Your AI Lab, Built Inside Your Business
Most companies know AI should be changing how they operate and have no realistic way to get there. The tooling is available; the capability to apply it is what is missing. We stand up an applied AI lab inside your company, run it with your people until it is shipping on its own, and then hand it over.
What is an AI Lab?
An AI lab is a standing capability inside a company that finds, builds, and ships applied AI into the business systems that company already runs. It has an environment, a ranked backlog, engineers, and work in production, which is what separates it from a research group or a center of excellence producing recommendations for somebody else to act on.
Mach12 builds that capability for you. We stand the lab up inside your security boundary, connect it to your ERP, CRM, HCM, PLM, and data platform, work the backlog with your people, and ship into production. Then we train your team, hand over the playbooks and the platform, and scale down.
The model is industry neutral and function neutral. Finance, supply chain, revenue, operations, engineering, HR, service, IT, and compliance share the same underlying problem: work that is well defined, high volume, and currently done by people who could be doing something harder. What changes between one company and the next is the vocabulary, the systems, and the regulations the lab has to respect.
Weeks
to the first production build
Something running in your environment, against your data.
Your boundary
is where your data stays
The lab runs inside your security perimeter, or in a compliant environment we host for you.
Your team
runs it at the end
We build the capability into your organization and then step back out of the way.
How It Runs
We run them in this order on purpose. Programs tend to stall when discovery runs for two quarters before anything is built, or when something impressive gets built that was not connected to a system of record.
Stand Up
Weeks 1 to 4
We build the lab inside your boundary. Secure model access, connectors into the business systems you already run, guardrails, access control, and an evaluation harness so quality is measured and not assumed. Your data stays yours.
- Secure environment inside your cloud or one we host for you
- Connectors into ERP, CRM, HCM, PLM, ITSM, and your data platform
- Guardrails, access control, logging, and a real audit trail
- Evaluation harness so each build is measured before it ships
Find the Work
Use case discovery
We map your value streams and score each candidate use case on value and feasibility. What comes out is a ranked, costed backlog with named owners and a first build already in motion.
- Value stream mapping across the functions that matter
- Use case scoring on value, feasibility, and data readiness
- A ranked backlog with named owners and dates
- The first build starts before the assessment is finished
Build and Ship
Weeks, not quarters
Agents, applications, and automations built against your real systems and your real data, shipped into production with the people who use them. Each build is instrumented so you can see what it returns.
- Agents and applications running against live systems
- Deployed into production on your systems
- Adoption designed in from the first sprint
- Measured value, reported against the business case
Hand Over
Your lab, your people
Your team takes it over. We train them, leave the playbooks and the platform behind, and scale down as your capability scales up. What you are left with is a working AI function your own people run.
- Your engineers and analysts trained on the platform
- Playbooks, patterns, and standards documented and handed over
- A governance model your team can run
- We scale down as your capability scales up
What You Keep
A lab team
Architects, engineers, and domain leads who have built this before, working inside your organization alongside your people rather than presenting to them from the outside.
A platform
The environment, connectors, guardrails, evaluation harness, and agent infrastructure. Built during stand-up, owned by you, and still there when we are not.
A method
A repeatable way to find, score, build, and ship use cases, and the governance model to keep doing it. In our experience this is the part most organizations are missing.
A head start
The applications we have already built. Where one of them fits your problem, you start from working software instead of a blank page.
Ways to Start
Priced on the outcome rather than by the hour or the seat. Most clients start narrow and widen once the first build is in production.
Embedded Lab
We run your AI lab with you.
A standing team inside your organization: architects, engineers, and domain leads working your backlog continuously. The model we would suggest where AI is an ongoing program.
Best for
Companies that want a durable internal capability and a steady stream of shipped work.
Lab Sprint
A defined use case at a fixed scope.
A focused engagement against one defined use case, from discovery through production. Useful for proving the model in your environment before committing to more.
Best for
Companies that want evidence before they scale, or that have one painful problem to solve now.
Accelerator Deployment
Start from something already built.
Deploy one of the applications we have already built, configured and extended for your environment. You inherit the head start and the lab adapts it to fit.
Best for
Companies whose problem closely matches something already in the library.
Across the Business
A lab is not an IT function. It works wherever there is defined, high-volume work sitting on top of a system that already holds the answer.
Applied to What You Already Run
Connectors are built during stand-up, before any use case ships. You do not replace anything first, and your data does not leave your boundary.
ERP
SAP S/4HANA and ECC, Oracle, NetSuite, Dynamics 365, Infor
CRM & Revenue
Salesforce, Dynamics, HubSpot, CPQ and CLM platforms
HCM & Workforce
Workday, SuccessFactors, UKG, Paylocity, ADP
PLM & Engineering
Teamcenter, Windchill, SAP PLM, Jira, Git platforms
Service & ITSM
ServiceNow, Zendesk, Jira Service Management
Data & Analytics
Snowflake, Databricks, BigQuery, Power BI, SAP BW
Common Questions
- What is an AI lab?
- An AI lab is a standing capability inside a company that finds, builds, and ships applied AI into the business systems the company already runs. It has an environment, a ranked backlog, engineers, and work in production, which is what separates it from a research group or a center of excellence. Mach12 stands one up, runs it with your people, and hands it over.
- How is this different from hiring a consulting firm?
- A consulting firm sells you a project and leaves with the capability. Here the capability is the deliverable, and building it into your organization is the work. We do the delivery as well, and the first builds are ours. The measure we would hold ourselves to is whether your team is still shipping after we scale down.
- How is this different from buying an AI platform?
- A platform gives you tooling and leaves the hard parts to you: which use cases are worth doing, how to connect to systems that were not designed for this, how to evaluate quality, and how to get anyone to adopt the result. The lab is the operating capability around the tooling, and there is no license to buy.
- How long does it take to stand up?
- The environment and the first connectors are typically live inside four weeks. The first production build usually ships inside the first quarter. Discovery runs in parallel rather than in front, since our view is that an assessment which delays the first build by a quarter is a poor trade.
- Where does our data go?
- It stays in your boundary. The lab runs inside your cloud, or in a compliant environment we host for you where your regulatory posture requires it. Your data is not used to train anyone else's model. That gets established and verified during stand-up.
- Do we need to modernize our ERP first?
- No. The lab connects to what you run today, including older systems. If a modernization is already planned, the lab can work either side of it, and the connectors get rebuilt against the new platform at cutover. Our view is that waiting for a clean landscape before applying AI costs years.
- What if our data is not ready?
- Data readiness is scored as part of use case selection, so the first builds get chosen where the data supports them. Several common use cases improve data quality as a side effect, since the exceptions finally surface. Few organizations have clean data, and we would treat it as a sequencing question.
- Which industries do you work in?
- The lab model does not change by industry. What changes is the vocabulary, the systems, and the regulations it has to respect. Our deepest regulatory experience is in aerospace, defense, and government contracting, which has its own section on this site.
- Do we have to use your software?
- No. The accelerators are available where one fits your problem, and starting from working software is faster than starting from a blank page. Most of what a lab builds is specific to you.
- What happens when the engagement ends?
- Hand over covers it. Your engineers and analysts are trained on the platform, the playbooks and standards are documented and handed across, and the governance model is one your team can run. We scale down as your capability scales up. Plenty of clients keep us on for new build capacity after that, and by then it is a choice rather than a dependency.
- How is this priced?
- By the engagement model and the outcome, not by the hour or the seat. An embedded lab, a fixed-scope lab sprint, and an accelerator deployment are priced differently. We scope that with you up front so you know what you are investing in.
- Who is behind Mach12?
- Mach12.ai was founded by the partners behind Revelation Technologies, a consulting firm that has spent years doing SAP implementations, ERP modernization, and operational transformation for complex, heavily regulated organizations. The lab model came out of running it on ourselves first.
Stand Up Your Lab
Tell us what your business runs on and where the work is piling up, and we will give you our read on whether a lab is the right answer.
Start a Lab