NexGen/Practices/Agentic and generative AI

Agents that do the work, with controls.

We build AI agents that run inside your live workflows: reading documents, reconciling records, drafting responses and routing approvals. Every one ships with an approval step, an audit trail and an owner.

Led by
AI engineers paired with process specialists
Works on
Documents, transactions, knowledge, service
Controls
Human approval, audit trail, monitoring
First step
Process selection
The problem

The pilot worked. Then it stayed a pilot.

Most organisations have seen a convincing AI demonstration by now. Far fewer have an agent doing real work on a Tuesday morning. The distance between the two is not the model. It is integration with the systems of record, controls a risk function will sign, and a process owner who trusts the output.

We treat an agent as a member of the process, not a feature. It gets a defined job, access to only the data it needs, a human approval step wherever a decision matters, and a log of everything it did. Generative AI goes where it earns its place, and conventional automation goes where that is the better tool.

What we do

From the first use case to an agent your auditors accept.

Process selection and business case

We score your processes on volume, rules, data quality and risk, and pick the ones where an agent pays back.

Agent design and build

Agents for document intake, reconciliation, policy checks, drafting and routing, built on the model and platform that fit your environment.

Generative AI applications

Contract review, policy assistants, report drafting and knowledge search over your own documents, with sources cited.

Integration with your systems

Agents connected to the ERP, document stores, email and service tools through supported interfaces.

Controls and governance

Access limits, approval steps, audit logs, testing and monitoring, documented so that risk and audit can sign off.

Training and handover

Your team learns to run, measure and extend the agents. We hand over the code and the run book.

An agent is given one job, the data for that job and nothing else. It shows its work, stops where a person must decide, and logs what it did.

Agent running
Matching 1,284 invoices to purchase orders · 37 routed for approval · illustrative
How it runs

Four steps, each with something you can hold.

The right-hand column is what you have in your hands at the end of each step. We confirm timing in the plan, once we have seen the work.

  1. 01

    Select

    We pick one process with a clear owner and a measurable outcome.

    Business case
  2. 02

    Design

    We define the agent's job, its data, its limits and the points where a person approves.

    Agent specification
  3. 03

    Build and test

    We build against real data, test with the people who do the work today, and tune until they trust it.

    Agent in production
  4. 04

    Run and extend

    We monitor accuracy and exceptions, then extend to the next process.

    Performance report
What you have at the end
  • An agent in production on a real process
  • A control framework your risk function has signed
  • Time and error reduction measured against a baseline
  • Code, documentation and ownership with your team
  • A ranked list of what to automate next
Who does the work
  • AI engineers

    Design, build and tune the agents and the generative AI applications.

  • Process specialists

    People who have run the finance, procurement or HR process the agent joins.

  • Integration engineers

    Connect the agent to your systems of record, securely.

  • Governance lead

    Designs the controls and the evidence that audit will ask for.

Works alongside

Practices that often join this one.

Problems rarely respect a single domain. One engagement lead coordinates across practices, so you never manage our hand-offs.

Practice

ERP and business systems

Most ERP programmes stop at go-live.

Open the page →
Practice

Modelling, budgeting and forecasting

Finance specialists and planning-system engineers who build investment models, driver-based budgets and rolling forecasts on modern planning platforms, connected to your ERP so the numbers refresh without a rebuild.

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Practice

Websites and apps

Product designers and engineers who take a website, portal or mobile app from the first wireframe to the release, and look after it once it is live.

Open the page →
Contact

Talk to the AI practice lead. They will be on the first call.

Agent@nexgentechstrategy.com
Practice
Agentic and generative AI
Delivery
International
Client presence
Saudi Arabia