AI Workflows
Multi-agent systems that solve complex problems. When one bot isn't enough, we build a team.
Orchestration over Isolation
Single AI chatbots are great for simple tasks. But real business processes are complex—they require research, reasoning, critique, and final drafting.
Our AI Workflows assign roles to different agents. One agent researches, another drafts, a third critiques for compliance, and a fourth finalizes. It's like having a digital department working in perfect sync.
Who needs AI Workflows?
Complex Operations
Businesses with multi-step processes that require decision-making at each stage.
Marketing Agencies
Teams needing to generate varied content types (blogs, social, emails) from a single strategy.
Research Firms
Organizations that need to synthesize vast amounts of data into coherent reports.
Product Teams
Automating user feedback analysis and feature specification writing.
/// The Aretis Ecosystem
Multi-Agent Systems (MAS) Architecture
Graph-Based Execution
We verify workflows using directed acyclic graphs (DAGs) where nodes represent agent actions and edges represent data dependencies.
Consensus Protocols
For critical decisions, we implement voting mechanisms where multiple agents must agree on an output before it's finalized.
Inter-Agent Communication
Agents communicate via a structured shared memory, allowing them to pass context and "thoughts" to one another seamlessly.