AI & Automation
Practical AI that saves time: assistants that answer from your own documents, agents that take safe actions, and automations that remove repetitive work.
What you get
- Chat assistant over your documents (RAG)
- AI agents with clear limits on what they may do
- Workflow automation between your tools
- MCP connectors to your systems
- Guardrails, test questions and cost limits
- Usage and cost reporting
How we work
We start with one real task and a set of test questions, connect the AI only to approved data, and measure answers before launch. Agents get the smallest set of permissions they need, and every action is logged.
Popular stacks
- LLM APIs (OpenAI, Anthropic, DeepSeek)Core
- RAG (retrieval-augmented generation)Core
- AI agentsProficient
- MCP (Model Context Protocol)Proficient
- PythonCore
- FastAPICore
Questions
Which AI model do you use?
We work with LLM APIs such as OpenAI, Anthropic and DeepSeek, and choose by quality, language support and cost for your task.
Can the assistant answer in Lao?
We design and test for Lao and English. Lao quality differs between models, so we measure it with your own questions before launch.
Will AI make mistakes?
It can. That is why we limit it to approved data, add a handoff to a person, and show users that answers come from AI.
Have an idea? Your first build can be free.
A limited number of free first builds each quarter, with scope agreed in writing. You own everything we make.