SC Nexus · AI agents

Hand the repetitive work to a system that actually does it.

There's work in your business that runs on a fixed procedure — same inputs, same steps, same outputs. That's automatable. I build agents that plug into your actual stack, run the task end to end, and escalate to a human when confidence drops.

Not a chatbot

A chatbot answers questions. An agent executes a process.

It ingests the inbound — email, form, ticket, webhook — pulls context from your systems of record, runs the task through the model with your business rules as guardrails, writes the result back into your tools, and flags a human on anything it isn't confident about. It runs on a trigger or a schedule, and logs every action so you can see exactly what it did and why.

I start narrow on purpose — one process, internal-facing, low blast radius — then instrument it, measure it against how a person did the job, and widen scope once the numbers hold.

  • Lead intake, qualification, and routing into your CRM
  • Quote and proposal generation from your own pricing logic
  • Inbox and document triage with structured extraction
  • Recurring reports assembled from multiple sources
  • Any deterministic, rules-based task a person repeats

Priced per project after a scoping call. Compare it to what the role costs loaded — not to what software costs.

The ten roles, written out

There are not a hundred different agents. There are ten, pointed in different directions — and every one of them is written up in the Library.

Each role has its own page: what the job actually is, the part that is harder than it looks, and what it looks like in 59 industries in their own vocabulary. Start with the role that sounds like your week.

Open the Library →

All ten agent roles — the Follow-Up, the Intake, the Drafter, the Watcher, the Answer Desk, the Scribe, the Reporter, the Reconciler, the Connector, the Gatekeeper.

How we start

The goal isn't a clever demo. It's a system you'd trust with a real slice of your operation.

So we find the highest-volume, lowest-risk task, define what "correct" looks like, and build to that. It runs alongside a human with full logging until its accuracy is boringly reliable — then we widen scope and hand it more responsibility.

  • 01Find the highest-volume, lowest-risk task to hand over first
  • 02Define success — what "correct" looks like, measurably
  • 03Build against your real data, tools, and business rules
  • 04Run it human-in-the-loop with full logging until it's proven
  • 05Widen scope and take on the next process

Common questions

Is this just a chatbot with extra steps?

No. A chatbot generates text; an agent takes actions in your systems — it reads, decides, writes back, and escalates. You're handing off a task, not adding a Q&A widget.

What about accuracy and mistakes?

Everything starts human-in-the-loop on a low-risk task, flagging low-confidence cases and logging every action. We measure its accuracy against a human baseline and only widen its autonomy once it's proven. You're never trusting a black box on day one.

What can it plug into?

If it has an API or an inbox, it can usually connect — your CRM, email, docs, spreadsheets, ticketing, internal databases. Mapping what it needs to touch is part of scoping.

Is my data safe?

We scope data access to only what the task needs, keep it inside your own tools where possible, and set clear boundaries on what the agent can see and do. That's part of the scoping call.

What does it cost?

Priced per project after we scope it. The honest way to weigh it: compare it to the loaded cost of the person doing that task today, not to what a piece of software usually costs.

Start a conversation

Tell me what's slow, expensive, or held together with tape. If I'm not the right fit, I'll say so on the first call.

I reply within one business day.

Prefer email? luke@scnexus.ai · or call (317) 225-6105.