Why Teams of Agents Deliver Better Business Outcomes
01
Fragmented workflows cost ≈5 weeks of productivity per employee, annually. Every interruption burns 23 minutes of focus.
02
Generic LLMs plateau: domain-tuned neurology models score 85% vs 46% for generalized models.
03
Single agents require constant human babysitting.
conclusion
The answer isn’t bigger models — it’s smarter, specialized AI teams.
The Teams of Agents Engine
Parse
Coordinator agent decomposes your goal.
Assemble
Specialist agents spawn, using the best model for each task.
Execute
Agents leverage full system access — APIs, files, GUIs — to deliver outputs.
Review & Iterate
Coordinator loops quality checks until your spec is met.
Built for Complex, Real-World Tasks
Innovation
Agent-level Knowledge Bases
Hierarchical Memory
Multi-Model Mesh
What It Is
Each agent owns its context & prompt history
Nested agents pass only relevant state upward
Finance → GPT‑4o, Design → SDXL, etc
Why It Matters
Prevents token bloat, slashes cost
Automatic relevance and long-term recall
35–70% domain accuracy boost over generic models
Plug Into Your Existing Stack
Teams of Agents act directly across your stack via secure, audited sandboxes
Flexible Pricing for Every Team
Scale Your Own AI
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