One
Credentials
A personal agent acts as the person running it, with keys sitting in the same place the model reads and writes. Nobody in the business can audit, rotate or revoke them.
About Lifter Studios
We didn’t set out to build an AI product.
The hard parts of running an agent workforce aren’t AI problems. Holding credentials safely, giving a business one shared memory instead of ten private ones, routing a risky action to a person, running work while nobody is watching. Serious software solved all four a long time ago. Nobody had applied them to agents, and that’s the gap Lifter was built into.
RefThe four walls every personal AI tool hitsSolved
01Credentials keys sitting where the model can read themYes
02Context ten people teaching ten agents the same factsYes
03Approvals a chat message that vanishes with the sessionYes
04Always on work nothing happens unless someone is watchingYes
Isolation · capability based access · shared storage · an audit trail · the four problems above are the four problems operating systems were invented to solve · not analogous to them, the same ones ·
01 · The insight
Every business wanted its AI to work like staff.None of the tools were built like that.
The models were never the hard part. Every frontier model can already draft the email, triage the ticket and write the report, and they all improve every few months. What nobody had solved was where that work runs, who it answers to, and what happens to what it learns.
Two
Context
Ten people teach ten agents the same facts. Nobody can inspect any of it, and it all leaves when someone resigns.
Three
Approvals
An approval becomes a chat message to whoever is in the session. It isn’t addressed to the person accountable and it leaves no record.
Four
Always on work
The report should land at 7am and the tickets should be triaged as they arrive. A personal agent only works while its person is watching it.
02 · What we worked out
Those are the four problems operating systems were invented to solve
Not problems that resemble the ones an operating system solves. The same problems, and they were solved the same way, decades ago, for programs sharing a machine. An agent workforce sharing a business needs exactly the same four things, for exactly the same reasons.
Isolation
Every agent runs as its own process with its own identity and memory, not inside a chat window. That’s what lets it keep working when nobody is talking to it.
Capability based access
Agents work through typed tools, never raw keys. Credentials live in our store and are checked against your policy before any call is made.
Shared storage
What an agent knows lives in plain files the whole team can read and edit, not in one person's history.
An audit trail
Every tool call records who asked, which agent ran, against which credential, what the policy decided and what happened.
An agentic operating system is a description, not a slogan.
We aren’t the first to think of these primitives. We’re among the first to build them for a company's AI workforce rather than for its files and its processes. We expect every serious platform in this category to converge on the same shape, because the requirements haven’t changed.
03 · What we’re building
One system every employee can use, and the business can still govern.
The objective hasn’t moved since the first line of code. An always on, always learning agentic operating system that lets a business put AI in front of everyone who works there, with the security and the guardrails already in place, so the people using it can simply get on and operate.
Almost everything else in this market is built for an individual and then stretched to fit a company. We started at the company and worked back.
Objective
Everyone, not a licensed few
AI that reaches the whole business rather than the handful of people who happened to get a seat. That’s why people are free on every tier and always will be.
Objective
Governed by default
Permissions, approvals and an audit trail in the architecture rather than in a policy document sitting beside it. Safe to hand to the whole organisation on day one.
Objective
Always learning
A workforce that knows more about your business this quarter than last. Memory held by the organisation, not trapped in one person’s history.
Objective
Owned by you
The agents, skills, memory, connections, automations and applications you develop are yours, under your brand, on your domain and independent of any one model. We’re the engine, not the landlord.
We would rather tell you where we are than imply a maturity we haven’t reached.
The platform is in production today, running real work inside real businesses. We’re taking five foundational clients before general availability, and what they run decides when that happens.
What those five run is what shapes the product, sets the published pricing and decides what general availability actually looks like. How that works.
04 · The team
A specialist AI engineering and product team.
Lifter is built by people who do this and nothing else. Not a general software team who added AI to a roadmap, and not a consultancy assembling somebody else’s tools. The platform, the runtime and the controls are ours, which is why we can answer for how they behave.
Deliberately close to the work. Everyone here’s near enough to what’s actually running to know what’s happening inside it, which is what makes a five client foundational group a real commitment rather than a line in a deck.
Engineering
Builds and runs the platform
The runtime, the permission and approval layer, the credential gateway, the connectors, and the isolated environment behind every workforce.
Product
Decides what gets built next
Shaped by what live deployments actually surface, rather than by a roadmap written a year ago and defended ever since.
Delivery
Gets it live and keeps it working
Scopes the roles, runs onboarding, and stays in the channel while a workforce is being trained on your business.
Led by
Co-founder · engineering
Roman Yakobnyuk
Leads the engineering team
Roman has built production systems at enterprise scale and holds a master’s degree in artificial intelligence, so the thinking behind this platform isn’t borrowed from a framework. The controls aren’t features added once a customer asked for them. They’re how he and the Lifter engineering team build, which is why they sit in the architecture rather than on top of it.
Co-founder · operations
David Dennings
Leads operations and client success
David has worked across many areas of a business and built high performing teams inside them, so he knows what it takes to operate efficiently and to empower great people to deliver their best. It’s why the product is built to make a strong team more productive than it has ever been, on accuracy and efficiency, and above all on support for the people doing the work to deliver success.
05 · Where we started, and why it travels
We proved it in the hardest place we could find.
Retail is high volume, thin margin, real time and unforgiving. Nothing is theoretical, the work happens every day whether anyone is ready or not, and a mistake shows up in the numbers by the afternoon. It’s a difficult place to make something like this hold up, which is exactly why we started there.
The platform itself isn’t a retail product. What’s retail specific is the connector set and the pre-built roles. The control plane, the memory, the permissions and the scheduling are the same wherever they’re pointed.
Horizontal
The platform
Agents, skills, memory, permissions, approvals, audit and scheduling. None of it’s industry specific and none of it changes when the industry does.
Vertical
The connectors and the roles
Hand tuned packages for the systems a sector actually runs on, plus the roles that recur in it. This is the part we build per market, and it’s configuration rather than a rebuild.
Live and next
Commerce first, then services
Retail and commerce are running now. Professional services is next, and the same pattern applies to anywhere with a daily operational rhythm and a lean team carrying it.
06 · What we stand for
Three things we won’t compromise on
These aren’t values on a wall. Each one costs us something, which is how you know we mean them.
01
Faster, and right
Speed only counts if the work holds up. We build for output your team can act on without checking it twice, because a workforce that has to be re-checked by hand has not made anyone faster at all.
02
Depth over breadth
We go vertical first. We know retail deeply, the systems, the workflows, the pressure points and what good looks like. We expand only when we’ve earned the right to.
03
Deliberate by design
We onboard deliberately rather than quickly. We hold the cohort small on purpose, so every deployment is set up to succeed. That care compounds into the product.
07 · How we work
Product led.Operator informed.Built to last.
Lifter is the business. Our professional services exist to make deployments succeed, not to generate billable hours.
Product first
Always
Every hour a customer spends with our team is an hour invested in getting the product to work harder for them.
Onboarding
With care
Every engagement includes a proper onboarding. We would rather charge for the month that decides whether it works than hand over a login and hope.
Value
That compounds
Every session, workflow and integration adds to a persistent memory of your business. The value doesn’t reset. It builds.
Yours
Under your brand
Lifter deploys under your identity. Everything you build inside it is your IP and exportable at any time.
Agents ready
10+
Pre-built and ready to deploy, with bespoke ones scoped and built as you need them.
Connectors live
100+
Across hand tuned retail packages and the wider ecosystem, growing every week.
Live today
02
Retail businesses running Lifter as a proof of concept right now, on their own systems and their own data.
Get started
Ready to see it in action?
Book a demo and tell us about your business. Someone from our team will be in touch within one business day.