WHAT WE DO
Custom AI Models
LLMs and vision models trained on your enterprise data.
RAG Architecture
Instant, accurate answers from your data via Retrieval-Augmented Generation.
Automation & Agents
Autonomous AI agents taking over repetitive processes.
How We Work
Security-first engineering approach.
01.
Data Discovery
What data do you have, what do you need? We analyze data quality and potential.
02.
Model Selection
We determine the best architecture (LLM, Computer Vision, Regression, etc.) and tech stack for your problem.
03.
Prototype & POC
We prove feasibility and expected ROI with a quick Proof of Concept.
04.
Development & RAG
We feed the model with enterprise data (Fine-tuning or RAG) and optimize accuracy rates.
05.
Integration
We install securely on On-prem or Cloud environments and integrate into existing workflows.
01Data Discovery
What data do you have, what do you need? We analyze data quality and potential.
02Model Selection
We determine the best architecture (LLM, Computer Vision, Regression, etc.) and tech stack for your problem.
03Prototype & POC
We prove feasibility and expected ROI with a quick Proof of Concept.
04Development & RAG
We feed the model with enterprise data (Fine-tuning or RAG) and optimize accuracy rates.
05Integration
We install securely on On-prem or Cloud environments and integrate into existing workflows.
AI Myths vs Reality
FAQ
Is our data used for model training?
No. In On-prem or Private Cloud setups, your data remains entirely under your control.
Which models do you use?
We fine-tune open source (Llama, Mistral) or use closed source (GPT-4, Claude) models depending on the need.
AI is not 'magic', it's a data engineering problem.
PyTorchLangChainOpenAI / LlamaVector DBs