Mei is a forward-deployed AI engineering firm. Our engineers embed with your team and ship AI into your operation — built on nearly a decade of putting AI into production at scale. This page is how we explain what that means and show what we've already built.
Since 2016
building production AI
20+ products
shipped to date
2M+ users
across our products
1.59B
message training corpus
A forward-deployed engineer is an outside AI engineer who comes into your business and builds a product as if they were an employee — combining technical skill, product sense, and an understanding of how your business actually makes money. We've done this for our own products for nearly a decade; now we do it for the companies that hire us.
In practice, that means we don't hand you a strategy and leave you to build it. We identify the highest-return uses of AI with you, then build the working software ourselves — AI that does the work your employees do today, integrated into the systems you already run. We don't change how your team works: what you get is effectively a new AI employee that uses the same tools your people already use. Most of the work in any engagement is that integration, not the model itself. If your team does it on a computer every day, we can usually build AI to do it more efficiently.
Firms like Palantir and OpenAI do this at million-dollar scale for government and big tech; at the other end, you can hire and manage your own engineers. We sit in between — senior builders, embedded, focused on one high-value workflow at a time. And we come at it the other way from the big platforms: their forward-deployed hires are brought on for pure technical delivery — read the job descriptions, there's nothing in them about your business or whether the work actually gets adopted. Nearly a decade shipping and operating our own AI products means we think about your workflow, your economics, and adoption first, and the code second.
Roughly nine in ten enterprise AI efforts stall before production — and rarely because of the technology. They fail for the same handful of reasons, and every one of them is what a forward-deployed engineer is there to prevent.
It launches as an experiment with no daily volume and no owner — so nothing depends on it, and it quietly dies.
The #1 thing we hear: 'the AI isn't doing what I wanted.' The demo dazzled; the real workflow exposed every gap no one scoped for.
The engineers who can actually build this tend to build for themselves. Talent that is both technical and fluent in your business is genuinely scarce.
A chatbot in a sandbox isn't a deployment. If it doesn't drive the tools your team already uses, it never leaves the pilot.
We're selective about where we start. The work has to be a real, daily pain point — pick the wrong target and we both lose.
If your employees do it on a computer every day, we can build AI to do it — with deep specialty in customer communication.
AI that does the repetitive digital work your team does today — reports, analysis, data entry, and form processing.
Inbound calls and messages handled by AI that books appointments and writes records straight into your CRM or production software.
Agents that hold real conversations over SMS, chat, email, and messenger apps — in 50+ languages.
AI that answers and places phone calls, works on any handset, and runs on carrier infrastructure.
Bespoke models and endpoints built to your data and workflows, deployed behind your own brand.
We wire AI into the tools you already run — CRMs, support desks, billing, and the vendor software your business depends on.
Every relationship starts with a fixed-scope, two-month build — a working tool live in your workflow, starting at $100,000. It's our minimum engagement, and how we get to know each other before any larger build.
We identify the task to automate, confirm it can integrate with your existing software, scope the requirements, and agree on milestones and a roadmap.
We build the working system, iterating day-to-day with an internal liaison on your side.
We harden the build and test it against your real cases — including the edge cases.
We deploy into your live workflow, exchange documentation, and write the SOPs your team runs on.
The build is our job. But an AI deployment only sticks when it's treated as a real initiative on your side — not a side project. Before we start, we look for four things.
Your internal lead is C-suite or the owner — someone with the authority to change a workflow, not just observe it. No exceptions; it's the clearest predictor of success.
Roughly one full-time-equivalent of your team's time through the build, from the people who actually do the work today.
A live, high-volume task — not an aspiration. We build for a specific job, with a specific user in mind.
You have to actually use it. A sherpa can carry you up the mountain, but if you don't walk, it's wasted — the first milestone that matters is real customers on the system.
Much of our client work stays confidential. Here are products you can look at — built for clients, with their partners, and as standalone ventures. More to come.
Built for industry coach Tom Ferry: an AI trained on his body of work that agents can ask for scripts, strategy, and on-demand coaching.
Read the case studyA standalone AI product built for the marketing space.
Read the case studyAn AI agent that answers every call, qualifies the job, and books it straight into ServiceTitan — end to end.
Read the case studyAI intake, e-signing, and treatment follow-up, with every conversation written back to the case file in Filevine.
Read the case studyAn AI call-and-response system that handles inbound client intake and routing for law firms.
Read the case studyA standalone consumer product that turns a child's idea into an illustrated, personalized storybook — built and operated on our own stack.
We're an AI lab that has put 20+ products into the world since 2016. An engagement gets you builders who run their own production systems — not a strategy deck.
Our engineers work inside your team — your standups, your repo, your roadmap — and own the outcome. No account managers in between, no offshore handoff.
2M+ users, 20M+ conversations, and a 1.59B-message corpus across the products we've shipped. We run AI in production, not just demo it.
Everything we build for you is yours, deployed under your brand. We sign your NDA and MSA and keep engagements confidential by default.
We're model- and vendor-agnostic. When a better model ships — a new Claude, a new GPT — you get it with a one-line change, never stranded on one provider's roadmap.
Several engagements became joint ventures. When what we build has a market beyond your walls, we'll commercialize it with you — not just hand it over.
An outside AI engineer who comes into your business and builds a product as if they were an employee. A good one combines technical skill, product sense, and an understanding of how your business actually makes money — senior enough that they could build the same thing for themselves.
Consultants hand you a strategy and leave you to build it. We identify the highest-return uses of AI with you and then build the working software ourselves — AI that does your employees' work, integrated into the systems you already run.
Every relationship starts with a fixed-scope, two-month build that puts a working tool into your workflow — our minimum engagement, starting at $100,000. It's how we get to know each other before anything bigger. Larger product builds, full integration, and commercialization come after, scoped to the outcome.
Our minimum engagement is $100,000 for a fixed-scope, two-month build. From there, larger builds and full integration are scoped to the outcome, and production AI is typically billed on usage once it's live. You'll always have a clear number before any work starts.
At the top end, firms like Palantir and OpenAI take million-dollar contracts — which effectively limits them to government and big tech, and even their forward-deployed hires are brought on for pure technical delivery, not alignment with your business. At the other end, you can hire and manage your own AI engineers. We sit in between: senior builders who've shipped their own products, embedded with your team, focused on one high-value workflow at a time — with a stake in whether it actually gets used.
You do. Work product from an engagement belongs to you, deployed under your brand. We can sign your NDA and MSA, and we keep client relationships confidential unless you'd like to be referenced.
Messages Improved is our self-serve platform — build your own AI agents with no code. Forward-deployed engineering is the high-touch version: our team builds and ships for you. Many clients start self-serve and bring us in for the hard parts.
If you have a repetitive, high-volume workflow you think AI should be doing, tell us about it. We'll tell you honestly whether it's a good fit and how we'd approach it.
Engagements delivered worldwide · 50+ languages