Every team carries work that has to be done, has to be done right, and doesn't need a person to do it. We build AI agents that take that work off your team's plate and run it start to finish. More output, the same payroll, and your people back on the work that actually needs them.
Three steps, and only the first one asks anything of you.
You don't need a plan or a polished brief to start. The process you already run, however messy it looks written down, is enough for us to work from.
We turn that process into an AI agent. Senior engineers build it around your exact way of working, then we run it once it's live, retraining it as the process changes.
There's no dashboard for your team to learn and nothing to babysit. The finished work lands where you need it, and that's the whole of your side of it.
The areas below are illustrative. The exact steps, triggers and outputs are designed around your firm's own process during a Discovery session.
This could look like an agent that takes a document in and a clean, structured result out.
Reading incoming paperwork. Pulling the fields that matter. Flagging what doesn't add up. Sorting by type, by priority and by exception. Forms, statements, applications, contracts and invoices, anything that arrives as a file and currently needs a person to work through it by hand.
A checked, structured record your team can act on without reading the whole document first.
We might build this as an agent that runs the same checks, the same way, every single time.
Validating against a defined set of rules. Comparing one source against another. Catching the cases that fail, passing the ones that don't. The decisions that aren't hard, exactly, but are easy to get wrong on the fortieth one in a row.
A consistent decision, with the reasoning recorded, ready for someone to sign off.
An agent here could take a routine request through to a routine reply.
Acknowledging, chasing, updating and confirming. The standard messages that have to go out, on time, in the right form. Status updates, reminders and handovers, the small communications that keep a process moving and quietly stall it the moment nobody gets to them.
The right message, sent at the right point, every time the process reaches it.
Or an agent that handles the whole sequence, not just one task inside it.
Several of the above, chained together. A document arrives, gets checked, gets logged, triggers the next action and sends the confirmation. The full run from trigger to finished output, with a person stepping in only where real judgement is needed.
A completed process, start to finish, with your team handling the exceptions and nothing else.
You don't commission an automation agent once and call it done. Software starts drifting the moment the process around it changes, and a process always changes. So for us the build is the start of the job, not the finish.
Most providers build and walk away. We run every agent we build, for as long as it's live: watching its output, retraining it as your process shifts, and holding quality to the standard you signed off. That's why this is a managed AI agent service, not a tool you're left to look after.
Designing and building an agent gets it live. Running it is what keeps it right.
You're not paying us for a build project, or for licences and seats. You pay for output, and only for output.
There's a refundable commitment per agent to get started. It's a prepayment that goes towards the work, returned in full if we don't deliver the agent to the spec we agreed. After that, you're billed per output: the agent produces a finished piece of work, and that's the thing you pay for.
And if an output doesn't meet the standard we agreed, you're not billed for it. Failed outputs are on us, not you.
An illustrative example: a back-office team handling a few hundred standard applications a week. Here is that process before an agent, and after one.
Applications arrive by email or web form. Someone opens and reads each one, checks it for missing information, matches it against existing records, and decides whether to pass it on or send it back. A significant amount of people hours are spent, and accuracy slips as the queue grows.
A new application arriving is the trigger. The agent reads the application, checks the fields, matches records, then sorts and decides. Handled start to finish, to the same standard every time.
A complete application is routed straight through to processing. An incomplete one is returned with exactly what is missing, and the applicant notified. Your team focuses only on the exceptions and higher-value work.
The fortieth check of the day is run exactly like the first.
People handle the exceptions and the judgement calls, not the routine run.
A busy week and a quiet week look the same to an agent.
Work doesn't pile up when someone is on leave.
This is an illustrative example. The processes we automate, and the way an agent handles them, are designed around your firm's own work during a Discovery session.
Plenty of automation tools follow a fixed script, and break the moment something isn't quite where they expected it. An AI agent reads, interprets and copes with variation instead of falling over at it. The bigger difference is that you don't operate ours. With most tools, your team still owns the work and the upkeep. With us, the agent's run for you, and the output is the only thing that reaches your desk.
Work with volume, and work where the main risk to quality is a person doing the same thing for the tenth time before lunch. If a process has clear rules and happens often, it's usually a candidate. Reading documents, running checks, routine communication and processes with defined steps. Work that needs real judgement, or sits on a live client relationship, is work to keep. Part of a Discovery session is being honest with you about which is which.
Yes. An agent isn't much use sitting in a silo, so connecting it to the systems you already run, your CRM, case management or document platform, is part of what we scope and build. That connection work is our AI integration services, handled inside the same managed service.
No, and that's the point of a managed service. We design the agent, build it, and run it. There's nothing for your team to install, maintain or learn.
Senior engineers, not juniors learning on your project. We build and run AI agents for governance-led businesses, and we're a Synextra company, with many years of cloud and infrastructure work behind us. The agent is developed around your specific process rather than configured from a template, and the team that builds it is the team that runs it once it's live.
Processes change, and an agent that isn't kept current quietly drifts out of date. Keeping it current is part of what you pay for. As your process moves, we retrain and adjust the agent so its output keeps matching what you actually need now, not what you needed at launch.
We test and evaluate the agent before it goes live, and we keep evaluating it while it runs. Output is held to the standard we agree with you at the start. If an output doesn't meet that standard, it isn't billed. Most AI fails when it's tested seriously, so we do that testing first, before any of it reaches your team.
We design it. We build it. We run it.
You only pay when it delivers.