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AI agents that do the work,with a human one step away.

Agents that read inbound tickets, WhatsApp messages, emails and alerts; decide what to do; act through your tools; and hand over to a person when they should — with logging, guardrails and a monthly report of hours saved and leads converted.

InboundWhatsApp · email · ticketsKnowledgedocs · FAQs · policiesAgentclassify · reason · act · logToolsCRM · ITSM · calendarHuman handoverexceptions · approvalsGuardrails · audit log · monthly outcomes (hours saved, tickets deflected, leads converted)Suzu Technology · AI Agent Automation · sheet 41not to scale
Fig. 41 — Agent architectureInbound → Knowledge → Agent → Tools
AI & development

What we do

We build agents the way we build infrastructure: with a defined scope, logging of every decision, rate limits, fallbacks and a human escalation path. The first workflow is usually the one your team complains about most — first-line support, lead qualification, report preparation, runbook execution.

We run lead-handling and support agents for our own businesses and for clients; they reply within seconds, update the CRM and know when to stop and ask a person.

Included
  • DiscoveryWorkflow mapping, data sources, exceptions, success metrics
  • Agent buildPrompting, tools, retrieval over your documents, guardrails
  • IntegrationsWhatsApp, email, CRM, ITSM, calendars, databases
  • Human-in-the-loopApproval steps, handover rules, review queue
  • OperationsMonitoring, logs, model updates, monthly outcomes report
How it runs

The engagement, step by step

01

Discover

Map the workflow, the data, the tools and the exceptions a human must handle.

02

Blueprint

Architecture, guardrails, integrations, success metrics and a fixed quote.

03

Build

Two-to-four-week build with staging, test cases and a human review loop.

04

Operate

Monitoring, logs, model updates and a monthly outcomes report.

Commitments

What we put in writing

Written into the blueprint before work starts. If a number is not here, ask for it — we put it in writing.

First delivery2–4 weeks for the first workflow
LoggingEvery action logged and reviewable
HandoverHuman takeover in one click, any time
ReportingMonthly: volume handled, deflection, hours saved
FAQ

Questions we get asked

Which models do you use?
Claude, OpenAI, Gemini or privately hosted open models depending on data sensitivity and cost; the workflow is model-agnostic.
Is our data used to train models?
No. We use APIs with no-training terms or private hosting, and your data stays in your systems.
What if the agent makes a mistake?
Scope, guardrails and approvals limit the blast radius; every action is logged, and a human can correct and retrain the behaviour.

Describe the manual process. We scope the first workflow and quote it.

Two-to-four-week first delivery with a measured before-and-after.