An AI digital employee for routine, rule-driven work
AI Digital Employee is a software colleague that takes the repetitive tasks your operations team does in the same five applications every day, does them the same way every time, writes down what it did and hands anything unusual to a person. It works inside the systems you already run, under the approval rules you set, and it never acts outside them.
See AI Digital Employee in action
The interactive demo will show routine tasks running in everyday business applications, the handover to a person when something is unusual, and the log of everything it did, with an AI guide beside it.
AI answers from our demo material can be wrong; please confirm details with our team. Questions are stored, so do not share personal or confidential information.
What AI Digital Employee is and who it is for
AI Digital Employee is an agent platform for operations and back-office teams that run high-volume, repeatable processes: order desks, finance operations, HR administration, customer service back offices and shared-services centers. Each digital employee is defined by a task, the applications it may touch, the rules it must follow and the point at which it must stop and ask. Under the hood it is agent orchestration of the kind we build in our agentic process automation work: a graph of steps, tool calls into your applications, checkpoints, and human approval gates where you want them.
It is bought as a subscription per digital employee, with the task definition, application connections and approval rules set up by us during onboarding and owned by your team afterwards. Deployment scope and the level of autonomy depend entirely on which applications are connected and which approval rules are configured; a digital employee can be set to propose every action for a person to confirm, or to act on its own within thresholds and escalate the rest.
We deploy for clients in India, UAE and Saudi Arabia from Chennai and Abu Dhabi, and for US clients from New Jersey, with the agent running where your applications and data residency rules require. It pairs naturally with our CRM & HRMS Platform for professional services firms and with the generative AI and agentic AI practice that builds custom agents.
What AI Digital Employee does, and what it refuses to do
Four properties. The last two matter more than the first two to the people who have to sign off on it.
Routine task execution
Completes defined, repetitive workflows from start to finish: reading an incoming request, looking up records, updating a system, sending the confirmation. The task is defined once, with its inputs, steps and finishing condition, and then runs every time the trigger fires.
Existing applications
Operates across the business systems you already have, through their APIs where they exist and through controlled interface automation where they do not. Nothing is migrated or replaced; the digital employee logs in with its own credentials and permissions, like a new hire.
Human handover
Escalates unusual cases to the right member of staff with the context attached: what it was asked, what it found, why it stopped. Thresholds, unfamiliar inputs and anything outside its rules trigger a handover rather than a guess.
Traceability
Maintains a record of every action it took, every record it read or changed and every decision it made, reviewable by your auditors and your process owners. If a step is questioned, the log shows what happened and why.
How AI Digital Employee is set up and run
Four steps from a task description to a running digital employee. The first one is mostly conversation with the people who do the task today.
- 01
Define a repeatable task
We sit with your team, document the task as it is really done, including the exceptions, and agree where a person must approve.
- 02
Connect approved applications
The digital employee is given its own credentials and the minimum permissions in each application it needs.
- 03
Execute the workflow
The task runs on its trigger, in shadow mode first so you can compare its proposed actions with what your team would have done.
- 04
Escalate exceptions and log actions
Live, it acts within its rules, hands exceptions to a named person and writes every action to the audit log.
Product note on scope and autonomy
Deployment scope and the level of autonomy depend on the applications connected and the approval rules configured. A digital employee is only as capable as the access you grant it and only as independent as the thresholds you set. We recommend starting in propose-only mode and widening autonomy as the audit log earns your confidence.
Explore more in AI Workforce & Business Management
A digital employee works across the systems you have. The platform below is one of those systems, built for engagement-driven firms.
Frequently asked questions
Which tasks are a good first assignment for an AI digital employee?
Tasks that are high-volume, follow written rules and touch two or more applications: moving customer requests from a mailbox into a ticketing or ERP system, reconciling records between systems, preparing routine reports, onboarding data entry. The best first task is one your team finds tedious and can describe step by step. Tasks that need judgment on every case are not a good start; those stay with people.
How do we stop it from doing something it should not?
Three controls. It only has the application permissions you grant, so it cannot reach what it has not been given. It only acts within the rules and thresholds you configure, and anything outside them is handed to a named person. And every action is logged, so you can review what it did and tighten the rules. Most clients begin in propose-only mode and widen autonomy gradually.
Does it work with our applications, including older ones without APIs?
Modern applications are connected through their APIs. Older systems without APIs are handled through controlled interface automation, which is slower and more fragile, and we say so during setup. Each digital employee logs in with its own credentials, so IT keeps full visibility and can revoke access at any time, exactly as with a human user.
What happens when the digital employee meets a case it has not seen?
It stops and escalates. The handover goes to the person you named for that task, with the request, the records it found and the reason it paused. The person resolves the case, and if it should have been handled automatically, we adjust the rules. The design principle is that uncertainty becomes a question for a human, never a guess written into your systems.
How is AI Digital Employee priced and how quickly can one start?
As a subscription per digital employee, with onboarding covering the task definition, application connections and approval rules. A first digital employee on a well-understood task typically moves from definition to shadow mode in a few weeks, and to live operation once you are satisfied with the comparison. We do not publish list prices because the application connections differ so much between clients.
Explore AI Digital Employee with our team
Describe the task your team would most like to stop doing by hand and the applications it touches. We will show a digital employee at work, assess the fit and propose a first digital employee in propose-only mode.