Google Cloud builds the agent runtime.
Lyzr takes it to production.
For CIOs and GSI partners standardising on Vertex AI and Gemini — Lyzr is the production layer that turns agent prototypes into governed, observable, continuously improving enterprise software. Your data stays in your GCP environment. Your models stay on Vertex AI. Lyzr connects it all and ships it.
Behind the scenes: How Lyzr builds enterprise AI on GCP
Most agents never make it past the prototype
Vertex AI and the ADK are exceptional at what they do. The challenge every delivery team faces is what happens next: getting from a working proof of concept to a governed, observable, production-grade agent that a regulated enterprise can actually run. That gap — between “it works in the demo” and “it runs in production” — is where most agentic AI programs stall. Lyzr is built specifically to close it, running natively inside your GCP environment alongside everything Google provides.
Without Lyzr: 14 platforms to stitch together.
14 separate platforms to stitch together: orchestration, vectors, memory, observability, guardrails, CI/CD, UI — each with its own security review.
With LyzrOne platform, one security model, one audit trail — running inside your GCP VPC, natively integrated with Vertex AI and BigQuery.
Without Lyzr: agents stall in prototype.
Agents reach production less than 30% of the time. The rest stall in prototype, waiting for infra that never gets built.
With Lyzr85% of Lyzr-backed projects reach production. Simulation, CI/CD, and governance are built in — not bolted on at the end.
Without Lyzr: each engagement rebuilds the stack.
Each client engagement builds its own production stack. Months of bespoke work before any agent goes live.
With LyzrA reusable agent factory across every client. Build the production layer once on Vertex AI. Deploy it across your entire book of business.
Google Cloud builds the foundation. Lyzr runs what’s built on it
Two platforms, one complete picture. What Google handles natively — and what Lyzr brings alongside it, inside your GCP environment.
| Capability Area | Google Cloud handles | Lyzr brings alongside it |
|---|---|---|
| Model & Runtime | Vertex AI, Gemini, Model Garden, Model Armor, Vertex Responsible AI — the deepest model layer in the industry | Routes Gemini only for the work that needs it. Six Sigma architecture lets smaller, cheaper models do routine tasks — lowering inference TCO without sacrificing quality |
| Agent Building | Vertex AI Agent Builder and ADK — powerful, code-first tools for engineers wiring foundation models into agentic systems | SuperFlow canvas lets business users design and ship agents without code. Architect enables natural-language agent building on top of ADK and any framework |
| Data & Grounding | BigQuery for analytics, AlloyDB and Firestore for persistence, Vertex RAG Engine for retrieval | Agentic RAG + GraphRAG that reasons across heterogeneous sources. Natural-language to SQL against BigQuery. Cognis persistent memory at 92.4% LongMemEval accuracy |
| Deployment & CI/CD | GKE, Cloud Run, Compute Engine — world-class compute infrastructure for running agents at scale | A real agent CI/CD pipeline: non-prod → pre-prod → prod promotion with approvals, versioned releases, and instant rollback per release — today, not on a roadmap |
| Safety & Quality | Model Armor and Vertex Responsible AI on every model call — policy enforcement at the inference layer | ASIM simulation engine — test agents against thousands of real-world scenarios before they touch production. Catch failure modes before users do |
| Cross-Vendor Governance | Robust observability and IAM within GCP — best-in-class within the Google Cloud environment | One control plane across Vertex AI Agent Builder, Agentspace, Agentforce, ServiceNow, Databricks, and custom agents. One entitlement model. One audit trail. Every vendor. |
| Continuous Improvement | Logging, monitoring, and cost attribution through Cloud Logging and BigQuery | Improvement Engine: RL-based drift detection that identifies when agent behaviour shifts from intent — and corrects it automatically, without a ticket or a sprint |
Nothing in Google Cloud gets replaced.
Everything gets connected
Lyzr deploys inside your GCP VPC. Vertex AI stays primary. Your data never leaves your perimeter. Lyzr adds the production layer that sits above — and extends to every other agent system you run.
Vertex AI agents stay in Vertex AI. Gemini stays primary. Lyzr connects your Google Cloud agent layer to the rest of your enterprise — adding orchestration, memory, simulation, and governance across every platform you run, without any data leaving your perimeter.
From a single prompt to a governed, grounded, traced answer
Every customer request walks the same path. Each step touches specific Lyzr modules and the GCP services that back them. Nothing leaves the VPC.
Request arrives
Lands on your customer-facing app deployed on Cloud Run. Forwarded to the Agent Service inside the platform.
Cloud RunSafety screening
Model Armor and Vertex Responsible AI screen for PII, injection, jailbreak, and policy violations before any reasoning begins.
Model ArmorAgent invokes Gemini
Inference runs on Vertex AI inside the VPC. ADK agents handle specialised reasoning. No data egress.
Vertex AI · GeminiRetrieval and memory
RAG Service retrieves from Qdrant and Vertex RAG Engine. Cognis reads prior context. Natural-language SQL runs against BigQuery.
BigQuery · CognisTools and integrations
200+ integrations available through the MCP Registry. Any REST API addable as a tool without code.
MCP RegistryEvery call logged
Token-level cost attribution. ASIM picks up the run for regression. The Improvement Engine converts edge cases into the next simulation suite.
ASIM · Improvement EngineEntitlement enforced
Runtime policy evaluation against your IdP on every call. Fine-grained control over what every agent can read, write, and trigger.
Entitlement PolicyAgents get better
Drift detected automatically. RL-based corrections fed back through the Improvement Engine. Agents that compound in quality over time.
Continuous ImprovementFor the two people who have to make this work
Full agent governance without leaving your GCP perimeter.
- Your data stays in your GCP VPC or on-prem. Lyzr deploys inside your boundary. No data egress, no shadow tenancy, no compliance conversation you weren’t expecting.
- Time to production cut from quarters to weeks — with a CI/CD pipeline your security and compliance teams already understand, not a bespoke one built per engagement.
- One governance model across your entire agent system: Vertex AI Agent Builder, Agentspace, Agentforce, ServiceNow, Databricks. One audit trail. One entitlement model. One place to look.
- Lower inference cost: Gemini and Vertex AI reserved for the high-stakes, long-context work they’re built for. Six Sigma architecture patterns put smaller, cheaper models to work everywhere else.
Turn every Vertex AI engagement into a reusable delivery practice.
- Higher margin per Vertex AI engagement — the production layer is no longer bespoke custom work each time. Build it once on Lyzr. Deploy it across every client in your book.
- Commit to production SLAs on agentic engagements with confidence. Simulation, CI/CD, and continuous improvement are built into the platform — not something you have to engineer per project.
- A defensible joint-GTM story with Google account teams. Lyzr is additive to Vertex AI and the ADK — it strengthens the Google position, not competes with it.
- Faster pivot from advisory revenue to managed-service revenue. A real platform underneath the offering changes the commercial model of every engagement you run.
Enterprise-ready on day one · VPC-native deployment
Google Cloud and Lyzr, better together.
Architecture reviews are scoped to your current GCP footprint, with concrete recommendations for where Lyzr brings the most leverage in the first ninety days. A working reference deployment in your environment within four weeks.