders and requests triaged and pre-processed in the ERP/CRM, approved by a person.
Local transcription and summaries of calls and meetings — sensitive audio never leaves the building.
Routing, classification and approvals as structured, schema-safe outputs in milliseconds.
1–2 weeks
Use-case discovery, data & systems inventory, security requirements, AI-readiness review.
1–3 weeks
Target architecture, model shortlist benchmarked on your data, hardware sizing, MCP & agent blueprint.
4–8 weeks
Infrastructure, model serving, specialised models, MCP servers and the first agents — in production.
ongoing
Training and mentoring for your team, evaluations, monitoring, upgrades as better models ship.
Timelines are indicative and depend on scope, hardware availability and the number of connected systems.
Tell us about your systems and what you want AI to do. We'll come back with a concrete architecture, model shortlist and plan.
+420 775 109 917