AI AGENT ORCHESTRATION

Complex AI. Clear Control.

watunga helps teams orchestrate specialized AI agents, reusable tools and multi-step workflows — and keep control over every outcome.

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// Illustrative example — agent orchestration
from watunga import Orchestrator, Agent, Tool
const researcher = new Agent('Researcher')
const analyst = new Agent('Analyst')
const flow = new Orchestrator([researcher, analyst])
flow.run('quarterly-report')
// Status: 2 agents active, 5 steps completed (example)

What watunga does

From isolated agents to coordinated systems.

Connect specialized agents, tools and knowledge into workflows you can inspect, adapt and integrate.

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Orchestrate

Coordinate multi-step work across specialized agents and teams.

Integrate

Connect tools, data sources and existing systems into one workflow.

Observe

Inspect execution, tool calls and outcomes at every step.

Govern

Define controls, routing policies and boundaries for every agent.

Two ways to work with us

Platform

Build and compose AI agent systems with reusable capabilities.

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Engineering services

Design architecture, integrate systems and develop custom solutions.

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Built on real engineering

Not a pitch deck. Working systems.

The architecture behind watunga is informed by real agent-driven products already running in production and research settings.

Corpus Analyzer

Agent-driven medical AI platform for image analysis and diagnostic support.

Corpus Core SaaS

Productized, reusable infrastructure for agent-based applications.

Clinical Skills

Specialized agent skills and tools for healthcare and research workflows.

Philosophy

Complexity Behind Glass

Transparency and control are not afterthoughts — they are the foundation of watunga. Agent decisions, tool calls and outcomes stay visible and reviewable.

See the reasoning

Follow each agent's plan, decisions and delegations step by step, in plain language.

Transparent tool calls

Every tool call and external interaction is logged with its parameters and response data.

Structured telemetry

Every run records the model, selected agents, tools used, latency and knowledge sources.

Full audit trail

Messages, decisions and state changes are persisted and reviewable for compliance and debugging.

Complex systems do not require opaque operations. With watunga, the sophistication is in the architecture — the glass is always clear.

For developers

Start where your workflow already lives.

Model-agnostic orchestration, the Model Context Protocol (MCP), and containerized deployment — built for teams who ship.

Multi-provider

Switch between OpenAI, Azure OpenAI, Anthropic and Google models at runtime.

MCP-native

Connect tools and data sources via the Model Context Protocol.

GitHub-friendly

Agent configs and skills are version-controlled, reviewable artifacts.

Documented

Quickstarts, architecture references and runbooks for every component.

View developer resources

Enterprise & deployment

Governance you can verify, not just trust.

Deployment, access control and routing are explicit and configurable — not hidden behind a black box.

Flexible hosting

Run on your cloud provider or virtual private server — no lock-in to a single environment.

Access control

Define which agents, tools and data sources each role can reach.

Routing policies

Choose how work is delegated: direct, skill-based, or always-delegate coordination.

Compliance-ready workflows

Supports sensitive-data handling patterns such as automated anonymization where required.

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About

The Builders

watunga — from Swahili wa-tunga, meaning "the creators" or "the builders." We build intelligent systems that create value.

Our Mission

Help teams turn complex, multi-step AI workflows into coordinated, maintainable systems — from research and analysis to automation.

Our Approach

Full transparency and control. Agent decisions, tool calls and outcomes stay visible and reviewable. We call it "Complexity Behind Glass".

Built to Run

Deployed on cloud providers or virtual private servers, with explicit access control and routing — ready for real workloads.

Read more about our story →

Insights

Latest from the blog

View all posts
Agent EngineeringMay 15, 2026

Designing Effective AI Agent Swarms: Architecture Patterns

Learn the key architectural patterns for building collaborative AI agent swarms that communicate, delegate, and execute complex missions autonomously.

Tool DevelopmentMay 8, 2026

Building AI Agent Tools with Structured Outputs

Learn how to create powerful, type-safe tools for your AI agents using Structured Outputs — no complex programming required.

Prompt EngineeringApril 28, 2026

Full Prompt Control: Why Transparency Matters in AI Agents

Learn why full visibility and editability of prompts is critical for building trustworthy, controllable AI agent systems.

Have a workflow worth rethinking?

Bring a real problem. We'll help you identify the right architecture, integrations and next steps.

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watunga

FAQ

Common questions

What does watunga actually orchestrate?

watunga coordinates specialized AI agents and tools around a shared task — delegating work between agents, grounding answers in selected sources, and generating shareable outputs from the result.

How does watunga differ from a single chatbot?

Instead of one general-purpose assistant, watunga routes work between specialized agents using configurable coordination modes — direct answers, skill-based delegation, or broader team delegation with source-grounded retrieval.

Can I see what an agent actually did?

Yes. Every run records structured telemetry — the model used, which agents were selected, which tools were called, latency, and the knowledge sources referenced — so you can review and debug every step.

Which AI model providers are supported?

watunga is model-agnostic. You can configure and switch between providers such as OpenAI, Azure OpenAI, Anthropic and Google at runtime, without changing your workflow logic.

How does watunga connect to our existing tools?

Through the Model Context Protocol (MCP) and dedicated connectors, watunga integrates with knowledge sources and business tools such as document storage, collaboration platforms and version control.

Is watunga ready for production use?

The underlying orchestration approach already runs real workloads, including multi-agent coordination, source-grounded retrieval, and structured output generation. Enterprise deployment specifics depend on your environment — talk to us about your requirements.

Contact

Get in touch

Have a workflow worth rethinking? Contact us for a free consultation and discover how watunga can support your team.

Address

72202 Nagold
Germany