We help companies put large models
to work in their own business.
Start with an internal AI gateway that brings company-wide AI usage under control: every token traced to an employee and a task. On top of it, we deploy models on your servers, connect them to your systems, and help a business line do more with fewer people and fewer errors.
Your people already use AI, but you can't see who, for what, at what cost, or whether sensitive data went out. We put an AI gateway inside your company, and every call is recorded against a specific employee, department and model. Set limits and permissions per person and team, redact sensitive data before it leaves, and audit or reconcile every record.
Who it's for
Companies whose people already use AI tools, without control over usage, cost or data.
What we deliver
An internal AI gateway, unified accounts and permissions, metering and department billing, redaction, audit logs.
What you get
Company-wide AI usage on one screen: who used it, for what, all on record.
On top of that foundation,
here's what else we build.
The gateway connects your people, data and models. From there, we can deploy models in your own data centre, connect them to the systems you run, and help a business line do more with fewer people and fewer errors.
AI infrastructure · On-premise deployment
Large models,
on your own servers.
Data that can't go to a public cloud can still use large models. Our engineers work inside your data centre and handle servers, model deployment and operations entirely inside your network. Sites back each other up, and release, rollback and alerting plug into the operations you already run.
Who it's for
Companies whose data can't leave the network, or that face strict compliance.
What we deliver
Compute and server planning, on-premise models, gateway and permissions, monitoring and operations.
What you get
A large-model service running inside your network, ready for staff to use.
AI applications · Business-line automation
One person,
the output of ten.
Not replacing people, but letting one person do the work of ten. We take one business line, such as sales follow-up, support tickets or finance reconciliation, and hand the repetitive entry, checking and chasing to agents, leaving people to judge and approve. Throughput goes up, error-prone manual steps go away, and results get more accurate. In sales, one sentence from a rep updates the stage and the follow-up.
Who it's for
Companies with a business line that is short-handed, repetitive and error-prone: sales, support, operations or finance.
What we deliver
We map that line's process, build agents into your existing systems, and keep human approval at key steps.
What you get
More volume with the same team, fewer errors, every step on record. Lower cost, higher output.
Integration · Connecting systems
Large models,
connected to the systems you run.
ERP, CRM, OA and store back-ends, with data scattered across them and reconciled by hand. We map the process on site, connect your existing systems without replacing any of them, and let the model handle orders, stock and reconciliation in between, passing mismatches to a person.
Who it's for
Companies running several systems, with data scattered and checked by hand.
What we deliver
API integration, a data hub, automated workflows, human fallback for exceptions.
What you get
One business flow that runs end to end, with your existing systems unchanged.
WHAT FDE MEANS
Same project. A different starting point.
Traditional outsourcing
How we work
Starting point
Build a new system from zero
Start from the systems, data and processes you already have
What you get
A piece of software
A business flow that runs end to end
How we work
Specs passed hand to hand
Engineers on site, working directly with the people doing the work
AI
A chat box bolted on
Built into the flow, reading and writing data within permissions
After launch
Sign-off and done
Keep iterating on real usage, and run it with you
HOW AN ENGAGEMENT RUNS
Make one flow work. Then scale.
Embed
Engineers join the team to map existing systems, where the data lives and where the flow gets stuck.
First loop
Pick the most painful flow and connect it from screen to data, so the front line uses it first.
Expand
Add more flows, models and data sources on the same foundation, never starting over.
Operate
Iterate on real usage; we share responsibility for running the servers and models.
Have a project in mind?
Tell us which systems you run today and where things get stuck, and we'll work out which layer to start with.
