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// AI / AGENTIC AUTOMATION

AI that does the work, inside a fence you control.

Your clients have moved past should we do AI to make it run our processes. We build autonomous agents for procurement approvals, incident triage and onboarding, with guardrails, escalation and audit trails as standard. Every agent ships under your brand.

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// THE EXECUTION GAP

Plenty of clients are piloting agents. Few have scaled them.

Nearly two-thirds of enterprises are experimenting with AI agents in 2026, yet fewer than one in four have scaled them to production. The gap is widening between clients asking for autonomous workflows and the partners who can actually deliver them. Even strong pilots stall on three hard problems: process redesign, governance and guardrails, and multi-agent orchestration. The teams that get it right see thirty to fifty percent acceleration across finance close, procurement and case resolution. The rest stay stuck at the demo.

// CAPABILITIES

What we build into the agents.

01

Tri-Platform Agent Builds

Autonomous agents on the platform that fits the client's cloud and licensing: Vertex AI Agents with ADK on GCP, AWS Q Agents with Bedrock on AWS, or Copilot Studio with Azure AI Foundry for Microsoft 365 estates. No vendor agenda, just the right fit.

02

Bounded Autonomy by Default

Role-based permission scopes define exactly what an agent may do. Circuit-breaker logic halts execution on anomalies. Regulated clients in banking, healthcare and insurance cannot accept agents without these, so we ship them as standard.

03

Human-in-the-Loop Escalation

Configurable triggers route high-value or low-confidence decisions to a person: value thresholds, confidence scores and exception patterns. The agent runs the routine work and knows precisely when to hand back.

04

Multi-Agent Orchestration

Specialist agents delegate to sub-agents across A2A Protocol, LangGraph and AutoGen. A procurement workflow splits into a policy-check agent, a price-comparison agent and an approval-routing agent, parallelised without brittle glue code.

05

System Integrations

Native tool connections into Salesforce, ServiceNow, SAP and Microsoft 365, with memory management and prompt-security controls. The agent acts inside the systems your client's business already runs on.

06

Audit Trails & Agent FinOps

Every agent decision logged in a format auditors and compliance teams can actually read, plus per-task cost tracking so token spend stays visible as the agents scale across processes.

// TELEMETRY

The numbers behind governed autonomy.

171%
ROI reported on scaled agent deployments
65%
Cut in cycle time on automated processes
96%
Routing accuracy on triage and approvals
4wk
From blueprint to a working proof-of-concept
// Sources: enterprise agentic AI adoption studies 2026, EU AI Act Article 9
// COMPARISON

How the options compare.

What your client gets from legacy RPA, a single-platform vendor, or our team under your brand.

CAPABILITY
Traditional RPA
Single-Platform Vendor
Belico, Your Brand
Agent builds across GCP, AWS and Azure
Multi-agent orchestration (A2A, LangGraph, AutoGen)
Partial
Bounded-autonomy architecture as the default
N/A
EU AI Act Article 9 documentation included
Delivered under your brand
Agent FinOps with per-task cost tracking
Partial
// FAQ

Agentic automation, answered straight.

01 What is the difference between RPA and agentic AI?

RPA follows fixed rules: click this button, copy that field, paste it there. It breaks the moment the interface changes. An agent reasons about a goal, picks the right tools, and adapts to a situation it has not seen before. Agentic AI handles the unstructured judgment RPA cannot touch: incident triage, procurement decisions, document analysis. When the screen moves, RPA fails and the agent finds another path.

02 How do you stop an autonomous agent making a bad call?

Bounded autonomy, shipped by default. Role-based permission scopes set what the agent can do, configurable escalation triggers route high-value or low-confidence decisions to a human, circuit-breaker logic stops execution on anomalies, and a complete audit trail records every decision for compliance review. The agent is autonomous inside a fence you define, never beyond it.

03 Our client wants a proof-of-concept in four weeks. Is that realistic?

Yes. The Agent Architecture Blueprint is a two-week structured discovery that finds the highest-value candidate process and produces a deployment plan. Weeks three and four build the working proof-of-concept. We already know which shortcuts are safe and which are not, which is what makes the timeline hold.

04 Which platform should we use: Copilot Studio, Vertex AI Agents or AWS Q?

That choice is part of what we deliver. We match the platform to the client's existing cloud posture, licensing position and data residency rules, not to whichever product a vendor is pushing this quarter. Platform neutrality across the three clouds is a large part of why partners bring these projects to us.

05 How do agents stay compliant with the EU AI Act?

For agents in EU-regulated industries, Article 9 risk-management documentation is a standard deliverable: risk classification, human-oversight design, audit-trail architecture and the technical documentation the Act requires for high-risk systems. Getting this right is what keeps a client clear of fines that can reach seven percent of global annual turnover.

06 Can agents work across CRM, ERP and ticketing at once?

Yes. Multi-agent orchestration is core to how we build. Specialist agents delegate to sub-agents across different tools, so a complex process is decomposed and parallelised rather than wired together with fragile code. One workflow can reach across Salesforce, SAP and ServiceNow in a single run.

// DEPLOY

Tell us what your clients need.

A tri-cloud migration. A 200-site SD-WAN rollout. A security architecture before NIS2 hits. An AI system your client is asking about next quarter. We scope it, staff it, and deliver it under your brand. One conversation tells us if we are the right team.