What is Google's Gemini Enterprise Agent Platform?

Gemini Enterprise Agent Platform is Google's enterprise platform for building, scaling, governing, and optimizing AI agents in production. It includes Agent Studio, ADK, Memory Bank, Agent Sandbox, Agent Registry, Agent Gateway, and Model Armor, with access to 200+ models through Model Garden including Gemini, Anthropic Claude, and leading open-source models.

What does Google Cloud Select Service Partner mean?

Google Cloud Select Service Partner is a validated specialization for partners with proven expertise to design, build, and run agentic solutions on Gemini Enterprise Agent Platform. HatchWorks AI holds this status alongside Anthropic certification and Databricks Validated Data Partner status.

How is GEAP different from copilots?

Copilots give humans a faster tool. GEAP gives the company a new operating layer where agents handle coordination, lookups, and cross-functional work that used to require layers of management, with verifiable identity, governed access, and continuous optimization.

What are HatchWorks AI's three GEAP offerings?

Agent Platform Foundation (GEAP environment setup with governance, security, IAM), Purpose-Built Agents (production agents for sales, finance, support, engineering), and Company Intelligence Layer (unified retrieval across CRM, data warehouse, code, tickets, and operational systems).

Which AI models can HatchWorks AI deploy through GEAP?

Through Google's Model Garden, HatchWorks AI can deploy over 200 models including Gemini, Anthropic Claude, Meta Llama, Mistral, and leading open-source options. As a Anthropic-certified partner, we have particular depth on when to use Claude versus Gemini versus open-source for each job.

How fast can a production agent ship with HatchWorks AI?

Through our GenDD methodology and Agent Garden templates, production-grade agents typically ship in days to weeks, not quarters. Foundation engagements set up the platform first; agent engagements deliver working agents to production with continuous evaluation built in.

HatchWorks AI on Google Cloud | Build the Intelligence Layer Your Business Runs On

Most companies gave their teams AI subscriptions. The leaders are building an AI operating layer.

Individual AI usage produces individual productivity. An intelligence layer connects your systems, gives agents real context, and makes the business itself queryable. That's the unlock Google built Gemini Enterprise Agent Platform to enable.

We help you build it.

Build

Scale

Govern

Optimize

4–6 weeks Discovery phase

01 Phase 01 of 03

Intelligence Layer Strategy

A clear-eyed plan for what your intelligence layer needs to do, what it connects to, and what it costs to build.

My team is using AI everywhere, but it’s not adding up to anything. I need a real plan for what we’re building, not another assessment.

We start by mapping where AI value is trapped inside your business: the systems that aren’t talking, the workflows where context dies, the agents you could be building but aren’t. Then we deliver an architecture, an opportunity map, and a business case your leadership team can fund.

What you get

Current-state assessment of AI usage, systems, and data sources
Workflow discovery and agent opportunity map
Reference architecture for your intelligence layer
Security and governance review
Phased roadmap with business case for funding

3–5 months Build phase

02 Phase 02 of 03

Architecture and MVP Build

A working intelligence layer connecting your priority systems, with the first set of governed agents running on top.

I have a strategy. Now I need someone who can actually build this without a multi-year program.

We build the first version of your intelligence layer on Gemini Enterprise Agent Platform: priority integrations connected, permissioning in place, governance live, and a focused set of agents doing real work. Designed to prove the model and create internal pull for the next phase.

What you get

Intelligence layer architecture deployed on Gemini Enterprise Agent Platform
Priority system integrations (CRM, data warehouse, knowledge base, comms)
Permissioning, access model, and governance configured to your standards
First set of high-value agents in production with eval and observability
Working internal proof that creates demand for the next phase

Ongoing Scale phase

03 Phase 03 of 03

Expansion and Operating Model

More systems connected, more agents in production, and the operating model that makes the intelligence layer durable.

The MVP works. Now I need to scale this without it becoming ungoverned sprawl.

We extend the intelligence layer across more of your business, stand up additional agents, and put the operating model in place: ownership, governance, evaluation standards, and the continuous improvement loops that make AI compound instead of decay. This is where the intelligence layer becomes how the company actually runs.

What you get

Expanded system integrations across the business
Additional agents tuned to your highest-leverage workflows
Evaluation, observability, and continuous improvement standards
Internal operating model for AI ownership and governance
Change management and enablement to bring the organization with you

Publications

Build the intelligence layer your business runs on.

Most companies gave their teams AI subscriptions. The leaders are building an AI operating layer.

One platform to build, scale, govern, and optimize agents.

Build

Scale

Govern

Optimize

No lock-in.

Start with proven patterns.

A three-phase journey, not three products.

Intelligence Layer Strategy

Architecture and MVP Build

Expansion and Operating Model

The partner credentials to build it. The methodology to deliver it.

Google Cloud Select Service Partner

Anthropic Certified Partner

Databricks Certified Partner

Let's get to work.

Start with a Strategy Session