---
title: "Angstrom Systems | Agentic AI Systems, Minneapolis"
description: "Angstrom Systems builds agentic AI systems for small and mid-size businesses: specified adversarially, verified before delivery, running in production today."
url: "https://angstromsys.com/"
---
Angstrom Systems · Minneapolis

# AI systems that run the work, not demo it.

Angstrom builds agentic systems for small and mid-size businesses: software that owns a job end to end, escalates when it should, and gets verified before anyone relies on it. I'm Andrew Kaiser — you talk to the person who builds it, and the work arrives with receipts.

[Tell me about your problem](https://angstromsys.com/contact/) [See how it gets built](https://angstromsys.com/method/)

Running in production

[

Surfaced

Your online presence, run for you

](https://angstromsys.com/products/#surfaced)[

ForgeField

Lead capture for field services

](https://angstromsys.com/products/#forgefield)[

SimplyEngaging

Event booking, handled end to end

](https://angstromsys.com/products/#simplyengaging)[

Misen

Agent-native dining discovery

](https://angstromsys.com/products/#tenet)

## Most AI projects die at ambiguity.

The demo worked. The spec lived in someone's head. The real system never arrived. Nobody was incompetent and nobody was lying — the requirements were simply never forced to be true and complete before code got written.

Generating code stopped being the constraint a while ago. What's left is the harder half: deciding what is actually supposed to be true, and then proving that it is. That's where this practice puts its weight.

The method

## First I learn your work. Then the machine builds it.

I sit with the people doing the work, find where the process actually breaks, and write the specification myself — that part isn't delegated. From there the build is decomposed into tasks with binary success criteria and executed behind two independent verification gates. I own the judgment; the machine owns the execution and has to prove it.

[Read the method, and the receipts →](https://angstromsys.com/method/)

This website was rebuilt through that pipeline.

The verifier rejected the work five times in one session, and not once was the code defective — every rejection caught a decision the work wasn't authorized to make. The whole ledger is published, because the execution layer is held to a standard I don't get to wave through when it's inconvenient.

## Six ways this shows up

Each one traces to a system running somewhere right now, and to a product on this site.

[01

### Agentic systems engineering

Software that completes work instead of answering questions about it.

](https://angstromsys.com/services/#agentic-systems)[02

### AI visibility engineering

Be in the answer when an assistant recommends a business like yours.

](https://angstromsys.com/services/#ai-visibility)[03

### Lead capture and field ops

The layer between a phone call and a signed job.

](https://angstromsys.com/services/#lead-capture)[04

### Communications automation

Stay reachable when nobody can pick up the phone — compliantly.

](https://angstromsys.com/services/#communications)[05

### Support continuity

Incident capture that reports what actually happened, as it happens.

](https://angstromsys.com/services/#support-continuity)[06

### Vertical AI directories

Industry data an agent can query and answer from with facts.

](https://angstromsys.com/services/#directories)

[All six, in detail →](https://angstromsys.com/services/)

Selected work

## A job that used to clear an afternoon now takes about twenty seconds.

A manufacturer's sales team spent two to four hours rewriting every incoming RFP around their own catalog. A knowledge base and a processing layer did the translation instead — and flagged anything it wasn't sure about rather than guessing.

[See the work →](https://angstromsys.com/work/)

~20s

from 2–4 hours, per RFP

Clients are described by industry and situation, never by name. Numbers appear only where the business confirmed them.

## Latest writing

[All posts →](https://angstromsys.com/blog/)

[

April 13, 2026

### AI Consulting for Small Business: A Practical Guide

A practical guide to AI consulting for small business — what it delivers, how to choose a consultant, real use cases, and questions to ask before you hire.

Read it →](https://angstromsys.com/blog/content-brief-ai-consulting-for-small-business-a-practical-guide/)[

March 29, 2026

### Why Small Businesses Should Build AI Agents (Not Buy SaaS)

Learn how to build AI agents tailored to your business instead of renting generic SaaS. Real examples, cost comparison, and the 3-step process we use to build custom AI agents for small businesses.

Read it →](https://angstromsys.com/blog/blog-post-why-small-businesses-should-build-custom-ai-agents-not-buy-saas/)

## Start with a conversation.

No pitch and no agenda — just enough questions to be honest about whether this is worth building, and whether I'm the right person to build it.

[Get in touch](https://angstromsys.com/contact/)