Autonomous systems you can actually trust
LA MANO is an AI automation consulting studio in London, working worldwide. We build autonomous agents and AI workflow automation that decide, act, and run unattended, each one held by hard limits it cannot cross. The proof is not a slide deck. It is software we run in live markets, on real money, every day.
What AI automation consulting means here
AI automation consulting is the work of replacing repetitive human effort with software that decides and acts on its own. We find the part of your operation that runs on copy, paste, and judgement at odd hours, and we hand it to an agent. Less advice, more machinery. We automate the boring and the impossible, and we tune the result until it earns its place.
An autonomous agent is the unit of that work. It is not a chatbot waiting to be asked. It observes a situation, chooses a move, takes it, checks its own work, and stops at a limit. Agentic automation strings these together into pipelines that run at 4am, AI agents for business that handle the cases a fixed script would choke on.
The reason to trust any of it sits in our own stack. We operate an autonomous quantitative trading system in live markets, where a wrong move costs real money. That is the bar. If our automation can be left alone with capital, the same discipline can be left alone with your operations. Trust here is a measurement, not a feeling. It is earned, never assumed.
What we automate
- Autonomous agent systems Agents that decide and act, with hard limits they cannot cross. Built to hold a goal, take steps, and check their own work before anyone reviews it.
- Workflow & ops automation The 4am work, handled before anyone wakes up. Ingestion, reconciliation, reporting, the slow manual pipeline replaced by one that runs itself.
- Quantitative tooling Signals, engines, and dashboards that turn data into moves. The same class of tooling we run against live markets, built for your edge.
- Guardrails, evals & hard limits Kill switches, spend ceilings, allowed actions, and evals that watch the agent. Autonomy is a privilege the system grants once the numbers agree.
How we work
- Map the bottleneck We find the work that drains hours or runs at odd hours, and we measure it. You cannot automate what you have not first understood.
- Build the agent or pipeline Custom, against your stack and your edge cases. AI in the core loop where it counts, plumbing where it does not.
- Set hard limits it cannot cross Caps, ceilings, kill switches, allowed actions, written into the system rather than asked of the model. Judgement never becomes a liability.
- Measure trust until it earns autonomy Shadow, then short leash, then alone. The agent runs unattended only after the numbers say it can be trusted.
Trust is a measurement
The proof is BURRY, our private autonomous quantitative trading system. It runs a momentum engine under a regime overlay, with hard risk limits it cannot breach, deployed in live markets on real capital. No human watches it through the night. It decides and acts, and it stops when a limit says stop.
That is the difference between automation you demo and automation you trust. We do not ask you to believe the agents work. We point at one that has been left alone with money and is still standing. Your operations are a gentler problem than that.
Automation we run ourselves
Looking for something adjacent? We also run AI Product & MVP Engineering for builds from idea to deployed software, and Music Catalog M&A for brokerage and advisory in the mid market. As an AI automation agency in London, working worldwide, the same hand does all three.
Questions, answered
What is AI automation consulting?
AI automation consulting is the work of finding the part of your operation that runs on repetitive human effort and replacing it with software that decides and acts on its own. We map the bottleneck, build the agent or pipeline, and tune it until it runs unattended. At LA MANO the test is live markets: we operate the same kind of automation on our own money before we ask you to trust it on yours.
What are autonomous agents?
An autonomous agent is software that observes a situation, decides what to do, and acts without a human pressing the button. It is not a chatbot that waits to be asked. A real agent holds a goal, takes steps toward it, checks its own work, and stops when it hits a limit. The hard part is not making one act. It is making one you can leave alone.
How do you keep AI agents safe and under control?
We give every agent hard limits it cannot cross, written into the system rather than asked of the model. Position caps, spend ceilings, kill switches, allowed actions, regime overlays. The agent earns autonomy in stages: it runs in shadow, then with a short leash, then alone, and only after the numbers say it can be trusted. Trust here is a measurement, not a feeling.
How is this different from RPA or no-code automation?
RPA and no-code tools follow a fixed script. They break the moment reality drifts from the recorded path. Our agents reason about the situation in front of them and choose, which means they handle the messy cases a script cannot. We build custom systems against your stack and your edge cases, not a template, and we wrap them in evals and hard limits so judgement never becomes a liability.
Do you build custom AI agents for our stack?
Yes. Everything is built against your data, your tools, and your constraints. We work in your codebase and your APIs, wire agents into the systems you already run, and leave you with software you own rather than a dependency on us. If a workflow can be measured, it can usually be automated.
What does an engagement look like?
We take a few engagements at a time, by referral or pitch. It starts with the bottleneck: show us the work that drains hours or runs at 4am. We scope it, build the agent or pipeline, set the limits, and measure trust until it earns the right to run on its own. Send the form at lamano.one and we respond in under 24 hours.
Show us the bottleneck.
The work that drains hours, or runs at 4am, or breaks every fixed script you have thrown at it. We build the agent, set the limits, and measure trust until it earns autonomy.