Humint Labs® + Google Cloud
Google Cloud Partner delivering enterprise conversational and agentic AI on Vertex AI, Gemini Enterprise, and Contact Center AI.
Building Conversational and Agentic AI on Google Cloud
Humint Labs is a Google Cloud Partner, listed on the Google Cloud Partner Directory. We design and deploy enterprise conversational, generative, and agentic AI on Google Cloud, with production depth in Vertex AI, Gemini Enterprise, Vertex AI Agent Builder, Contact Center AI (CCAI), and Conversational Agents (Dialogflow CX). Enterprise teams across banking, superannuation, retail, and insurance rely on us to take Google Cloud AI from pilot to production. Every engagement moves along our four-pillar framework, from GenAI & LLMs and AI Workflows through to AI Agents and full Agentic AI, so leaders can see where they stand today and what governed autonomy looks like next.
GenAI & LLMs and AI Workflows built on Vertex AI and Gemini Enterprise
AI Agents and Agentic AI orchestrated with Vertex AI Agent Builder
Enterprise contact-centre delivery on Contact Center AI (CCAI) and Conversational Agents (Dialogflow CX)
Listed on the Google Cloud Partner Directory
Modernising Legacy Customer Experience AI
Humint Labs modernises enterprise contact centres running on ageing conversational AI. That includes Dialogflow ES, the earlier generation of Google Cloud conversational AI, alongside legacy on-premises IVR and other third-party conversational AI platforms. We move these deployments onto Conversational Agents (Dialogflow CX), Vertex AI, and Vertex AI Agent Builder, preserving working call flows whilst adding generative natural language understanding, deterministic controls for regulated actions, and a clear path from automation to governed agentic AI.
Migration from Dialogflow ES to Conversational Agents (Dialogflow CX)
Migration from legacy on-premises IVR and other third-party conversational AI platforms
Modernisation onto Vertex AI, Gemini Enterprise, and Vertex AI Agent Builder
Where We Run Deep on Google Cloud
Our conversational, generative, and agentic AI expertise on Google Cloud delivers enterprise-grade customer experience.
Vertex AI
We build, evaluate, and deploy generative AI on Vertex AI in production, including model tuning, grounding, and MLOps for enterprise workloads with the governance regulated industries require.
Contact Center AI (CCAI)
We implement CCAI to automate and augment contact-centre interactions, combining virtual agents with agent assist and insights for measurable gains in handle time and customer satisfaction.
Conversational Agents (Dialogflow CX)
We design and build Conversational Agents (Dialogflow CX) for complex, multi-turn voice and chat experiences across enterprise channels, with state-based flow design and deterministic control.
Gemini Enterprise & Vertex AI Agent Builder
We design and ship agent orchestration on Gemini Enterprise and Vertex AI Agent Builder for large enterprises, building tool-using, multi-step agentic systems grounded in our production Vertex AI and CCAI experience.
The Questions Enterprise Leaders Ask Us
The four themes that decide whether enterprise AI reaches production on Google Cloud, and how we address each one.
Governed agentic AI
We take agentic AI from pilot to governed production on Vertex AI Agent Builder, with human override designed in from the start, so autonomy is earned capability by capability rather than switched on all at once.
Data readiness and grounded responses
We ground responses on Vertex AI Search and enterprise data, with clear retrieve-versus-act governance and deterministic, auditable responses wherever regulation requires them.
Customer experience protection
We increase deflection without sacrificing customer satisfaction or first-contact resolution, with clean virtual-agent-to-human handoff through Contact Center AI so complex cases reach a person with full context.
Enterprise scale and safety
We engineer for security, rollback, and safe-failure paths, delivered by lean senior teams that stay accountable from architecture through to run.
What We Validate Before Scale
Partner-page claims should stay tied to the engagement evidence available for review. These are the signals we make visible before recommending a Google Cloud AI rollout.
Release gates, rollback paths and operating ownership are defined before pilot traffic becomes production traffic.
Retrieval behaviour is checked against source freshness, entitlement filtering and answer traceability.
Containment, escalation, handover and customer-experience measures are reviewed against the actual journey.
Identity, audit, data residency and compliance controls are mapped to the workload before scale-up.
Outcomes Across Engagement Types
Representative outcome patterns from enterprise Google Cloud AI work, with specific claims carried by the relevant case study or delivery evidence.
Superannuation operations
Form processing, document extraction and member-service workflows where speed, accuracy and exception handling have to improve together.
Retail service journeys
Voice and chat automation that protects customer satisfaction by preserving context, detecting escalation triggers and handing complex cases to a person cleanly.
Insurance customer experience
Conversational AI across service channels, with governed answers, clear handover and measurable changes in handling effort and response quality.
Enterprise AI You Can Stand Behind
We run a hybrid architecture that keeps regulated actions deterministic and auditable, with generative AI providing natural language understanding on top rather than making unconstrained decisions. Human-in-the-loop review sits at every consequential step. On Google Cloud we align to platform controls, including Identity and Access Management, VPC Service Controls, Cloud KMS encryption, and Cloud Audit Logs. We also align to ISO 27001, SOC 2, the Australian Privacy Principles, and APRA CPS 234 expectations for financial services. Data can be processed and stored in the Sydney region, australia-southeast1, with PII redaction and Australian-only processing options.
Hybrid architecture: deterministic, auditable execution for regulated actions
Human-in-the-loop review at every consequential step
Identity and Access Management, VPC Service Controls, Cloud KMS, and Cloud Audit Logs
ISO 27001, SOC 2, Australian Privacy Principles, and APRA CPS 234 expectations
Australian data residency in australia-southeast1 (Sydney) with PII redaction
One grounding foundation
The same grounding layer can serve discovery, conversion, service and retention without duplicating retrieval policy four times.
Scroll diagram horizontally
Frequently Asked Questions
Your Guide to Enterprise AI
Generative AI, LLMs, AI Workflows, AI Agents & Agentic AI: a practical guide for executives navigating enterprise AI adoption.
Read the GuideCase Studies
Industry: Financial Services
Fraud detection with review controls
Delivery work for real-time fraud detection, false-positive control and review-team prioritisation in financial-services workflows.
Read moreIndustry: Healthcare
Triage support that gathers and escalates, and a clinician who decides
The design question was never how much of triage could be automated. It was which part of it must never be, and how the system behaves at the edge of what it is allowed to do.
Read more