Pilots that never launch
Another impressive demo, another phase two that never arrives. Months of meetings, and nothing running in your business.
What it costs you: months spent, nothing live
We deploy AI systems
that actually run.
Most enterprise AI never reaches production.
We find the use case that pays for itself, build the system, deploy it inside your environment, and own the outcome.
- Working system in 2-3 weeks
- Fixed scope, fixed price
- One measured outcome
- unstructured inA support ticket
- read-only analysisRoot cause
- actionable outCause, proof, fix
2 min
from ticket to root cause
10,000+
scheduled checks running every day
10
data feeds joined into one picture
40x
faster than manual triage
Three ways an AI
deployment dies.
Almost never because the technology was not ready. Almost always because the engagement was designed to produce decks instead of deployments.
Advice with no builders
Strategy from people who have never shipped a system. You pay for opinions, then still have to find someone to build the thing.
What it costs you: you still have to build it
Big-firm timelines
Six-figure discovery phases and quarterly roadmaps. By the time anything works, the problem has already changed shape.
What it costs you: six figures before line one
Things we have
already deployed.
Not AI that suggests the work, AI that does it. These three are running today. Your first engagement starts in one of them, and we will tell you which on the first call.
Running
Support troubleshooting agents
An agent reads an unstructured support ticket, decides what to look at, queries your live data read-only, and hands back the cause, the evidence, and the fix in plain English.
- Reads the ticket and plans its own queries
- Read-only against production, with no write path
- Written for the engineer who has to relay it
Deployed to an enterprise support organization
Running
Monitoring and maintenance agents
Always-on agents that watch your feeds, tables, and jobs on a schedule. Security sweeps, maintenance windows, and routine checks run whether or not anyone remembers to run them.
- Deterministic scheduled checks, so an outage cannot be invented
- Alerts on state changes only, after repeated failures
- Unreachable reports as unknown, never as broken
- The agent drafts the action, a person approves it
Shipped as a production agent console
Running
Decision intelligence platforms
We pull your separate data streams into one place, then let your team interrogate them in plain language. Ask a question, get an answer and the query that produced it, across datasets that were never built to talk to each other.
- Many feeds combined into one live, queryable picture
- Ask in plain language, get the answer and its source
- Cross-dataset analysis nobody could assemble by hand
- Predictive and prescriptive, not just historical reporting
- Dashboards and scheduled briefings that send themselves
Live for a consulting practice across 7 organizations
Deployment is a discipline,
not a demo.
An autonomous system pointed at production has to be trustworthy before it is clever. Every system we deploy follows the same six rules, and your security team can audit all of them.
Read-only by default
Agents read, analyse and draft. Nothing writes to your systems unless you ask for it, and then only through a separate path with its own credentials and its own audit trail.
A person approves the action
The agent authors, a human commits. Anything that would change data or configuration is saved paused until someone reviews it and presses play.
Detection is deterministic
Whether something is broken is decided by scheduled queries against your own data, never by a language model. An outage cannot be invented.
Unknown is not broken
A system we cannot reach reports as unknown. A dropped connection never becomes a false alarm, and repeated failures are required before anything fires.
Alerts fire on change
One alert when the state changes, not the same problem re-sent every cycle. Your team never learns to ignore it.
Every figure is traceable
Each number comes back with the query that produced it, so your team can reproduce the finding without us in the room.
Watch one work.
Then decide.
A short look at a deployed agent doing the actual job: it takes a request written in plain language, works out what to query, reads live data, and comes back with the cause, the evidence behind it, and the fix. No slides, no staged screenshots, just the software running.
Deployed
An autonomous troubleshooting agent, recorded on sample data.
2-3 weeksto a working system on your own data
Read-onlyby default, with every query auditable
100%source and documentation handed to your team
What you get.
And what you are missing.
Most AI engagements end with a recommendation. Ours end with software running in your business. Here is the difference, line by line.
The typical engagement
What you are missing
- A demo that never shipsIt impresses the room, then waits on a phase two that never gets funded.
- Strategy from non-buildersRecommendations written by people who will not be there to implement them.
- An open-ended retainerAn hourly meter with no agreed finish line and no defined deliverable.
- A black box you rentThe vendor holds the source, so every change is another statement of work.
- Directional metricsNumbers you cannot reproduce, from a model that will confidently guess.
- Six months of discoveryWorkshops and interviews before a single line of working code exists.
Deploy AI
What you get
- A system live in productionRunning inside your environment, wired into your tools, by week six.
- The engineers who build itThe people who scope it are the people who ship it and hand it over.
- Fixed scope, fixed priceAgreed before any work starts. No hourly meter, no surprise invoice.
- Full source, yoursCode, documentation, and training. You can run it and change it without us.
- Figures you can reproduceEvery number traces back to a query against your own data.
- A working build in week threeSomething your team can click and judge before you commit further.
One measured outcome per engagement, agreed up front. If the pilot does not hit it, you do not continue.
From first call to live system
in six weeks.
Four fixed stages. You know the price, the deliverable, and the measure before anything starts.
1Week 1
Diagnose
We find the one workflow where an autonomous system pays for itself fastest, and define exactly how we will measure it.
You get: a scoped plan and a price
2Weeks 2-3
Build
A working system on your real data, small enough to prove itself quickly and big enough to be worth proving.
You get: software you can click
3Weeks 4-6
Deploy
Hardened and integrated inside your environment, with read-only defaults, approval gates, and an audit trail your security team can read.
You get: a system running in production
4Handover
Own it
Full source, documentation, and training for your team, plus support until you are confident running it without us.
You get: everything, with no lock-in
Stage one
Describe
It tells you what happened, with the query it used to find out.
Stage two
Explain
It works out why, and writes the cause in language anyone can relay.
Stage three
Predict
It flags the failure before the morning it would have broken.
Stage four
Prescribe
It drafts the fix and waits for a person to approve it.
Shakeem Grohmann
Founder, Deploy AI
Builds and ships autonomous AI systems for enterprise operations teams, including production troubleshooting agents and always-on monitoring agents.
Productionnot prototypes
Weeksnot quarters
Onemeasured outcome
Built by people who ship,
not people who present.
Our systems already run in enterprise environments: an agent that troubleshoots live support tickets against production data, always-on agents that detect breakage and diagnose it before anyone opens a ticket, and an intelligence platform a consulting practice uses to run its accounts. All of them read-only by default, all of them auditable, all of them handed over.
One measured outcome per engagement. Fixed scope. If the pilot does not prove itself, you do not continue. That is the whole pitch.
Ask us anythingFair questions.
A working system on your real data in 2 to 3 weeks. Not a mockup, and not a video. Software your team can click, test, and judge for themselves.
Pilots are fixed scope and fixed price, agreed before any work starts. No hourly meter, no surprise invoices. Tell us the problem on a free consult and we will tell you exactly what the pilot costs.
No, not by default. Agents read, analyse, and draft. Anything that changes your data or your configuration is saved in a paused state for a person to review and approve. The agent authors, a human commits. Where write access is genuinely required, it runs through a separate path with its own credentials and its own audit trail.
Because detection is not the model's job. Checks are deterministic queries on a schedule, so the decision that something is wrong comes from your data, not from a language model. The model is only used to write the explanation once the state has already changed. On top of that: a system we cannot reach is reported as unknown rather than broken, alerts require repeated failures before they fire, and we only alert on transitions instead of re-sending the same problem every cycle.
Yes. An agent that cannot see your data cannot do anything useful. We work inside your security rules: scoped read-only credentials, an audit trail of every query, and nothing leaves your environment without your sign-off. Your security team gets full visibility into what runs and what it touched.
No. It removes the repetitive volume so your people handle the exceptions, the judgment calls, and the customers. Every system we ship keeps a person in the loop at the point where a decision actually matters.
Then you do not continue. The pilot is scoped around one measured outcome, and if it does not hit that outcome we stop. You will have spent a fixed amount to learn something real, instead of funding a six-month maybe.
You do. Full source, documentation, and training for your team. No hostage licences, and no black box you cannot run without us.
Your competitors are piloting.
You could be deploying.
One free 30 minute call. Bring the problem, and we will tell you whether an autonomous system can solve it, what it would cost, and how we would measure it.
Fixed scope pilots. One measured outcome, or you do not continue.