AI agent development from an existing, configurable foundation

AI agent development connects model-based reasoning with tools and a defined workflow. AI agents are useful when a task needs several steps, changing information or coordinated specialist roles. The design must also specify where deterministic software, a simple automation or a person should make the decision. More agents do not automatically produce a better service.

Our developed GINOP Marketing Agent Set

HolisticRM has already developed its GINOP marketing-agent core. For a client assignment, we configure that foundation around the required sources, questions, tools and review responsibilities. The Marketing Agent Set brings together specialist work on research, planning, content, customer decisions and review. The AEO/GEO agent is a concrete application: collected answers and tool outputs feed source checks, tailored reporting and a prioritised content or technical backlog.

For an AEO finding, the input records the question, audience, language, search surface, model/version where available, run time and approved product facts. The output records the observed answer, cited sources, factual discrepancy, proposed action, owner and review status. The next content specialist receives that evidence, not an unexplained instruction to “improve visibility”. A repeat run retains comparable conditions and discloses material changes.

Choose agents by responsibility, not by the number of bots

A single assistant can be sufficient for a bounded question. Specialist agents become useful when tasks need different information, checks or approval boundaries. Before adding another role, identify its input, output and failure condition. Decide whether a deterministic function would perform that step more reliably or cheaply.

Existing platforms and client tools can supply capabilities. We assess their interfaces, access and evidence quality before treating them as a working integration. The developed core is real; a new customer’s connector, access model and external-action permission still require configuration and testing. No external publication or customer contact follows merely because an agent has drafted an output.

Choose the approach that fits the decision

Map evidence, tools and approval handovers

For an AEO workflow, identify the products, prompt set, approved facts and report owners. For a marketing launch, identify the research sources, draft outputs and publishing authority. List each external action separately from read-only research so permission is designed into the configured workflow.

Configure the developed core for one useful workflow

1. Select only the specialist roles needed for the agreed output and define their handovers.
2. Connect approved sources and tools; record which adapters have actually passed access and behaviour checks.
3. Replay normal, conflicting-source and unavailable-tool cases, including explicit escalation.
4. Review complete outputs with the owner before allowing broader execution or additional responsibilities.

Measure reliable task completion

For the AEO application, assess source-linked findings accepted by a reviewer, correction effort and the cost of producing a comparable monitoring run. For a content workflow, measure a usable brief and approved draft, not the number of generated words or agents invoked. Evidence records make mistakes easier to diagnose.

Sample: an illustrative evaluation plan

Sample — illustrative scenario, not a client result. For illustration, test a product-content workflow on 50 replayable requests: 30 ordinary tasks, 10 conflicting-source cases and 10 unavailable-tool or permission failures. Require source-linked findings and visible escalation for unresolved facts. Track accepted outputs, correction minutes, tool cost and any unauthorised-action attempt. These are Sample cases; they do not describe a completed client benchmark.

For the wider choice of model and delivery partner, see our AI development guide. Its agency-selection questions help compare complete proposals.

What you receive

A workflow and permission map, configured specialist roles, tool-connection register, replayable test cases and an evidence-bearing report format. The delivery specifies escalation, approval, audit records, running-cost visibility and support responsibilities. A connector is listed as operational only after its required access and behaviour have been tested.

Questions buyers ask

Can we connect existing tools?

Yes, subject to available interfaces, access permissions, terms and practical testing. An integration is validated for the specific assignment.

Does every action need approval?

The project defines approval according to consequence and reversibility. Low-risk retrieval and high-impact external actions can have different permissions.

Do you already have an agent core?

Our GINOP marketing-agent core is developed. We configure and evaluate client-specific questions, tools, reporting and controls rather than start every engagement from zero.

The AEO/GEO agent is one focused application of this capability. It connects existing tool outputs with tailored evaluation and reporting. Explore relevant industry applications or our AI development approach.

Discuss your AI agent project. Bring a short, non-confidential description of the decision, current process and available data.