AI ENABLEMENT LAB
Your team has the tools. The Lab changes how they work.
One Lab, built for your company or your portfolio, on the workflows your people actually run. We interview your team first, rebuild their real work with them in the room, then run weekly office hours for the four weeks after it.
What a Lab Is
Built on your work, not a curriculum.
A Lab is a tailored engagement for one company, or for one group of leaders across a portfolio. Before we schedule a room, we interview your leads and the people doing the work, and we look for the assets your team rebuilds every week: the board deck assembled by hand, the reconciliation nobody trusts, the report that eats a Friday.
Those become the material for the day. When your team sits down with the tools, the workflow on screen is their workflow and the output is something they were going to have to produce anyway. A Lab is built for one company rather than delivered from a curriculum, so what your team builds on the day is work they already owed someone.
Some rooms have people who have never opened an AI tool and some have engineers already shipping with one, so the day is hands-on rather than presented, with Elios operators moving between tables. Our operators work inside your environment, under the controls your leads set.
Interviews with your leads and the people doing the work
The weekly assets and workflows worth rebuilding first
The tools your company already bought, or help choosing them
Your technology leads set up access, controls, and connectors before the day
A named outcome, with the baseline set in the pre-work and read back at the end
How a Lab Runs
Tailor. Run. Follow through. Read back.
A fixed-fee engagement: a half-day onsite for up to thirty people, then a weekly two to three hour office hours block for the four weeks after it. Elios travel is included.
Tailor
We interview your people, pick the workflows, and build the day around them. Your technology leads own the setup: they install the tools from our checklist with our engineers on the call, set budget and privacy controls, and approve which connectors and shared skills are allowed. The pre-work is also where we confirm the scope together before the onsite goes on the calendar.
Run the Lab
A half-day onsite for up to thirty people. A short demo, then straight into the work: small groups rebuilding a real workflow with an Elios operator at the table, because past thirty people we cannot put an operator next to everyone who gets stuck.
Follow through
A weekly two to three hour office hours block for the four weeks after the Lab. People bring the work in front of them, we unblock it live, and the workflows rebuilt on the day get their first runs against real deadlines.
Read back
An executive session on what changed, what your team now owns, and the next thing worth doing. No slide-only handoff: the readback names concrete next steps against the outcome you set in the pre-work.
“The work on the table is your work.”
Who Runs One
One company, one business unit, or a whole portfolio.
A company that bought AI seats and is not seeing usage
Licenses are live, a few champions are doing interesting things, and everyone else works the way they always did. The Lab puts the tools inside the workflows people are already accountable for.
A business unit with work it rebuilds every week
Finance closing by hand, revenue teams assembling the same pipeline view, engineering and IT carrying manual toil. We take the specific asset your team recreates on a cycle and rebuild it with them, then keep unblocking it for four weeks.
A private equity firm working across its portfolio
Bring the same role together from several portfolio companies, finance leaders or revenue leaders in one room, and build against the problem they share. The pre-work is where we look for that shared problem before anyone travels.
For a portfolio, we build the cohort around one role across the participating companies: finance leaders, revenue leaders, or HR leaders in one room, with the same thirty-person cap on the onsite and each company's time on its own work set in the pre-work.
Where a Lab Lands
Where we recommend starting.
Revenue
Pipeline, proposals, and account research
Rebuild the account brief, the proposal draft, and the pipeline review so the work arrives ready for a human to judge instead of assembled from scratch.
Finance
Close, reporting, and collections
Take the reconciliations, variance commentary, and invoicing follow-up that eat a cycle, and rebuild them with the controls your finance leads need to trust the output.
Engineering and IT
Delivery, support, and internal toil
Agentic coding on your codebase, ticket triage, runbooks, and the internal requests that queue behind one person who knows how the system works.
AI fluency
The whole team, not the champions
Get everyone past the demo: what these tools are good at, where they fail, how to check them, and how to write down what worked so the next person can use it.
Security and governance
Controls people can actually work inside
Access, data boundaries, approved connectors, and where a person still has to approve, set with your technology and security leads.
Proof
The format came out of doing it.
We built this shape with a consumer brands company. The pre-work turned up a live commercial deadline, the launch of a new product line, so the hands-on session was built around that launch and the team spent it producing the real thing rather than a sample exercise.
The follow-through is the part we would not drop. Office hours after the onsite kept people moving when their own deadlines hit, and the engagement led to further work with the same team. That is why the Lab is scoped as one fixed engagement with the follow-through included.
What You Own After
The capability stays with your people.
A Lab is built so your team ends up running the work. The workflows your team builds live in your systems, under your own controls, with ownership terms set in the engagement agreement.
The rebuilt workflows, running in the tools your company already pays for
Prompt and skill libraries written down for the people who were not in the room
The setup your technology leads approved: access, controls, and connectors
Named owners inside your team for each workflow the Lab touched
A readback your executives can act on, with the next engagement named if there is one
PARTNER NETWORKS
We partner with the leading AI labs.
Elios is part of the OpenAI Partner Network and Anthropic's Claude Partner Network.
That context complements our hands-on experience deploying AI inside enterprise workflows, systems, and teams.
Frequently Asked
Frequently Asked Questions
A tailored, hands-on engagement built to get a team working AI-native on its own work. Elios interviews your people first, builds a half-day onsite for up to thirty of them around the workflows they run today, holds a weekly two to three hour office hours block for the four weeks after it, and closes with an executive readback.
Pre-work interviews, then a half-day onsite, then a weekly two to three hour office hours block for four weeks, then the readback. A portfolio cohort runs the same shape, built around one role across the participating companies.
A Lab is a fixed-fee engagement rather than an hourly one. The fee covers the pre-work, the onsite, the office hours block, and the readback, with Elios travel included; your AI tool licences and seats stay yours. Tell us the scope and we will quote it, including whether a portfolio cohort or a single business unit is the better shape.
The ones your company already bought. Elios is part of the OpenAI Partner Network and Anthropic's Claude Partner Network. We work across the leading models and help you choose if that decision is still open.
Up to thirty per onsite. The day is hands-on, with Elios operators moving between tables, and past thirty people we cannot put an operator next to everyone who gets stuck. Larger organizations run Labs one function or team at a time.
A weekly two to three hour office hours block for four weeks, run on your real deadlines, then an executive readback covering what changed, what your team owns, and the next thing worth doing. Where a bigger problem turns up, it can continue as a Deployed Specialist or an Embedded Team.
Give us one workflow. Let us prove it.
Tell us what your team does every week that should not take as long as it does. We will tell you whether a Lab is the right way to start.