About HEU.AI

HEU AI LLC is a US company building autonomous systems that run real business workflows in production.

Most companies have now watched a convincing AI demo. Far fewer have something running that a team depends on by Monday morning. We exist for the second part: taking a workflow that costs your business real money to run by hand, and handing it to a system that runs it continuously, measurably, and inside the tools you already own.

Why we started

HEU.AI grew out of a decade of enterprise software work, and out of watching the same failure repeat. A company would buy an ambitious platform, run a pilot that impressed everyone in the room, and then quietly return to the spreadsheet six months later. The technology was rarely the problem. The problem was that nothing had been built to survive contact with a real team, real data, and a real Monday.

When autonomous agents became genuinely capable, that gap got wider, not narrower. Building something that answers a question well became easy. Building something that can be trusted to act, repeatedly, without a person checking its work, stayed hard. That is the part we chose to specialize in, and it is why our engagements are measured by what is running in production rather than by what was delivered as a document.

Today we build autonomous agents, retrieval systems, MCP servers, and the data infrastructure underneath them for growth-stage software companies and established enterprises. You can see what that looks like in practice on our case studies.

What we are trying to do

Make autonomous systems ordinary infrastructure for the businesses that were never going to get them: the teams without a research lab, without a twelve-month platform budget, and without the appetite to be someone's experiment.

That means being honest about what a system can own today, refusing the work that would look impressive and fail quietly, and pricing engagements against outcomes our clients can point at.

How we build

Four rules decide most of the arguments we have internally. They are also the fastest way to tell whether we are the right partner for a piece of work.

One use case first

Every engagement starts by picking the single workflow with the clearest return, shipping it, and proving it. Platform-wide rollouts come after something is working in production, not before.

Outcomes, not tools

We build systems that own a result end-to-end. If a person still has to supervise every step, the automation has not done its job, and we treat that as unfinished work.

Grounded, not improvised

Answers come from your documents and systems, with sources attached. We would rather a system say it does not know than produce a confident invention that someone acts on.

Fits the tools you have

Our work lands inside the CRM, ticketing system, and messaging tools your team already uses. Adoption fails when it depends on people opening one more dashboard.

What working with us looks like

Five stages, each with a point where you can stop. Every stage below links to an engagement where you can see it in practice.

  1. Discovery and process mapping

    We sit with the people doing the work and map the process as it actually runs, including the workarounds. We identify where time is lost, where errors enter, and which steps genuinely need a person. The output is a written assessment, whether or not you proceed.

    Where you can see this

    Quote assembly became a process a manager can inspect, rather than an outcome only one long-serving person could explain.

    Quoting and planning knowledge automation
  2. Proof on one workflow

    One real workflow, built properly against your own data, in a short cycle. Not a demonstration. The purpose is to establish whether the approach holds in your environment before the scope grows.

    Where you can see this

    A single estimation workflow, scoped tightly enough that two assessors could check the result against each other.

    Estimation and assessment support
  3. Build and integrate

    Production build connected to your live systems, with permissions, audit trails, approval gates, and failure handling designed in. Delivered in reviewable increments rather than one release at the end.

    Where you can see this

    Graded autonomy, hard stops, and a full audit trail were specified before the first agent was allowed to act.

    Autonomous agents with defined authority
  4. Handover and enablement

    Technical documentation, runbooks, and training for your team, so the system becomes something you operate rather than something you depend on us to run.

    Where you can see this

    House style is held as editable configuration, so the client refines it without a redevelopment cycle.

    Central AI content standardization service
  5. Operate and improve

    Production monitoring, evaluation of model output quality, incident response, and an agreed cycle for extending the system as the business finds the next process worth automating.

    Where you can see this

    Every model call is observed and evaluated, so regressions surface as data rather than as user complaints.

    AI-assisted recruitment operations platform

What we tell clients before they buy

AI removes the repetitive portion of a process. It does not remove the need to understand the process. Organizations that map the work honestly get a working system; organizations that automate a broken process get a faster broken process.

The company

HEU AI LLC is the contracting entity for every client engagement, from the first statement of work through to support. Your project is scoped and built without handoffs, from discovery through to handover.

500+
Projects Completed
50+
Enterprise Clients
99.9%
Uptime
10+ yrs
In Enterprise Software

Capabilities

Tell us the workflow that costs you the most

A free consultation, and a straight answer on whether an autonomous system is the right fix for it.