Reliable AI for real business problems

Automate the busywork with AI that verifies itself

Manual work costs you time. AI you can't trust costs you money. We build self-checking AI systems that automate your biggest bottlenecks, including:

Content engines that catch their own errors Workflows that research, write, and check every claim against its source before you hit publish.
Reliable voice and chat assistants Multi-modal AI that handles complex customer conversations inside the rules you set.
Knowledge and data automation Pipelines that turn hours of meetings, video, or raw data into structured reports and automated alerts.

What AI gives +15–50%

Productivity gains measured in field studies: 15% in customer support, 26% in software, 50% in marketing.

Stanford AI Index 2026 · Economy chapter
What it takes back when nobody checks 40%

Nearly 40% of the time AI saves goes back into people fixing and checking its work by hand.

Workday survey, January 2026 · 3,200 employees

We build that check into the system.

Our productAI-poweredEarly access

Miloop Editor

Record once. Publish everywhere

Your own AI editor, set up for your show. It turns each recording into a finished episode with subtitles and graphics, plus shorts for every platform you post on. Now accepting interviews, talk shows, solo shows and shorts.

See it in action

Early-access spots are limited.

What we do

From your first assessment to ongoing support

01 / DIAGNOSE

What you walk away with

02 / BUILD

What you walk away with

03 / BUILD

What you walk away with

04 / BUILD

What you walk away with

05 / VERIFY

What you walk away with

Proof in production

Systems we have designed, built, and shipped

Miloop Editor

Portfolio

Three systems you can try, read, or watch for yourself

Live

Multi-Agent Pipeline

FactLoop Newsroom

Type a topic in any language and watch it research, write, and fact-check a sourced article, live.

Try it live

0.794 Held-out kappa

97.2% Retrieval Hit@4

Case study

RAG Evaluation

Driftboard RAG Eval

An evaluation framework for RAG, stress-tested against a fictional knowledge base. It measures what the system does when it has no answer, and checks its own judge for blind spots.

Read the case study

Case study

Agent Permissions

DeskLoop

An IT and HR helpdesk agent whose permission check sits outside the model, in a tool server of its own. Persuading it gets you no further, and a confirmation belongs to one action and nothing else.

Watch the walkthrough

About Miloop AI

Most AI looks good in a demo. Few systems hold up against a real deadline and a real edge case. We build the kind that do, and hand it over running on your own infrastructure, with a runbook your team can change.

The saving shows up in the first month. The capability stays with the company.

Learn About Us