AI integration studio/telecom-grade since 2015
C0nfig takes AI out of the deck and into your stack. Roadmap consultancy, the integration and automation work itself, and a standing watch on everything the field ships — one team, accountable from the first workshop to the signed acceptance report.
01The gap
The distance between a convincing prototype and a system your business depends on is not a model problem. It is permissions, data contracts, retries, evals, ownership and cost — the unglamorous work nobody demos.
C0nfig was built for exactly that. We start at zero — often against a vague brief and a frustrating spreadsheet — and we end at a signed integration acceptance: criteria written before we began, met in your environment, handed over with documentation your own engineers can defend.
Long before models, we were integrators. Since 2015 we have architected, optimised and cut the cost of telecom-grade services — for existing systems and for new applications — where a bad deploy costs real traffic and real revenue, not just a red CI badge. AI is simply the newest workload to get that treatment.
And because the stack genuinely can change every month, the plan does too. We re-baseline scope, model choice and cost at every monthly checkpoint.
02Services
Take one, take the chain, or take the whole arc. Engagements are modular by design because the right starting point moves as fast as the technology does.
We map the opportunity space against the data you actually have, then say what is worth building — and what to leave alone for another six months.
The models get wired into the places the work already happens: ERP, CRM, warehouse, ticketing, and the internal tools nobody wants to touch.
Workflows that stop asking a human to copy-paste between two systems. Built to fail loudly, retry sanely, and escalate when confidence drops.
Nothing here is fixed except the acceptance criteria. Providers move quarterly, prices fall, capabilities jump — so we re-baseline the roadmap every month and you keep the right to change scope, stack or speed at any checkpoint.
03Process
Every phase ends at a gate you can close. If the numbers don't hold, we stop — that is a feature, not a failure.
2 weeks
We audit the stack, the data and the workflows, then tell you what's worth doing. Usually three candidates, one survivor.
1–2 weeks
A 6–12 month plan with phases, costs and the exact point at which each phase can be killed. Acceptance criteria get written here, not at the end.
3–5 weeks
One workflow, end to end, under production conditions: real data, real users, real latency. If it can't survive this, it won't survive the rest.
4–12 weeks
The unglamorous middle: identity, permissions, data contracts, retries, monitoring, cost ceilings, and the boring reliability work that makes it real.
2 weeks
Acceptance run against the criteria from phase 01, signed off together. Then documentation, training and a support window — you are not held hostage to us.
04Radar
Every model release, price change, deprecation, benchmark and paper lands somewhere in a real stack. We follow all of it, test what's relevant, and bring you only the parts that change a decision.
This isn't research, and it isn't a lab. It's the reading we do before we recommend anything — which is why the monthly re-baseline is a working document and not a ritual.
The six channels on the left, held open. When one of them changes something that touches your stack, you hear about it at the next checkpoint — not a quarter late.
05The studio
No pyramid, no bench. The people in the room are the people writing the code.
We hold no reseller margin. If the smaller, cheaper model is enough, we say so.
Code in your repo, inference through your accounts, data where it already lives.
Delivered means signed off against criteria written before the first commit.
Architecting, optimising and cost-reducing services for existing and new applications — carrier-grade, where uptime is contractual and every millisecond is billed.
The same engineering discipline aimed at models, agents and automation — zero to signed acceptance, with the evals and cost ceilings to prove it.
Every release, price change and benchmark that could touch a client stack — read, tested, and folded into the next recommendation.
founder
“We are not here to sell you the largest model. We are here to make the thing work on a Tuesday, at 9am, with fourteen people using it at once.”
06Start here
A diagnostic starts with a 45-minute conversation and a look at one workflow. You leave with an honest read on whether AI helps here at all.
No form, no scheduler, no sales rep in between — it lands with the person who would actually do the work.