Not a pilot. Not a proof of concept. We build AI systems that run your marketing, your operations, your support and your hiring — live in weeks, and judged only on what they produce.
Five practices, one team. We take the whole problem — the strategy, the build, the deployment and the number it has to hit — not a slice of it.
Agents that finish work, not chatbots that answer questions. They act, check their own output, and hand to a person when they should.
Customer-facing agents Multi-step workflows Back-office orchestration Document processing Systems integration Human-in-the-loop reviewYour own model, running on your own servers, trained on your own data. Nothing you own leaves your building, and we test it every week to catch the day it starts slipping.
Custom LLM deployment Private & self-hosted models RAG & knowledge systems Fine-tuning & distillation Evaluation harnesses Guardrails & claim gatesThe unglamorous half most AI firms never finish. Real applications, real load, real deployment — built to be handed over and run without us.
Web applications Mobile applications SaaS products APIs & integrations Cloud infrastructure Data platformsCameras that understand what they are looking at. Inspection, counting, tracking and document reading — on the line, or at the edge.
Quality inspection Detection & tracking OCR & document AI Video understanding Edge & on-premise Custom model trainingThe systems we built for our own growth first, now installed for clients. Because they already exist and already work, they go live in weeks.
Performance marketing Conversion & landing pages Content production SEO, GEO & AEO Lead capture & nurture Creative at volumeStill run by the same single marketer.
One designer was the bottleneck. Now there isn't one.
In the guest's own language, at any hour.
110 checks against live visitor data, then rebuilt.
We agree what success means before we quote. If we can't find a number worth moving, we'll say so and you keep the budget.
A growing brand had exactly one marketing person and no writers. Competitors published daily. Hiring a content team meant six months of recruiting and a salary bill they could not justify.
An engine that picks the topic from real search demand, writes the piece, sources every statistic, draws its own charts, and publishes straight into the CMS. A person approves. Nobody types.
Each piece is written for Google and for the AI engines that now answer questions directly, then scored out of 100 before it is allowed out. Anything below the bar gets rewritten, not published.
From two posts a month to over five hundred assets a month, run by the same single marketer. Organic traffic quadrupled inside six months, and the brand now gets quoted in AI answers.
We find the process costing you most, and agree the number it has to move.
Baseline before build. What the work currently costs, produces and loses.
Two-week increments. Output you can actually use from the first one.
Into live operations, with monitoring, runbooks and your team trained on it.
Baseline against live, on the number from stage one. Written up either way.
Tuning, model upgrades, next use case. It should get cheaper every quarter.
We agree what the system has to move before we quote. No number worth moving, no project.
Live and working in weeks. A demo proves something can happen once, not every day.
Every system ships with the tests that check it, so you can audit our work without us.
Source, models and data stay yours, in your accounts, from the first commit onwards.
Approval gates, rollback and claim checks are built in from day one, not bolted on later.
If AI isn't the answer, we'll tell you what is — even when that costs us the project.
We didn't add AI to an existing agency. We started here. That difference shows up in what gets shipped — most firms selling AI today are running an old delivery model under a new label, which is why so much of the spend ends in a pilot nobody uses.
We work the other way round. Every system we build starts from a real process that costs real money, and it isn't finished until it's running in production against a number we agreed at the start.
Take a system we have already built and proven. We fit it to your business and hand it to you running.
Your process, your system, built from scratch. Your team is trained to run it before we leave.
Our engineers work inside your team, on your roadmap, in your tools, for as long as you need them.
You are building AI in-house and want someone senior to check the plan before you commit to it.
We build for ourselves too. Both of these sit in markets where the most important work is still done by hand.
Deal flow, rate cards, deliverables and payouts still run on spreadsheets and DMs — inside a market moving billions a year.
Nexus is the system that should have been underneath it all along, built for the people making the work rather than the brands buying it.
Hiring is the largest process in most companies and the least measured. Pipelines leak quietly and shortlists come down to one tired opinion.
Caliber takes the mechanical half of hiring so that human judgement lands where it actually changes the decision.
Nobody comes to us with a brief. They come with a problem that is already costing them. This is where they landed.
“We publish more in a month than we used to manage in a year, and it reads better than what our agency was charging us for. I still run it on my own.”
“A guest asks something at 3am and gets a real answer in seconds. My night team stopped drowning, and our review scores went up because of it.”
“We used to fight over which six ads to make. Now we ship hundreds a month, all on brand, and the cheapest lead we have ever had came out of it.”
“Same traffic, same ad spend, more than double the leads. It paid for itself inside the first quarter and we have not touched the budget since.”
AI agents, workflow automation, vision applications, custom LLM deployments, software products, and marketing and content systems. If a process in your business runs repeatedly, there is usually something here worth building.
Framing takes about a week and we can begin within two. If you're installing a system we've already built rather than commissioning a new one, first output usually lands inside a month.
Whichever one we agree at the start, and we won't begin without it. Cost per lead, conversion rate, hours returned, cycle time, cost per unit of output. No number worth moving is a reason not to build.
Fixed for system installs, milestone-based for custom builds, monthly for embedded pods and advisory. No hourly billing — it pays us to be slow, and that's the wrong incentive.
Yes. Source, models, prompts, evaluation sets and outputs are yours, in your repositories and your cloud accounts, from the first commit. Nothing is held back for renewal leverage.
Then we say so. A good share of what arrives as an AI problem turns out to be a data problem, a process problem, or something that doesn't need solving. Better to hear that in week one than month six.
Read-only by default on anything connected to your live systems. Changes need approval, a visible before-and-after, and a rollback path. Credentials live in your secret manager. Self-hosted where the data requires it.
We prove it against the baseline, hand it over with runbooks and training, then either step back or stay on to tune it. Most systems get noticeably cheaper and better in the two quarters after launch.
Tell us what's costing you the most. You'll hear back from an engineer, not a sales team — and if we're not the right fit, we'll say so in that reply.
