Google builds the agents.
Lyzr puts them in production.
One control plane for every agent in your Google Cloud estate, and every agent outside it.
For CIOs and global SI partners standardising on Vertex AI, Gemini, and the ADK, Lyzr is the production layer that turns agent prototypes into governed, observable, continuously improving software. Your data stays in your GCP VPC. Your models stay on Vertex AI. Your grounding stays in BigQuery. Lyzr adds what Google does not.
Google gives you world-class primitives and a world-class model runtime. What sits between proof of concept and production is a different category of software.
Vertex AI
Foundation models, the Model Garden, embeddings, the RAG Engine, Model Armor, and Vertex Responsible AI. The deepest model-layer offering in the industry, served on Google’s infrastructure with native ties to BigQuery, AlloyDB, GKE, and Cloud Run.
Vertex AI Agent Builder + ADK
Code-first Agent Development Kit and the building blocks engineers use to wire foundation models into agentic systems. Powerful, Google-native, and aimed squarely at data scientists and developers.
The missing layer
Speed of development, agent memory and retrieval at enterprise quality, simulation and continuous improvement, governed CI/CD, entitlement policy, drift detection, and one place to see every agent across every stack you run.
One platform on top of Google Cloud — not fourteen tools stitched together.
Building a production agent on Vertex AI alone typically means standing up around fourteen separate platforms: LangChain for orchestration, Weaviate for vectors, Mem0 for memory, Arize and LangFuse for observability, custom guardrails, a custom UI, a CI/CD pipeline. Every one is an integration, a security review, and something to keep in sync. Most projects never make it past the prototype.
Lyzr collapses that fragmented stack into one platform with a single security model, single audit trail, and single development experience — running inside the customer’s GCP VPC, integrating natively with Vertex AI, grounded against BigQuery, gated by Model Armor and Vertex Responsible AI on every model call.
Lyzr projects reach production. Industry average is under 30%.
From blank canvas to a deployed, governed, simulated agent.
Platforms collapsed into one agent production infrastructure.
Pre-built agents and tool integrations out of the box.
Lyzr layers on top of Google Cloud. Nothing gets replaced.
Your data stays in your GCP VPC. Models stay on Vertex AI or any model you serve through the Model Garden. Native agents stay in Vertex AI Agent Builder. Lyzr sits above as the production layer, wrapped end-to-end by a Central Control Plane.
Build on Vertex AI, then layer Lyzr’s production capabilities. Google models, Google runtime, your data, your VPC.
Your data stays in Google Cloud.
Lyzr deploys in your VPC or on-prem. No data egress, no shadow tenancy.
Your models stay on Google.
Vertex AI and the Model Garden serve every call. Model Armor and Vertex Responsible AI remain in the safety path.
Your agents stay where they are.
Vertex AI Agent Builder and ADK agents run unchanged. Lyzr orchestrates above them through Proxy Agents.
One pane of glass across every agent in your estate.
Agents will not live in only one stack. Your enterprise will accumulate them in Vertex AI Agent Builder, in Google Agentspace, in Salesforce Agentforce, in ServiceNow, in Databricks, and in custom-built systems. Lyzr’s Agent Gateway and central registry give you one place to discover, govern, and observe them all. One entitlement model. One audit trail. One observability layer.
Wherever the agent runs, the control plane is the same.
Dev → staging → prod, built in.
What you tested in staging is exactly what runs in production. No bespoke CI/CD glue.
Native rollback per release.
Every deployment is versioned and instantly reversible.
Multi-cloud failover.
Switch GCP ⇄ AWS or to on-prem without touching the agent.
From a single prompt to a governed, traced, grounded answer — across the whole stack.
Every customer request walks the same path. Each step touches specific Lyzr modules and the GCP services that back them. Nothing leaves the VPC.
- 01
Entry
Request lands on the customer-facing app deployed on Cloud Run. Forwarded to the Agent Service inside the platform.
- 02
Dispatch
Agent Service consults the Agent Registry — the versioned source of truth for every agent, tool, memory layer, and guardrail in the workspace.
- 03
Gate (inbound)
RAI Service runs Lyzr’s pre-flight checks and routes the prompt to Model Armor + Vertex Responsible AI for PII, injection, jailbreak, and policy screening.
- 04
Reason
The agent invokes Gemini through Vertex AI. ADK agents sit alongside for specialised reasoning. All inference inside the VPC; no data egress.
- 05
Ground
The RAG Service retrieves from Qdrant and the Vertex RAG Engine. Data Query translates natural-language questions into SQL against BigQuery.
- 06
Remember
Lyzr Cognis reads prior turns and persists new context — AlloyDB for durable state, Firestore for session state.
- 07
Act
Tools invoked through the Tools / MCP Registry. 200+ integrations available. Any REST API addable as a tool without code.
- 08
Observe & learn
Every call logged with token-level cost attribution. ASIM picks up the run for regression. The Improvement Engine converts new edge cases into the next simulation suite.
What you get when you layer Lyzr on Google Cloud.
Adopt the full platform or pick the modules that close your specific gaps. Every module is interoperable with native Google components and with Lyzr’s open agent protocols.
Build faster
Architect
Vibe coding for enterprise agents. Build agentic workflows in natural language, then swap frameworks with a single command via GitAgent.
SuperFlow
The drag-and-drop canvas where business users design agents — triggers, prompts, tools, memory, conditionals — and ship to production with one click.
Lyzr AgentStudio
The full-stack workspace containing SuperFlow, Architect, Registry, and Simulation in one workspace deployable inside your VPC.
Run smarter
Lyzr Cognis
Advanced memory for enterprise agents. Leads both LoCoMo and LongMemEval benchmarks.
Agentic RAG + GraphRAG
Plan, route, and reason over heterogeneous enterprise data — including knowledge graphs over BigQuery and Drive.
Six Sigma Architecture
Use smaller, cheaper models and still get frontier-model capability. Lower inference TCO.
Govern at scale
Agent CI/CD
A real pipeline. Approvals from security, compliance, and line-of-business owners. Versioned releases, automated rollback, full audit history.
Agent Entitlement Policy
Fine-grained policy on what every agent is permitted to read, write, and trigger, evaluated at runtime against your IdP.
Continuous Improvement Engine
Monitor logs, detect drift, and feed improvements back through automated reinforcement learning.
Agent Simulation Engine (ASIM)
Simulate scenarios at scale before agents touch production traffic. Stress test reasoning, validate against business outcomes.
Unify the estate
Central Control Plane
One console for every agent — Lyzr, Vertex AI Agent Builder, Agentspace, Agentforce, ServiceNow, Databricks, or your own.
Agent Gateway
Single ingress for all agent traffic, with policy enforcement, rate limiting, observability, and entitlement applied uniformly across vendors.
Multi-vendor Registry
A canonical inventory of every agent in production — ownership, lineage, dependencies, risk posture.
What this means for the people responsible.
For the CIO
- ·Time to production cut from quarters to weeks, with a CI/CD pipeline your security and compliance teams already understand.
- ·Data sovereignty preserved. Lyzr runs in your GCP VPC or on-prem. No data leaves your boundary.
- ·One governance model across every agent stack, instead of five separate audit trails.
- ·Lower inference TCO via Six Sigma architecture patterns that let smaller models do frontier-class work.
- ·Drift, hallucination, and policy violations caught and remediated continuously — not in postmortems.
For the GSI partner
- ·Higher delivery margin per Vertex engagement, because the production layer is no longer bespoke each time.
- ·A reusable agent factory across customers. Build patterns once, deploy them across accounts.
- ·Faster pivot from advisory revenue to managed-service revenue, with a real platform underneath the offering.
- ·A defensible joint-GTM story with Google account teams, positioned as additive rather than competitive.
- ·Confidence to commit to production SLAs on agentic engagements, backed by simulation and continuous improvement.
Enterprise-ready from day one.
VPC-native deployment · SOC 2 · HIPAA · GDPR · ISO 27001 · SSO · RBAC · Audit logs · VPC-SC · CMEK · Google Cloud enterprise security controls
Customer data never leaves the perimeter.
Bring Lyzr into your Google Cloud AI program.
Architecture reviews are scoped to your current GCP footprint, with concrete recommendations for where Lyzr modules add the most leverage in the first ninety days. No slideware. A working reference deployment in your environment within four weeks.
Where Vertex ends, Lyzr begins. On infrastructure you already own.