Lotus Mind
An AI systems company · Dublin, Ireland

AI you can trust, at a price anyone can pay.

We build AI that people and companies can actually rely on — software that checks its own answers, keeps your data on your side, and costs a fraction of what AI usually costs to run. The same engineering serves one person on a laptop and a team with rules to answer to.

See what we buildAbout the company
✓Runs on your machine
✓Free where it can be
✓No manual required
What we buildAll products →
Why we build this way →
Why we exist

The best AI goes to whoever can pay the most. We think that is a choice, not a rule.

Good AI is expensive, private and well engineered — if you are a large company. Everyone else gets a chat box and a warning not to trust it. Closing that gap is the whole reason this company exists.

Our vision

AI should be safe, affordable, and open to everyone.

Today the best AI goes to whoever can pay the most. Large companies get private, governed, carefully engineered systems. Everyone else gets a chat box, a monthly subscription, and a quiet warning not to trust the output.

We do not think that split has to exist. It exists because most AI software is built to burn as many model calls as possible, and to keep your data somewhere the vendor can see it. Both of those are choices, not requirements.

Open to everyone also has to mean you can leave. Our tools run on your own machine, what they remember is a file you can read, and your work stays in your own hands rather than ours.

We build the opposite: AI that a person, a small business and a bank can each trust — and each afford.

Our mission

Make AI safe enough to rely on, cheap enough to use, and simple enough for anyone.

  • Safe. An AI that works on your behalf has to be honest about what it does not know, and it has to ask before doing anything you cannot undo. We treat that as a design rule rather than a setting. And your work stays yours — on your own machine, or inside your own systems.

  • Low cost. Using AI should not need an enterprise budget. We build so that ordinary software does most of the work and the model is called only where real judgement is needed. Much of what we make costs nothing at all to run.

  • Simple. You should not need training, a setup project or a consultant before it is any use. You say what you want in ordinary words and the software does the technical part. If something needs a manual before it helps you, we have not finished it.

  • For everyone. One person, a small business, or a large company — the same standard of safety and the same quality of engineering. We do not ship a weaker, less careful version for the people who cannot pay much.

Who we build for

One person, a small business, or a whole company

Most AI companies pick one of these and ignore the other two. The safety and cost work underneath is the same either way, so we did not have to choose.

For people and families

One person, a laptop, and a life to get on with

A companion that remembers you and belongs to you. An academy that teaches a child how AI actually works. A file too big for a spreadsheet, opened and answered on your own machine. Free, or close to it, and private by default.

  • Project Nobi
  • Aika
  • Datalic Sheets
  • JenOS
For developers

Agents that need somewhere safe to work

Run your coding agents in isolation and review everything before it lands. Put a governed, verified data layer behind your own product with an SDK, an MCP server and drop-in widgets.

  • Lopy
  • Datalic SDK
  • Datalic MCP
For companies

Real data, real rules, and an audit trail

Governed AI over the databases you already run, deployed inside your own network, where the cloud half has no way to reach your data at all.

  • Datalic
  • JenOS
  • Datalic Sheets
What we do

Five things, one company

We are not an agency that connects APIs, and not only a product company. The engineering, the advice and the software are the same practice.

AI Engineering

We design and ship complete production systems — agents, retrieval, evaluation and the plumbing around them. Not prototypes handed over as a slide deck.

AI Consulting

Opportunity assessment, workflow analysis, data readiness and an adoption roadmap. We start by finding the problem that is worth solving.

AI Applications

Internal tools, assistants and workflow automation built on your own systems, with a person kept in the approval loop.

AI Data Systems

Safe, governed access to data across 32 database engines and the files on your own machine — the layer that decides what an AI is allowed to see and do.

AI Products

Our own software — some of it free to run on your own laptop, some of it sold to companies. Client projects are delivered on the same foundation, which is why they take weeks rather than quarters.

Not sure which one you need?

Describe the problem in a few sentences. We will tell you which of these it is — or that it is none of them.

Talk to us →
Products

Software we own, and use ourselves

Client work is delivered on top of these, which is why a project takes weeks rather than quarters. Some are sold to companies; some are free for anyone.

All products →
How we work

Find the problem, prove it on real data, then build

Most AI projects fail at step two, so we do step two first — on your data, not on a sample.

01

Find the real problem

A short discovery conversation, then a written assessment of where AI helps and where it does not. Often the honest answer removes work rather than adding it.

02

Prove it on your data

A small working prototype on your real data, not sample data. This is where most AI projects quietly fail, so we do it first.

03

Build the system

Delivered on top of our own platform, so the foundation — connectors, governance, verification — already exists and is already tested.

04

Run it with you

Hosting, monitoring, model updates and training. You can also take the whole thing in-house; it is designed to be self-hosted.

Portfolio

Selected engineering work

The decisions behind the products — what was hard, what we chose, and what it changed.

Full portfolio →
2026

A cloud service that cannot open your database

To answer a question about a company's data, something has to see that data. Every AI data tool solves this by taking the customer's database credentials into its cloud. For finance and regulated teams, that single fact ends the conversation.

Datalic →
2026

Answers that check themselves — or abstain

A model querying a database is exactly as confident when it is wrong as when it is right. A plausible wrong number in a board pack is worse than no number.

Datalic →
2026

Teaching a schema what the business means

Ask about "monthly recurring revenue" and a model has to guess which table and which sum you meant. In a large schema it guesses wrong often, and it guesses differently each time.

Datalic →

Have a problem worth solving properly?

Tell us what you are trying to put AI in front of. We will say plainly whether we can help, and if we are not the right fit we will say that too.

Start a conversationAbout the company