One Practice for
Everything Agentic

From stalled pilot to governed production system to an agent that keeps running. Every path starts small, priced, and dated.

Start With One Workflow
Explore Agents by Industry ↓

You’ll talk to a senior engineer, not a salesperson.

RTS Labs engineers at work
The gap everyone is standing in
85%

already use GenAI in the enterprise

Economist, Unlocking Enterprise AI

22%

are confident their infrastructure can run it

same report

40%+

of agentic AI projects canceled by end of 2027

Gartner

Systems already running in production for
Why AI projects stall

Your AI Problem Probably Is Not the Model

The demo is the easy part.Production is where the real work starts.

01

The workflow is unclear

The team built a demo before deciding exactly what work the AI should own.

02

The data is scattered

What the agent needs lives across documents, databases, email, and business systems.

03

The agent cannot safely act

Security and legal will not approve an agent without boundaries, approvals, and auditability.

04

The pilot never became real

The demo worked. Integration, testing, adoption, monitoring, and ownership did not.

90 seconds

See What a Production Agent Actually Looks Like

Controlled action, not unlimited autonomy.

01

Work arrives

Document, task, alert, or exception.

02

Agent reasons

Reads context and approved data.

03

Human checkpoint

Approval where risk requires it.

04

Agent acts

Updates systems, routes work.

05

Everything logged

Decisions and outcomes stay visible.

No robots. No orbs. Just the work, before and after.

How we work

Bring us one workflow. We prove it pays, build it properly, control it so security signs off, and keep it running after everyone else has moved on.

The RTS Labs office

The whiteboard where most engagements start. No slideware, no discovery theater.

The lifecycle

One Lifecycle. Start at Whichever Stage Hurts.

Stalled pilot? Start at Assess. Already built something security won’t approve? Start at Govern. Agent running but nobody watching it? Start at Run. Platform vendors start their lifecycle at your data; ours starts at your problem.

Stage 01
Assess

Audit every AI initiative. Go, kill, or fix, in two weeks.

Pilot Rescue →
Stage 02
Design

The workflow, the data, the buy-vs-build call, the ship date.

How We Design →
Stage 03
Build

Senior engineers ship in your repo, in your standup, on your sprint board.

Embedded AI Teams →
Stage 04
Govern

Identity, audit trails, human gates, kill switches. Standard.

Agent Governance →
Stage 05
Run

Anyone can demo an agent. Keeping one durable, observable, and on budget is the job.

AgentOps →
Agent library

Which Agents Actually Fit Your Business?

Start with industries where we already understand the workflows, systems, controls, and economics. Every agent below is one we have scoped, and each one links to how it works.

What agents actually do

Six Jobs an Agent Can Own

Not every workflow needs an agent. These are the classes of work where intelligence plus action removes meaningful manual effort.

Monitor

Watch transactions, shipments, work orders, alerts, or operating signals.

Research

Pull information from approved systems, documents, and data sources.

Decide

Classify, prioritize, recommend, and route based on context.

Create

Draft reports, memos, responses, summaries, and operational documents.

Act

Update systems, trigger approved workflows, and complete defined tasks.

Escalate

Know when confidence is low and send the work to the right person.

The adoption ladder

Do Not Jump Straight to Autonomy

The safest path is to give AI more responsibility as the workflow proves itself.

Measure the real work

Track volume, delays, exceptions, handoffs, and manual effort before deciding what AI should do.

  • Where does work stall?
  • Which exceptions consume the most time?
  • What can be measured before automation?
Outcome
A workflow with a baseline and a business case.

Automation is earned, not assumed.

Is the workflow worth it?

Run Your Numbers Before You Run an Agent

Before we recommend building anything, we look at the economics. You can too, right now.

Frequency × Cost of Work × Improvement

If the outcome is not measurable, it is probably not the right first agent.

Bring Your Number to a Scoping Call
Estimated monthly opportunity
$2,200
$26,400 per year · 40 hours returned monthly
Entry points

Start Small, On Purpose

Stuck pilot

AI Pilot Rescue

From $30K

2 weeks · delivered as the Lumynate ROI Audit

A go/kill/fix verdict per initiative. Half the fee credits against your build.

Diagnose Your Pilot →
Risk + controls

Governance Assessment

From $25K

2 weeks

Your agent estate mapped against NIST-aligned controls. Framework published open.

Assess Your Risk →
Need the talent

Embedded AI Teams

From $25K/mo

Resident FDE

A senior AI engineer in your team, backed by the full RTS bench.

Meet the Model →
Ready to build

Production Agent Build

Fixed scope, fixed ship date

One workflow shipped as a governed system, 90 days of run support included.

See How We Build →
Platform-agnostic, on purpose

Ask a Platform Vendor Which Platform You Need. Guess What They'll Say.

We don’t sell a platform, so our answer can change with your workflow. Sometimes the right call is a product that already exists. Sometimes it’s custom. Usually, it’s both.

Verdict: Deploy

A platform already fits

When a proven agent platform covers your workflow, we say so by name, then handle the integration, the governance, and the rollout inside your stack.

Verdict: Build

The workflow is your edge

When the workflow is what makes you money, renting it from a vendor makes no sense. We build it custom, in your repo, and you own it.

Verdict: Both

Most companies land here

Platforms for the standard work, custom agents for the differentiating work, one governance and run layer across all of it.

Whatever runs, our guardrails and operations layer wrap it. One accountable partner across every platform you own. See how we decide →

The receipts

Hundreds of Systems Shipped. Six Agents You Can Inspect.

Named production agents, real workflow traces, and the numbers behind them live on our development page, along with the tech stack and delivery model.

See Agents in Production
RTS Labs engineers in a working session

The senior engineers who ship it are the ones you meet on the call.

Need to go deeper?

Fair Enough. The Longer Answers.

What is agentic AI consulting?

It is help with the whole lifecycle of a system that takes action, not just help building a model. An agent reads context, decides, and then does something in a system of record. That last part is what changes the work: it pulls in security review, permission design, human approval, audit trails, cost control, and somebody operating it after launch. A consultancy that only builds hands you the demo and leaves the hard half. We run all five stages, and you can start at whichever one hurts.

No, and most clients don’t. Stalled pilot, start at Assess. Something built that security won’t approve, start at Govern. An agent running that nobody is watching, start at Run. The lifecycle is how the work fits together, not a queue you have to join at the front. Platform vendors start their lifecycle at your data because that is what they sell. Ours starts at whichever stage is costing you money.

Usually in the parts that are nobody’s full-time job. Teams that can build a good agent often have no eval harness in CI, no drift review, no tested kill switch, and no rota when something goes wrong at 2am. That is not a skills gap, it is a staffing one. We also get hired for the honest second opinion on a build the team is too close to. If your team has all of it covered, we will say so on the call rather than sell you a pod.

Fixed fee at every entry point, so you can approve it without a blank cheque. The two-week diagnostics are priced on this page. Builds are fixed scope and fixed ship date, quoted after the diagnostic, and half your diagnostic fee credits against the build if you proceed. Embedded engineers are a monthly subscription with a three-month minimum. Nothing here is time and materials, and there are no change orders inside a two-week engagement.

Ninety days of run support ships with every build, because an agent that nobody watches degrades quietly. Uptime stays green while quality, cost, and the human approval gate all move. After those ninety days you either take it in-house with the instrumentation already in place, or we keep operating it. Either way you leave with the evals, the dashboards, and the runbook, because they are yours.

Every engagement above runs on Lumynate, the RTS Labs system for building and operating production AI agents.

Method
Library
Guard
Teams
Run

Bring Us One Workflow

Thirty minutes with a senior engineer. You’ll leave knowing whether it’s a build, a buy, or a bad idea, and exactly what proving it would cost.

Book a Scoping Call

Workflow. Systems. Current pain. Desired outcome. That is enough to start.