Multi-agent systems with Google ADK, from prototype to production
Agent Development Kit is Google's open framework for building agents in code: explicit orchestration, typed tools and evaluation built in. We deploy it on Vertex AI Agent Engine and wire it to your business events through Confluent.
No commitment · 30 minutes · With a senior architect
- Version-controlled code, not settings in a UI
- Interoperable with MCP and A2A
- Managed deployment on Vertex AI Agent Engine
An agent you cannot evaluate is an agent you cannot ship
Building an agent that impresses in a demo takes an afternoon. Getting it to production demands what any critical system demands: version control, tests, traces and a way to know whether a change made it better or worse. ADK brings that engineering model to agent development.
Explicit orchestration
Sequential, parallel and hierarchical flows are declared in code, so system behavior reads and reviews like any other module.
Tools with a contract
Every tool declares its types and its scope. The agent never guesses what it can call or with which arguments.
Evaluation from day one
Test sets that measure the agent's full trajectory, not just whether the final answer sounds right.
No vendor lock-in
Gemini, open models or third-party models. The same code runs on Vertex AI, on another cloud or on your own infrastructure.
From a single agent to a multi-agent system
Design, build and operate agents with ADK, integrated with the systems you already run. We pick the runtime per case: Python to iterate fast, Go when volume calls for lower consumption and a lighter binary.
Design
- Breaking the use case down into agents
- Sequential, parallel and hierarchical patterns
- Memory model and session state
- Guardrails and limits on what agents may do
Build
- Agents and tools in Python or Go, whichever fits your stack
- Integration with your APIs and databases
- Tools exposed through MCP
- Agent-to-agent collaboration with A2A
Data and context
- Event consumption from Confluent
- RAG with real-time context
- Vertex AI Search and vector databases
- Context enrichment in Flink
Operations
- Deployment on Vertex AI Agent Engine
- Trajectory and response evaluation
- Traces, metrics and cost control
- Improvement cycles driven by production data
Three ways to work with us
From solution design to running your agents day to day.
- 2 to 3 weeks
Agentic solution design
We turn the use case into an agent architecture: which agent does what, which tools it needs, where the context comes from and how it will be evaluated.
Multi-agent system blueprint
- 6 to 12 weeks
Build and deployment
We develop the agents and their tools, integrate them with your systems and deploy them on Vertex AI Agent Engine or the environment you choose.
Agents in production and a trained team
- Monthly retainer
Evaluation and evolution
We measure quality, cost and latency against real production data, and tune prompts, tools and models on that evidence.
Monthly quality and cost report
What we build with ADK
Systems where several agents split the work and answer for the result.
Assisted risk analyst
One agent gathers the applicant's information, another checks it against credit policy and a third drafts the recommendation with its rationale. A person still makes the final call.
First-line technical support
The agent checks the real state of the subscriber's network, runs the diagnostics a technician used to run and escalates with the context already gathered when it cannot resolve the issue.
Inventory and replenishment operations
Agents watch for stockouts, propose store-to-store replenishment and raise the orders, with a human approving anything above a set amount.
Internal process automation
Processes that today cross several systems and several people are modeled as an agent workflow with typed tools and a trace of every step.
Agents that react to business events
Instead of waiting for someone to ask, the agent wakes up when the event it owns occurs and acts on the system that matters.
The platform that feeds these agents
Data Streaming with Confluent and IBM
Kafka, Flink and Confluent Cloud, implemented by the team that has been doing it in the region for seven years.
Explore specialtyAgents with IBM watsonx
watsonx Orchestrate, watsonx.ai and watsonx.governance for organizations that answer to a regulator.
Explore specialtyWant to build agents that survive production?
Book 30 minutes with a senior architect. We look at your use case and what it would take to ship it. No sales pitch.