Research & Analysis-Heavy Teams
Agents that gather information, cross-check sources, and synthesise findings — compressing days of research into hours.
Multi-Agent Systems
We design multi-agent systems where specialized AI agents — researchers, planners, executors, reviewers — collaborate under orchestration to handle complex tasks that a single model or workflow cannot reliably complete alone.
Specialized agent rolesInter-agent orchestrationShared memory & context
Who we build for
Who We Build Multi-Agent Systems For
Some problems are too broad for a single prompt or workflow. We design systems of specialised AI agents — each with a role, tools, and guardrails — that collaborate under orchestration to get complex work done end-to-end.
Operations Teams with Multi-Step Processes
Break complex processes into specialised agent roles — planners, executors, reviewers — that hand off work cleanly.
Product Teams Building AI-Native Features
Add agentic capabilities to your product — from coding assistants to autonomous task runners — built on your data and tools.
Enterprises Automating Cross-Department Work
Agents that work across systems and teams — pulling from CRM, finance, and support tools to complete tasks that used to need multiple handoffs.
Why Chayaniq for multi-agent AI
Multi-Agent System Benefits
Complex work needs more than one model call. Here is how we design systems of collaborating agents that handle real end-to-end tasks reliably.
Specialised Agent Roles
Researcher, planner, executor, and reviewer agents — each with a focused job, the right tools, and clear boundaries.
Inter-Agent Orchestration
A coordinating layer that routes tasks between agents, manages state, and resolves conflicts when agents disagree.
Shared Memory & Context Management
Agents share context and results without losing information or repeating work — even across long-running tasks.
Guardrails & Safety Boundaries
Each agent operates within explicit limits — what it can access, what it can change, and when it must ask for approval.
Tracing & Observability Across Agents
Full traces of every agent's reasoning and actions — so you can debug, audit, and improve the system over time.
Iterative Evaluation & Tuning
Eval suites that test the whole system, not just individual agents — catching regressions before they reach production.
Industries we serve
Multi-Agent Systems Across Industries
Complex, multi-step work looks different by industry — claims adjudication, supply chain coordination, clinical workflows. We design agent systems around the processes specific to your vertical.
Remote patient monitoring
- Real-time collection of wearables data
- Enhanced doctor-patient communication
- Comprehensive view of patient health data
- Data-driven report generation
- Seamless integration with existing systems
- Improved patient outcomes
Electronic medical records (EMR)
- Interoperability of medical data across departments
- HIPAA / GDPR compliant solutions
- Improved patient care
- Quick access to patient records, vitals, and lab results
- Enhanced security and privacy of patient health data
Document management
- Compliant documentation workflow
- Streamlined management of health information
- Integrations with existing systems for a 360° data view
- Secure file sharing and access management
Insurance verification
- Automated medical insurance eligibility
- Proactive identification of coverage issues
- API-ready and HIPAA-compliant
How we work
Our Process for Multi-Agent System Delivery
Systems of agents fail in different ways than single models — coordination, state, and runaway loops all need design attention. Our process treats the system, not just the agents, as the product.
Discovery & Task Decomposition
We break the end-to-end task into discrete roles — researcher, planner, executor, reviewer — and define what each one owns.
Architecture & Orchestration Design
We design the coordination layer — task routing, shared memory, and conflict resolution — before writing agent logic.
Agent Build & Tool Wiring
Each agent is built with its own tools, prompts, and permission scope — then wired into the orchestration layer.
Guardrail & Safety Testing
We test failure modes, runaway loops, and permission boundaries — with kill-switches verified before go-live.
Phased Deployment
We deploy with human approval gates on high-stakes actions, removing gates incrementally as trust builds.
Tracing & Continuous Tuning
End-to-end tracing across the system feeds into ongoing evaluation and tuning.
How we build multi-agent systems
Complex work needs more than one model call. We design systems of collaborating agents — each with a focused role — that handle real end-to-end tasks reliably.
We define researcher, planner, executor, and reviewer roles — each with a focused job, the right tools, and clear boundaries.
- Role definitions matched to your real workflow steps
- Tool access scoped per agent role
- Clear hand-off contracts between agents
Our stack
Our Multi-Agent System Technology Stack
Orchestration, memory, and tracing layers built for systems where multiple agents collaborate on a single task.
Models & Providers
- Anthropic Claude
- OpenAI GPT
- Google Gemini
- Open-source models
Agent Frameworks
- LangGraph
- AutoGen
- CrewAI
- Custom orchestrators
Shared Memory & State
- Redis
- Vector stores
- PostgreSQL
Tool & API Orchestration
- Custom tool servers
- Internal APIs
- Temporal
Evaluation & Tracing
- LangSmith
- Custom eval suites
- OpenTelemetry tracing
Compute & Hosting
- AWS Lambda
- ECS
- Docker
Perspectives
Ideas that pair with Multi-Agent Systems
Short reads from how we ship—architecture, product, and ops. Same themes as this service, different angles.
March 2026
Single Agent vs Multi-Agent: When Does the Complexity Pay Off?
Multi-agent systems aren't always better. A practical guide to knowing when one well-prompted agent is enough — and when you need a team of them.
Continue readingFebruary 2026
Designing Guardrails for Autonomous AI Agents
Permission scopes, approval gates, and kill-switches — the safety patterns every multi-agent system needs before it touches production data.
Continue reading
