AI agent development for work your business needs to control
An invoice needs checking against an order. A service request needs information from three systems. A customer update needs drafting, but a person must approve the commitment it makes. These are useful starting points for AI agent development because the work, the boundaries and the responsible team can be defined.
Talk to our team
Share a few details and we'll get back to you.
FI Digital scopes AI agents around business workflows and the systems that support them. We identify what the agent may read, what it may change and when it must ask for help. The first goal is a tested workflow that your team can evaluate and operate.
Choose a task with a measurable outcome
Start with a recurring activity whose current performance you can describe. How many items arrive, how long does handling take, where do exceptions occur, and what happens when a mistake is made? Those facts help distinguish a useful automation opportunity from an interesting demonstration.
Finance workflows with review built in
Scope invoice preparation and expense review around validation, exceptions and authorised decisions. Start with a bounded pilot and measure the complete handling process before expanding automation.
- 1Validation
- 2Exceptions
- 3Authorised decision
Decide where judgement stays with people
Define the action before building the agent
Illustrative workflow · Not a client architecture or performance claim
- 1Incoming taskAgreed service scope
- 2Check the boundaryInformation + permissions
- 3Permitted actionRecord the outcomeor
- 4Human decision or unresolved exceptionKeep the owner and context visible
Scope illustration • No client data or exact system architecture shown
An agent should have a defined operating boundary. Reading an approved knowledge base, preparing a draft and changing a financial record carry different consequences. We agree allowed actions, approval points and escalation rules with the people responsible for the process.
For consequential decisions, the workflow can present supporting information and request human approval before taking the next step. When information is incomplete or contradictory, it should follow an exception path. The specification should explain what happens when a reviewer is unavailable and who owns the unresolved work.
Connect to systems with explicit ownership
The integration design identifies the authoritative system for each record and the permissions needed for the task. It also covers duplicate requests, failed updates, rate limits and changes to source data. Credentials and production access are arranged through an agreed secure process.
We assess whether existing business rules or conventional automation can handle part of the process more reliably. AI may help interpret a document or prepare a response while deterministic checks control transaction values and required fields. The design follows the work rather than assuming every step needs a language model.
Evaluate the complete workflow
Testing should use representative tasks, difficult exceptions and cases where the agent should decline to act. We agree acceptance criteria before the pilot: what counts as a correct result, an acceptable referral or a failure that prevents release. A single accuracy percentage rarely describes all three.
The evaluation records the input, expected outcome, actual outcome and review decision. It should also assess completion time, cost per task and the effort required from reviewers. Changes to prompts, models or connected systems need an appropriate regression check against the accepted examples.
Make the deployment decision on evidence
The proposed pilot handover includes a workflow specification, integration and permission map, evaluation results, known limitations and a recommendation for the next phase. It should identify the work required before production, including monitoring, support and user training.
Data location is a design requirement to verify across model inference, storage, logs, backups and support access. We review the proposed configuration and contractual requirements with your responsible team. Selecting a UK cloud region alone does not establish that every component processes information only in the UK.
Agree the operating responsibility
Production support needs named owners, an escalation route and a way to pause the workflow. The agreement should distinguish software faults, source-system problems and changes in business policy. Coverage hours and service commitments are specified for the engagement.
Bring one workflow, the systems it touches and the person who can approve its outcome. We can then define a first assessment and the evidence needed to decide whether a pilot is worth funding.
Evidence from an Australian service engagement
For an anonymous Australian personal injury law firm, we built agents within Zoho Desk using the OpenAI API, Zia agents, custom scripts, RAG and MCP. The firm reported 70% autonomous resolution across approximately 800 incoming service tickets over six months. The implementation took six weeks to go live, with people involved for legal-advice enquiries. This is an Australian delivery reference, not a claim of a UK client or a standard outcome for another firm.
Frequently asked questions
001What makes an AI agent different from a chatbot?
An agent can use connected tools to perform an agreed sequence of work, while a chatbot may only answer a question. The distinction does not justify unrestricted access. A business implementation needs defined permissions, allowed actions, approval points and exception handling so the team can understand and control what the system does.
002Which process should we automate first?
Choose a recurring task with accessible information, a clear owner and an outcome that can be checked. Avoid starting with a broad instruction to transform an entire department. A bounded workflow makes it easier to establish the current effort, identify exceptions and evaluate whether automation improves the work sufficiently to justify expansion.
003Can an agent work with our existing CRM or ERP?
That depends on the interfaces, permissions and business rules available in your systems. We assess those dependencies during scoping. The design should identify the authoritative records, allowed updates and failure handling, including duplicate prevention. Access to an API does not by itself establish that an end-to-end workflow is ready for automation.
004Will the agent make decisions without human approval?
The permitted actions are agreed for the specific process. Some low-risk steps may run automatically; other actions may require a person to approve a draft or review supporting evidence. The specification should also define uncertainty, missing information and escalation, with a practical way to pause or reverse supported actions when necessary.
005How do you measure whether a pilot works?
We agree representative tasks and acceptance criteria before testing. Measures can include correct completion, appropriate escalation, serious errors, reviewer effort, task cost and completion time. Results are compared with the agreed baseline and documented limitations. A demonstration that handles a few favourable examples is not sufficient evidence for a production decision.
006Can you guarantee that an agent will never make an error?
No. The work is to understand failure modes, reduce their likelihood and control their consequences. Evaluation, restricted permissions, deterministic checks and human review can support that aim. The release decision should reflect the risk of the particular workflow, and the operating plan should include monitoring and a response when something goes wrong.
007Does a UK deployment keep all data in the UK?
The answer depends on the complete configuration and service terms. Model processing, storage, logs, backups and support access may have different locations. We map those flows against your requirements and verify the relevant services. A UK application server or billing address alone does not establish the location of every processing activity.
008What do we need for the first discussion?
Bring a description of one workflow, its owner, current systems and a few sanitised examples of ordinary and difficult tasks. Explain the volume, current effort and consequences of mistakes. Do not send production credentials or confidential records through the enquiry form; detailed information and access can be arranged through an agreed process.
Discuss an AI workflow assessment
Discuss an AI workflow assessment→Tell us what you'd like to automate
Share a few details and our engineering team will come back with an honest assessment.
- Reply within 1 business day
- Straight answer on fit, scope and approach
- No obligation, no sales script