AI systems that ship.
We build AI that does real work in your business every day – sorting the inbox, answering the phones, chasing invoices, reconciling the numbers – and we keep it running. Not a demo. The actual job, done.
30-second start
What should you automate first?
Two quick questions. We will point you straight at the automations worth a look, and the one we would pilot first.
How big is your business?
01What we build
Six ways we put AI to work in your operations
From sorting your inbox to answering your phones – real systems that run every day, and that you own outright when we are done.
02Why TelarLabs
Most AI projects die as demos. Ours run daily.
The difference is not the models – it's whether the system survives contact with real operations.
Built by operators
Our background is IT operations, project delivery, and systems engineering – not demos. We automate work we used to run by hand, so we build for the people who live with the system.
You own the stack
Your infrastructure, your data, your models. Where it fits, we deploy local models with zero per-token cost. We build and hand over – no lock-in, no black-box SaaS.
Production is the only milestone
No slideware, no eternal pilots. Systems ship with evals, monitoring, retries, escalation paths, and documentation – the unglamorous parts that make AI dependable.
Infrastructure we work with daily
03In production
What a morning looks like for our agents
Triage, reconciliation, reporting, monitoring – running on schedule with humans on exceptions only.
Illustrative log – patterns from our production systems, no client data.
04Case studies
Real systems. In production.
Enterprise finance automation: 2–3 hours of CFO time freed daily
An AI system that automates vendor correspondence, invoice reconciliation, document classification, and ERP sync across multiple major vendors – freeing 2–3 hours of CFO time every working day.
PulseSales: a real-time voice agent for outbound sales
A real-time voice agent for outbound SDR, appointment confirmation, and multilingual outreach. A 13-state workflow engine keeps every conversation on a controlled path; a live dashboard shows every call, transcript, and result.
Does it pay off?
Size a pilot with your own numbers
Put in what a repetitive task actually costs you. This is a rough model on your inputs, not a quote. We confirm the real payoff in a pilot.
Rough payback
Assumptions: 3.6 h/week saved (your inputs) at £28/h over 4.33 weeks, less running cost. Your numbers, a rough model, not a quote.
Pressure-test this with us05Start here
Tell us what you're trying to automate
Not sure which service fits? Describe the bottleneck, the pilot that stalled – or the automation your last developer left behind – and we'll map the right system and scope it honestly.